P R E F A C E

Since its inception in 1998, Richard Seewald’s name was synonymous with the Sound Foundation Through Early Amplification Conference. In concert with other leaders in pediatric audiology, Richard brought together international experts in childhood hearing loss with the goal of capturing our current state of knowledge in assessment and intervention, and to identify those areas for which we needed further study. These conferences have developed into the “home” conference for many of us who have dedicated our careers to working with and for children with hearing loss and their families. Every three years we spend a few days immersed in pediatric assessment and intervention via lectures, panels, and, most importantly, conversations with our colleagues from around the world. We then return to work refreshed with new designs for our practice and research. Indeed, these conferences have always hit the spot!

Richard noted in the preface to the first Proceedings 15 years ago, “By stating that we should identify permanent hearing loss by 3 months of age implies that, once the identification has occurred, we know how to do the rest. It also implies that all of the required assessment and habilitative services to do the rest, and to do it very well, in fact, exist. This, of course, is the assumption”. This statement sums up why this conference was so important to Richard and why, for the 6th Sound Foundation Conference, we sought to continue his tradition of cutting-edge and forward-thinking presentations and discussions. Our conference was kicked off by a provocative Keynote Address by Blake Papsin. Dr. Papsin presented behavioral, physiological, and imaging data to support the importance of binaural hearing – data that confirms our long-held beliefs that binaural is better. We also heard about advancements in hearing technologies that we could only dream about years ago. These technologies combined with earlier identification and current intervention services have resulted in vastly improved outcomes for children with hearing loss and their families. However, as discussed in the Endnote Address, significant hearing care disparities still exist around the world. We heard about promising efforts to reduce those disparities via telepractice but we still have a long way to go. These and so many other fresh ideas presented throughout the conference provide us with the inspiration to continue our noble work.

There are so many individuals we want to thank for the success of this conference. First and foremost, we want to thank the 500 attendees and speakers who traveled from 16 countries around the world to participate. We also offer our sincere thanks to the Conference Steering Committee for working with us to develop the content of this conference. The contribution of all in attendance, the exceptional speakers and attentive audience, is what makes this a true global exchange of ideas that is memorable for us all. Of course, we want to thank Phonak and, especially, Ora Beurkli, Angela Pelosi, and Katarina Schiffer, who worked diligently for over a year to run a smooth conference that was rich in connectivity. Their detailed attention to providing accessible presentations for those with hearing loss, posting presentations online, and displaying twitter feeds throughout the conference truly jettisoned us into the modern world. And, finally, our thanks to Jerry Northern, Ph.D., for his able editing of these proceedings.

Anne Marie Tharpe, Ph.D.

Chair, Phonak Research Advisory Board

Vanderbilt Bill Wilkerson Center

Department of Hearing and Speech Sciences

Vanderbilt University School of Medicine

Nashville, Tennessee USA

Marlene Bagatto, Au.D., Ph.D.

Adjunct Research Professor

National Centre for Audiology

Western University

London, Ontario, Canada

C O N T R I B U T O R S

Sophie E. Ambrose, Ph.D.

Director, Communication Development Laboratory

Boys Town National Research Hospital

Omaha, Nebraska USA

Marlene Bagatto, Au.D., Ph.D.

Adjunct Research Professor

National Centre for Audiology

University of Western Ontario

London, Ontario, Canada

Jamie H. Cadieux, Au.D.

Coordinator, Pediatric Cochlear Implant Program

St. Louis Children’s Hospital

St. Louis, Missouri USA

Sharon L. Cushing, M.D.

Archie’s Cochlear Implant Laboratory

Department of Otolaryngology – HNS

The Hospital for Sick Children

Toronto, Canada

Lisa Davidson, M.A.

Assistant Professor, Department of Otolaryngology

Washington University

St. Louis School of Medicine

Coordinator of Pediatric Audiology

Central Institute for the Deaf

St. Louis, Missouri USA

Janet DesGeorges

Executive Director, Hands & Voices

Boulder, Colorado USA

Noel Y. Dwyer, Au.D.

Research Coordinator

Washington University School of Medicine

St. Louis, Missouri USA

Manuela Feilner, Ph.D.

Phonak AG

Staefa, Switzerland

Jill Firszt, Ph.D.

Associate Professor, Department of Otolaryngology

Director, Cochlear Implant Program

Washington University School of Medicine

St. Louis, Missouri USA

David Foster, Diplomate in School Mgmt

Chief Executive Officer

Kelston Deaf Education Centre

Auckland, New Zealand

Rene Gifford, Ph.D.

Assistant Professor

Department of Hearing and Speech Sciences

Vanderbilt University

Nashville, TN USA

Danielle Glista, Ph.D.

Senior Research Associate

Adjunct Professor

National Centre for Audiology

University of Western Ontario

London, Ontario, Canada

Karen A. Gordon, Ph.D.

Archie’s Cochlear Implant Laboratory

Department of Otolaryngology – HNS

The Hospital for Sick Children

Toronto, Canada

Laura K. Holden, Au.D.

Research Scientist

Washington University School of Medicine

St. Louis, Missouri USA

Martyn Hyde, Ph.D.

Professor of Otolaryngology, University of Toronto

Associate Director, Hearing, Balance and Speech Department

Consultant, Ontario Infant Hearing Program and

British Columbia Early Hearing Program

Mount Sinai Hospital

Toronto, Ontario, Canada

Christine Jones, Au.D.

Director, Pediatric Clinical Research

Phonak LLC

Warrenville, IL, USA

Dawna Lewis, Ph.D.

Staff Scientist

Director, Learning and Listening Laboratory

Boys Town National Research Hospital

Omaha, Nebraska USA

Wendy McCracken, Ph.D.

Professor of Deaf Education

School of Psychological Sciences

University of Manchester

Manchester, UK

Ryan McCreery, Ph.D.

Ryan W. McCreery, Ph.D.

Director of Audiology

Boys Town National Research Hospital

Omaha, Nebraska USA

Mary Pat Moeller, Ph.D.

Director, Center for Childhood Deafness

Boys Town National Research Hospital

Omaha, Nebraska USA

Imran Mulla, Ph.D.

Research Co-ordinator

The Ear Foundation

Nottinghamshire, UK

Stephanie Olson, B.A.

Family Consultant, Audiology

Speech Pathology, Language Services

Colorado Children’s Hospital

Aurora, Colorado USA

Blake Papsin, M.D.

Professor, Otolaryngology – HNS

The University of Toronto

Otolaryngologist-in-Chief

The Hospital for Sick Children

Toronto, Canada

Gary Rance, Ph.D.

Associate Professor

Department of Audiology and Speech Pathology

The University of Melbourne

Melbourne, Australia

Ruth M. Reeder, M.A.

Research Scientist

Washington University School of Medicine

St. Louis, Missouri USA

Frances Richert, M.Sc.

Clinical Faculty in Audiology

National Centre for Audiology

School of Communication Sciences and Disorders

University of Western Ontario

London, Ontario, Canada

Susan Scollie, Ph.D.

Associate Professor

National Centre for Audiology

School of Communication Sciences and Disorders

University of Western Ontario

London, Ontario, Canada

Sterling W. Sheffield, Au.D.

Department of Hearing and Speech Sciences

Vanderbilt University

Nashville, TN USA

Michelle Simha, B.S.

Department of Communication Sciences and Disorders

University of South Florida

Tampa, FL USA

Jody Spalding, M.A.

Research Audiologist

Boys Town National Research Hospital

Omaha, Nebraska USA

Meredith Spratford, Au.D.

Research Audiologist

Boys Town National Research Hospital

Omaha, Nebraska USA

De Wet Swanepoel, Ph.D.

Professor of Audiology

Department of Speech-Language Pathology and Audiology

University of Pretoria

Pretoria, South Africa

Anne Marie Tharpe, Ph.D.

Professor and Chair

Department of Hearing and Speech Sciences

Vanderbilt University School of Medicine

Associate Director

Vanderbilt Bill Wilkerson Center

Nashville, TN USA

J. Bruce Tomblin, Ph.D.

DC Spriestersbach Distinguished Professor

Department of Communication Sciences and Disorders

University of Iowa

Iowa City, Iowa USA

Daniel Valente, Ph.D.

Technician Communications Specialist

SAS Institute, Inc.

Cary, North Carolina, USA

Elizabeth A. Walker, Ph.D.

Research Associate

University of Iowa

Iowa City, Iowa USA

Susan Wiley, M.D.

Associate Professor

Division of Developmental and Behavioral Pediatrics

Cincinnati Children’s Hospital Medical Center

University of Cincinnati

Cincinnati, Ohio USA

Jace Wolfe, Ph.D.

Director of Audiology

Hearts for Hearing Foundation

Adjunct Assistant Professor

Department of Communication Sciences and Disorders

University of Oklahoma

Oklahoma City, Oklahoma USA

S E C T I O N I

Taking Our Pulse:

How Are We Doing Now?

Session Chair: Patricia Roush (USA)

C H A P T E R  O N E

Conference Keynote Address:

Awakening the Auditory System

Binaural Benefit Revisited

Blake C. Papsin, M.D. Sharon L. Cushing, M.D. Karen A. Gordon, Ph.D.

Abstract

This keynote presentation reviewed the process of auditory assembly of the perceived environment and how this assemblage is potentially benefitted by having two (stereo) sensory inputs. The presentation outlined some of the concepts regarding the evolutionary advantage of adaptation and focussed on the improved survival afforded those organisms who can most rapidly and correctly identify potentially harmful, or helpful stimuli in their surroundings. The advantage of having two ears, the binaural benefit, was described and evaluated in this context. The basic auditory scientific experiments conducted in our laboratory were reviewed, demonstrating improved auditory performance results from having two auditory inputs even if the “normal” levels of binaural benefit are not accrued. The role of the cortex and higher level processing was discussed with the suggestion being made that, even with a degraded primary sensory input in organisms with impaired hearing, extraction of information of benefit to survival can and is retrieved better with binaural hearing.

The white peppered moth resides in Northern England. This moth’s dominant phenotype changed from whitish gray to a solid black and then back again in conjunction with a concomitant change in building colour during first the industrial revolution and then second after the post WWII clean-up. The moth’s remarkable ability to extract and assemble sensory data about its surround and then respond to it, no doubt saved several of its kind from predation. The ability to change is a key factor in determining an organism’s ability to survive and that the ability to adapt puts an organism at an advantage.

The ability of an organism to adapt is a direct result of sensing the changes in the environment which signal either safety or danger and assembling these sensory clues correctly through a process known as feature extraction. It is of interest that humans have developed very good abilities to make decisions based on sensory data that they receive and, in fact, human decision making skills are superior to other animals in which more primary sensory superiority (vision, olfaction) has been more significantly developed. Consider how difficult it is to catch a fish or snatch a toy from a dog. These animals have sensory abilities and motor functions that are an equal match for our cleverness in trying to outwit them. As clinicians and scientists focused on the auditory system we are interested in determining what processing occurs in children with potentially degraded sensory inputs that occur in varying degrees of deafness. The question is to look at children with degraded primary sensory input (i.e., deafness) and ask if there is a significant advantage in extracting features from their environment using two ears as opposed to just one. In other words, is there a truly a binaural benefit?

One of the key factors that determine the accuracy with which we assemble sensory information, aside from its quality, is the quantity of the information we receive. The input of two simultaneous streams of information, as would occur with two eyes or two ears, offers information processing systems additive data beyond that contained in the two primary inputs. This “stereoscopic” information, plus our sensory experiences, allows us to process our environments with high fidelity and surprising accuracy. There is comparison relationship between two inputs and advanced processing that establishes a multi-dimensional model based on the sensory input. Whereas the visual system relies heavily on spatial information, the auditory system more heavily relies on timing information. These comparisons in the auditory system are performed primarily at the level of the brainstem.

In our laboratory we have shown that the auditory system develops abnormally in children in whom there is prolonged unilateral sensory deprivation and that furthermore this reorganization does not normalize even with eventual restoration of bilateral input (Gordon, et al., 2008, 2011, 2012; Gordon, Wong and Papsin, 2010, 2013; Gordon, Jiwani and Papsin, 2013). What has been less clear is what effect the central reorganization of the auditory system might have on perceptual capacity of the organism and even more importantly the effect on sensory reassembly.

Our research group, as well as others, have demonstrated that the benefits of bilateral cochlear implantation have only slight benefits on speech perception abilities of children (Gordon and Papsin, 2009; Van Deun, van Wieringen and Wouters, 2010); Chadha, et al., 2011). Additionally, there are some indications that asymmetric inputs from auditory input, as would be the case with cochlear implants placed with a long inter-implant delay, might further diminish the speech and language outcomes (Jewell, Papsin and Gordon, 2012).

Sensory perception, and more importantly, reassembly of the auditory world relates to perception in the three dimensional environment. Here the critical skill required is locating the source of the incoming data. When successfully done, this allows the rest of the sensoria (i.e. vision) to focus and enrich the incoming information by providing corroborating or conflicting information to help the reassembly and decision making process. It is here that the bilateral input, even with the degraded primary input as provided by cochlear implants, shows the greatest benefit. In both spatial unmasking and lateralization experimental paradigms, our group has shown greatest improvements in bilateral conditions and especially in children with simultaneous or near-simultaneous hearing habilitation (Gordon and Papsin, 2009; Chadha, et al., 2011; Gordon, Wong and Papsin, 2013; This corresponds closely to the degree (specifically the lack) of central auditory system reorganization. What is fascinating is that the simultaneous or near-simultaneous cochlear implant recipients use inter-aural timing cues to make nearly correct responses in the lateralization condition -even though by definition the primary sensory data is devoid of temporal information (Gordon et al., in preparation).

An interesting finding occurs in these studies and also in a number of other studies related to this work. That is, children with bilateral implants hear in ways we didn’t think they could. This may be akin to moths changing colours to survive. The information about the three dimensional world may be so critical that one wonders if our processing system, the system that humans preferentially developed over olfaction for example, has determined a novel way to solve the reassembly puzzle with degraded but importantly, bilateral input. Another interesting finding is that correct responses take longer for children using cochlear implants to make than would be the case in children with normal hearing. Reaction time is a surrogate measure of cognitive effort and therefore suggests that the correct answer is taking more effort to establish in children with bilateral cochlear implants. Putting it all together we have a sensory reassembly story that seems to make the moth’s pale by comparison.

The human information processor needs information to orient, communicate and evaluate its environment. Despite the fact that the preferred sensory information is not available (i.e. lack of timing cues with cochlear implants) humans with bilateral cochlear implants might have found a novel way to extract the sensory information they need to negotiate their multi-dimensional environment. It just may take them longer to do it since they are relying on cortical processes to replace the factory-installed processors in the brainstem that rely on temporal information. This hypothesis is highly speculative, to be sure, but there is other sensory experimental data that suggests such processing does occur (Czarnecki, et al., 2012).

Children need to extract as much information from their environments as they can; for those children with hearing loss this extraction process is tiring and involves considerable cognitive effort. Children have far less experience on which to understand tense, grammar and the way the world around them actually works. The rapidity of the diagnosis and habilitation and the quality of the input, whether it be a result of bilateral input or better hearing aid fitting, are the subjects central to this conference. They are amongst the many other topics of this conference devoted to improving the quality of the sensory input and improving the ability of the child to extract important information from their environment and reassemble it correctly. A main purpose of this presentation is to point out that the superiority of human information processing may make it possible to use heretofore unusable data to satisfy its need for information. That is an exciting prospect and should inspire us all to apply the knowledge presented at this conference to best provide the highest fidelity and reliable auditory data to the children with hearing loss in our care. Then, like moths, these children will seek the light on their own.

References

Chadha, N.K., Papsin, B.C., Jiwani, S., Gordon, K.A. (2011). Speech detection in noise and spatial unmasking in children with simultaneous versus sequential bilateral cochlear implants. Otology and Neurotology,

32(7), 1057-1064.

Czarnecki, L.A., Moberly, A.H., Turkel, D.J., Rubinstein,T., Pottackal, J., Rosenthal, M.C., McCandlish, E.F.K., Buckley, B., McGann, J. P. (2012). Functional rehabilitation of cadmium-induced neurotoxicity despite persistent peripheral pathophysiology in the olfactory system. Toxicological Sciences,126(2), 534–544.

Gordon, K.A., Valero, J., van Hoesel, R., Papsin, B.C. (2008). Abnormal timing delays in auditory brainstem responses evoked by bilateral cochlear implant use in children. Otology and Neurotology, 29(2), 193-198.

Gordon, K.A. and Papsin, B.C. (2009). Benefits of short interimplant delays in children receiving bilateral cochlear implants. Otology and Neurotology, 30(3),319-331.

Gordon, K.A., Wong, D.D., and Papsin, B.C. (2010). Cortical function in children receiving bilateral cochlear implants simultaneously or after a period of interimplant delay. Otology and Neurotology, 31(8), 1293-1299.

Gordon K.A., Wong, D.D., Valero, J., Jewell, S.F., Yoo, P., Papsin,. B.C. (2011). Use it or lose it? Lessons learned from the developing brains of children who are deaf and use cochlear implants to hear. Brain Topography, 24(3-4), 204-219.

Gordon, K.A., Salloum, C, Toor, G.S., van Hoesel, R., Papsin, B. C. (2012). Binaural interactions develop in the auditory brainstem of children who are deaf: effects of place and level of bilateral electrical stimulation. Journal of Neuroscience, 32(12), 4212-4223.

Gordon, K.A, Jiwani, S., and Papsin, B.C. (2013). Benefits and detriments of unilateral cochlear implant use on bilateral auditory development in children who are deaf. Frontiers of Psychology, 4:719.

Gordon, K.A., Wong, D..D, and Papsin, B.C. (2013). Bilateral input protects the cortex from unilaterally-driven reorganization in children who are deaf. Brain, 136(Pt 5), 1609-1625.

Jewell, S., Papsin, B.C. and Gordon, K.A. (2012). Bilateral benefit improves with symmetric function between the ears. Paper presented at: 12th International Conference on Cochlear Implants and Other Implantable Technologies. Baltimore, MD.

Van Deun, L., van Wieringen, A. and Wouters, J. (2010). Spatial speech perception benefits in young children with normal hearing and cochlear implants. Ear and Hearing, 31(5), 702-713.

Acknowledgement: For the Symposium proceedings publication, I have elected to write in prose style and refer to the published literature for more detailed study of the work and concepts presented. The goal of this address was to inform and inspire rather than solely transmit data which is published in full form elsewhere. I have included my two academic partners in our cochlear implant program as coauthors of this paper. They have shared in the experimentation and data analysis that informs this work and hours of discussion among us have generated much of the material I presented in the keynote address.

C H A P T E R  T W O

Physiologic Assessment of Young Infants – Puzzles and Challenges in Early Hearing Detection and Intervention

Martyn Hyde, PhD

Abstract

This paper touches on selected topics related to the validity, accuracy and efficiency of initial audiologic assessment of babies referred from newborn hearing screening. Utilization of OAEs, CMs, ABRs, ASSRs, and late cortical potentials are discussed. The puzzles and challenges discussed include the following: (1) Many factors can complicate the physiologic assessment and differential diagnosis of ANSD. (2) ABRs to rarefaction and condensation clicks can show extraordinary and puzzling differences, (3) slow cortical potentials can yield hearing threshold estimates in sleeping newborns, (4) the frequency specificity of the ASSR should not be based simply on stimulus energy spectra, (5) comparative studies of techniques should follow some simple methodological rules, and (6) ABR thresholds can be more efficient if stimulation and averaging tactics follow some basic statistical principles.

Accurate, Early ANSD Diagnosis – Sometimes Easy, Often Challenging or Impossible

ANSD is characterized by degraded neural function relative to cochlear receptor function. Diagnostic criteria have evolved from ‘normal OAEs and absent ABRs’ to ‘present OAEs and/or cochlear microphonics (CM) and absent or abnormal ABRs’. Major factors that govern physiologic assessment procedure and diagnostic inference include:

• ANSD can involve inner hair cells (IHCs), their synapses and the cochlear nerve, in isolation or combined.

• Dysfunction components/subtypes range in severity from minimal to complete.

• It can occur concurrently with conventional cochlear

(ccHL) and conductive hearing loss (CHL).

• Pathology can change over time, due to degeneration, recovery, neurodevelopment and neuroplasticity.

• ANSD-type selective IHC pathology can occur with variable severity at specific cochlear frequency regions, alone or combined with typical ccHL pathology elsewhere in the same cochlea (Amatuzzi et al.,

2011)!

Given absent ABR, normal OAEs rule in ANSD and rule out both moderate or greater ccHL and CHL; mild ccHL is not ruled out. Present OAEs at isolated frequencies suggest ANSD but are not definitive. OAEs are usually abolished by slight CHL, with risk of missing ANSD. If tympanometry shows a peak, OAE absence suggests ccHL but with no peak, OAE absence is non-diagnostic; in either case, ANSD is not ruled out. In fact, the only finding that might ever rule out ANSD is a normal, complete ABR waveform for clicks at or below 90 dBnHL.

If OAEs are minimal or absent, CM is measured to rarefaction/condensation clicks and distinguished from artifact by insert tube clamping. Large (300+ nanovolts), oscillatory CM with absent ABR rules in ANSD, but small, brief CM does not. Moreover, significant CM does not rule out even severe ccHL: CM can arise from OHCs, from IHCs if OHCs are compromised, and from any cochlear region (Withnell, 2001). CM is notoriously variable across subjects, abolished by large CHL and depends strongly on stimulus level. Low-pass cut-offs below 3 kHz can abolish high-frequency CM and large CM can be associated with various central lesions (Santarelli, et al., 2006.)

With ABR present, interpretation is even more difficult. Postsynaptic ANSD can yield a prominent early peak blend of CM asymmetry, true summating potentials and wave I, with abnormal or absent later waves. At maximal click levels, vestibular potentials may intrude. ABRs that look antiphasic for rarefaction/condensation clicks can arise due to cochlear excitation phase effects and be confused with prolonged CM.

More sophisticated protocols to disentangle receptor (CM/SP) and neural potentials are required. Options include using several click levels, high (91+/s) and low (~21/s) rates, increased bandwidth, CM quantification and addition/subtraction of averages. Category rating scales for ANSD likelihood and severity are also required.

Currently, the amplitude ratio of pure CM and ABR V-V’ is a crude but useful indicator; when V is clear, CM/V ratios above 2 strongly suggest ANSD, but there is a likelihood continuum and morphologic factors also contribute. Comparative CM and ABR data in young infants are extremely limited (Shi et al., 2012) and are a research priority.

Extraordinary ABR Waveforms

As noted earlier, evaluation of rarefaction (R) and condensation (C) click ABR records is commonplace to explore cochlear microphonic (CM) and differentiate between sensory receptor and neural activity. It is usually assumed that whatever inverts when rarefaction and condensation click records are compared is CM, whereas what does not invert is either SP or neural. Conventional wisdom is that latency shift between (R) and (C) ABR tracings is due to preferential neuronal activation in the scala-media-negative CM phase. For tonepips, the time difference is a half-period of the carrier, ranging from 125 ms for a 4 kHz tonepip to 1 ms for a 500 Hz tonepip. Peak cancellation or smearing effects in alternated average are negligible at 4 kHz and 2 kHz and, near threshold, are irrelevant at 500 Hz.

Usually, ABR morphology is similar for the two tonepip polarities but in a small (unknown) proportion of cases, the differences are marked. ABR waves can differ in size or even be absent for one polarity and present for the other. Waves can also differ in latency by much more than a half-period of the carrier, even to the point of response cancellation in alternated averages. These phenomena appear to be quite common in adults with high-slope, high-frequency hearing losses; combined extra-tympanic electrocochleography and ABR are common clinical tools with extraordinary asymmetries of CM and ABR waves a frequent finding. Examples of major asymmetries of R and C click ABRs in young infants are shown in Figure 1.

Figure 1. Clinical record extracts from three infants illustrating differences in rarefaction and condensation ABRs to 85 dBnHL clicks at 21.1 per second by insert earphone. X-scale 15 ms, Y-scale 0.5 V per division. All three blocks show replicated rarefaction responses with condensation responses immediately below; the upper and lower blocks also show tube-clamped averages. CM is apparent at about 1 ms in the upper and lower blocks.

The mechanism and pathophysiologic significance of these findings are unclear. A possible mechanism is differences in the (R) and (C) click travelling wave neural excitation profile and the resulting timing of ABR waves from different sites along the cochlear partition. Wave cancellation might occur if the place-sourced component ABRs happened to be partially anti-phasic, which is more plausible than polarity-specific brainstem generator inactivity. It would be of interest to examine cases of ABR asymmetry using a subtractive, high-pass masking technique to isolate place-specific component ABRs. There may be place-ABR findings suggestive of cochlear dead zones.

Late Auditory Cortical Evoked Potentials

– Forgotten Findings

Late (slow) cortical potentials, widely known in adult subjects as ‘N1-P2’, have undergone a resurgence of interest in the last decade. These late potentials have a number of possible applications such as biomarkers of cortical maturation, a measure of aided audibility and an objective index of perceptibility of a variety of acoustic events. These are clinical additions to the longstanding use of N1-P2 as arguably the best non-behavioural estimator of frequency-specific hearing thresholds in passively cooperative older children and adults. The N1-P2 has been especially useful in confirming functional hearing loss and in hearing assessments for medical-legal purposes (Hyde, 1997; Stapells, 2001). N1-P2 is not a unitary response; its two components differ in cortical site of origin, stimulus relationships and possibly their functional significance. The two features have different neurodevelopmental time courses, with N1 being absent in young infants.

N1-P2 has been described as an ‘exogenous’ response, reflecting its strong dependence on acoustic stimulus parameters such as rise rate, envelope, duration and energy-density spectrum (Hyde, 1997). Other late potentials such as the mismatch negativity and P300 are deemed to reflect more ‘endogenous’ aspects such as stimulus discriminability, probability and cognitive significance. However, N1-P2 is strongly dependent upon stimulus-oriented attention and in typical averaging sequences it is a highly habituated phenomenon dependent on stimulus repetition rate, mark-space ratio, regularity and sequence length.

In recent years, there have been numerous discussions about the ‘acoustic change complex’ (ACC). It would appear that the ACC is essentially the traditional N1-P2 response. Hearing threshold is actually a change from silence to sound, i.e., a special case of amplitude modulation. In fact, N1-P2 is evoked by any perceptible change in any dimension of the acoustic environment, including any direction of change in stimulus amplitude, frequency, spectral content and perceived source location.

The ACC terminology reflects obvious functional dynamics of N1-P2. Clynes (1969) reported on N1-P2 properties evoked by frequency-modulated (FM) stimuli. He found clear responses to upward and downward frequency changes in rectangular FM envelopes, but no responses at all to triangular FM, not even at the points of sharp change in direction of modulation. This led Clynes to describe N1-P2 functional dynamics in terms of a ‘rest-motion (R-M) brain function’. That is, N1-P2 does not simply reflect temporally discrete acoustic change but only such change when it is preceded by a sufficient period of lack of change or ‘sensory rest’.

In adults, N1 has typical latency about 100 ms and P2 about 180 ms, for tone bursts of moderate intensity and typical rise/fall and plateau times of at least 10-20 ms. Response amplitude follows an energy integration profile plateauing at about 30 ms. Repetition rates are typically 0.5 per second, with 20-50 stimuli per average. In infants, N1 is not well-developed and P2 is the main feature, typically peaking at about 300 ms but with substantial range.

In EHDI programs, P2 can be used to estimate hearing thresholds when the accuracy of ABR-based estimates is questionable, the obvious example being suspected or definite ANSD. Current clinical practise is to wait for ear-specific, frequency-specific visual reinforcement audiometry results (VRA), typically obtainable at age 6 months or later. However, this 6-month wait for results may be a major source of frustration and anxiety for families. Furthermore, waiting so long may incur significant, unnecessary delay or compromise in auditory neurodevelopment. For infants with visual, motor or cognitive comorbidities, reliable VRA results may never occur. If ANSD were suspected or identified at 1-3 months of age, the rationale for seeking an early alternative to behavioural threshold measurement is compelling. In major pediatric audiology centres, early use of P2 is increasingly common. Stimuli can be tone bursts by air or bone conduction, masked in the opposite ear when necessary and calibrated in dB HL.

There is widespread belief that P2 measurement in infants is best done with the infant awake. It is not clear how this viewpoint arose and whether it is valid. For estimating hearing thresholds in young infants, the strongest published report to date is based on testing in natural sleep. Taguchi, Picton, Orpin et al. (1969) reported ‘excellent results’ (almost 90% success) for tone burst threshold estimation at 500 Hz and 2 kHz in 250 newborns less than two weeks of age. Among the rationales for testing during sleep is that very young infants sleep naturally most hours of the day and the auditory evoked responses are easier to see and measure with subjects asleep. Age is a major determinant of optimal P2 testing approach; the earlier the testing is done the more viable sleep testing becomes. Taguchi et al’s results suggest that skill in recognising sleep state using ongoing EEG is relevant to determining accurate threshold estimation. It has long been known that the latency, size and morphology of AEPs depends on sleep state, so averaging across a mixture of conditional states may be misleading. The younger an infant is, the simpler it is to determine their sleep state categories by monitoring of the ongoing EEG morphology and the easier it is to render sleep state distinctions. It may be sensible to acquire relatively small averages along with their sleep state categories, then amalgamate the mini-averages in matching sleep states post hoc. Taguchi et al used tone bursts with 3-second cycle times; inter-stimulus recovery and sequence habituation time constants are larger in newborns and infants, so parameters that are optimal for adults will not apply.

The history of adult N1-P2 utilization and accuracy is typified by a wide range of technique, skills and understanding. Accurate work with late potentials is different tactically, much more interactive and generally more demanding than most ABR measurements. Ishida, Stapells & Small (in preparation, 2013) confirmed the ability to elicit the P2 response in sleeping infants in response to 60 dB white noise bursts in 16 sleeping young infants with presumed normal hearing (Figure 2).

Figure 2. Slow cortical potentials elicited by 60 dB white noise bursts, from 16 sleeping infants. Waveforms from individual subjects plus the grand mean waveform are shown (Personal communication, figure extracted from Ishida, I., Stapells, D. & Small, S. (in preparation, 2013).

There are many other potential applications of N1-P2. For example, Michalewski et al. (2005) used N1-P2 in adults to measure gap detection thresholds. Dimitrijevic et al. (2012) found interesting differences in N1 amplitude to FM and AM stimuli at low and high tonal frequencies that interacted with ANSD pathologic subtypes. It remains to be seen what ultimately can be revealed in infants with this under-exploited tool.

Brainstem (80 Hz) ASSRs & ABRs

Another puzzling challenge relates to the ABR and the auditory steady state response (ASSR). Is the ASSR actually a tonepip ABR evoked by stimulus repetition at 80-110 Hz and analyzed in the frequency domain, and does it matter if it is or not? In this author’s view, on current evidence the answer is ‘sometimes’ to both. At high sensation levels, energy periodic at the modulation frequency may include: stimulus artifact, cochlear receptor potentials, an entire ABR wave sequence from I through VI and rate-adapted remnants of later potentials such the middle-latency response (MLR). Depending on recording bandwidth, the slow postsynaptic potential components of the ABR also may be represented. Fourier analysis of response magnitude will not distinguish these sources, but they can usually be distinguished in the time domain.

At near-threshold intensity, the transient ABR evoked by a tonepip usually comprises a wave V peak and a trough often called V’. The peak-to-trough interval varies around 5 ms and there may be a wave VI with a V-VI interval of around 10 ms. For the ASSR, there is a sequence of brief quasi-sinusoids concatenated at the modulation frequency. Stimulus artifact, receptor potentials and MLR residues will vanish and slow postsynaptic components will be present or absent depending on bandwidth. Under these conditions, the phenomena may be assumed to be identical, unless and until contradictory evidence is found.

However, equality of generators does not mean equality of audiometric characteristics. Stimulus waveforms for the transient ABR and ASSR may be very different (Stapells, 2011). A common tonepip ABR stimulus is a 2-1-2 cycle trapezoidally modulated tone, and the ABR is an onset phenomenon governed by stimulus energy in the first 2-3 ms from onset. Above 2 kHz, the 2-1-2 cycle stimulus is too short to evoke optimum ABR amplitude, having energy-equivalent duration of only 0.58 ms at 4 kHz. In contrast, at 500 Hz only about the first half of the initial rise contributes to the ABR. For the simplest possible ASSR with sinusoidal modulation at 80 Hz, the zero-to-peak time is 12.5 ms and only the first part of the rise generates the ABR waves giving rise to the ASSR. The effective stimulus magnitude is significantly less than the commonly measured levels, whether in peak SPL, RMS SPL or dBHL.

A related puzzle is the frequency-specificity of the tonepip ABR and ASSR. The energy density spectrum of typical ASSR stimuli is far narrower than that of the typical 2-1-2 cycle gated tonepip with the same carrier frequency. This is universally interpreted to mean that the ASSR is much more frequency-specific that the tonepip ABR. But, the logic of that step is difficult to grasp. First, if the ASSR is an ABR and the ABR is an onset phenomenon with an integration time of 2-3 ms, it doesn’t matter what the ASSR stimulus looks like for each modulation after 2-3 ms from onset. Yet, the Fourier spectrum reflects the entire modulation period. No one would do a tonepip ABR with a 20 ms tonepip and expect it to be much more frequency-specific than a 2 ms tonepip – the flaw is obvious.

A second issue is that in the abnormal cochlea, frequency resolution is vastly inferior to that of the resonant peak when the cochlear amplifier is intact, reducing to the mechanical resolution of the basilar membrane itself, for cochlear losses greater than about 60 dB. Since what we hear is governed by whatever is transmitted through the cochlea to the central auditory system, the relevance of the acoustic Fourier spectrum of the stimulus to the actual frequency specificity of an evoked potential is difficult to comprehend. This does not mean that the ASSR is not more frequency specific, only that the usual argument for that belief is invalid.

Challenges with Comparative Studies

It is common to ask whether technique A or B is better for a given purpose such as estimation of thresholds in babies who have failed ABR hearing screening. There are several challenges with such a deceptively simple question:

1. What is meant by ‘better’? The usual answer would be ‘faster’ or ‘more accurate’. But, speed and accuracy have an inverse relationship, so either one must be fixed and the other evaluated or, far better, the trading relationship function between the two must be determined.

2. Accuracy itself has two parts: bias (mean error) and precision. Of the two, precision is vastly more important, because bias can be corrected by fixed

adjustment. Precision has two major components: within-subject and between-subject variation. For this reason, at least two repetitions of every condition for every subject are a minimum.

3. A more difficult issue is optimization of each technique. Are the parameters of each procedure chosen to be representative of common practise, or to be credibly optimal? It is unlikely that common practise is also optimal. If representativeness is chosen, then the question asked is not whether A is truly better than B, but whether A as commonly practised is better than B as commonly practised. Because optimality is a function of so many parameters of subjects, procedures and contexts of practice, this question is by far the most practicable.

4. The literature is full of deficiencies of data analysis. A general remedy is to always tabulate in an appendix all pertinent data for all subjects, so that third parties can re-analyze as they see fit. A common issue in such an analysis is over-reliance on summary statistics. Statistical means are uninformative compared to distributions or scatterplots. Standard deviations are misleading unless data are normally distributed and contain no outliers. Correlation coefficients are the most opaque of all: they are strongly affected by data range and vastly different patterns of relationship can yield the same coefficient.

5. Even good reports may overgeneralize inferences based on statistical means, so wherever possible, results for individual subjects should be illustrated graphically. In general, it is the exceptions to average behaviour that that are far more informative than the average results themselves.

ABR Threshold Estimation Efficiency – So Much Wasted Time!

What is ‘sufficient’ audiometric information? One possible answer is threshold estimates at 2 kHz and 500 Hz within 10 dB, plus valid inference of hearing loss type. Whatever the answer, the session comes down to threshold estimates for various stimulus frequencies and routes. How can threshold estimation be optimized? The two main variables are (1) tactics of intensity selection and (2) signal averaging. Consider a single frequency-route for which no prior information is available, such as air conduction measures at 2 kHz.

Threshold estimation is a set of binary response detection trials. A crucial principle is that for any trial, the more equiprobable the outcomes, the larger the information gain. So what should be the starting intensity level? In a nil-risk baby, the positive predictive value of AABR screening failure is about 0.1, so a response at 30 dBnHL is much more probable than a non-response. We would have to go lower intensity levels to raise the non-response probability, but that would enmire us in minor middle-ear disorders, so testing should start at the minimum level of interest because any higher level is less informative. If we get clear responses at the initial intensity level, then changing frequency to 500 Hz or switching ears should be the next step in the ABR testing protocol.

However, if there is no response at 30 dB at 2 kHz, one choice is to change to bone-conduction testing at 2 kHz at 30 dB to quickly determine is this sensorineural or conductive hearing loss? The other option might be to increase the air conduction intensity level, to explore the severity of hearing loss. If we chose the latter option, the question becomes to what level? The answer depends on the a priori distribution of hearing thresholds in the population with hearing loss at 2 kHz. Given a range of about 30-100 dB HL and an assumption of uniform distribution, the test level for equiprobability is about 60 to 65 dB with a 5 dB correction factor for ABR threshold estimates at 2 kHz. Given no ABR response at 60 dB, the next level to test might be a jump to 80 dB. This strategy of large intensity ascending step size is very efficient. The least efficient strategy is to repeat ABR testing in 10 dB ascent (or descent) steps.

If there is no ABR response at 30 dB but a clear response at 60dB, should we next decrease intensity to 50 dB or to 40 dB? In fact, ABR trials are not binary, because we have information about response size and signal-to-noise ratios (SNR). Accordingly, a reasonable strategy is to decrease intensity to 40 dB if the ABR response at 60 was large or decrease intensity to 50 dB if the ABR response at 60 was small. These principles can be applied to 5 dB steps, but it is far more efficient and useful to get complete results in 10 dB steps before even considering 5 dB steps. In the author’s experience, ABR threshold definition within 10 dB can be accomplished in infants with no response at 30 dB within three further levels or less the vast majority of the time.

There are five key points to consider in signal averaging tactics. (1) You cannot conclude that a response is “absent” if you could not have seen it even if it were present. Negative judgements require that residual noise levels in averages are below a criterion level. (2) Positive judgements are based on the SNR or, when the SNR is not overwhelming, the determination is made on tracing reproducibility. Thus, the final intensity threshold bracket upper levels should always be repeated. (3) Due to the root-n law of diminishing returns from averaging, fewer smaller signal averages are generally more useful than one large signal average. Signal averages should never be smaller than 500 sweeps because of the increased variability. (4) The total time spent on any given stimulus condition should be limited; if you cannot decide on response presence or absence within three averages totalling 6,000 sweeps, something is wrong; either you are chasing shadows or the EEG noise levels are unacceptably high. The best tactic in these circumstances is to increase intensity by 20-30 dB and attempt to identify a definite ABR tracing. (5) There are three categories of ABR response judgment: present, absent, and indeterminate. When you cannot decide with confidence that the response is present or absence, do not guess – additional measurement is obligatory.

References

Amatuzzi, M., Liberman, M.C., & Northrop, C. (2011). Selective inner hair cell loss in prematurity: a temporal bone study of infants from a neonatal intensive care unit. Journal of the Association for Research in Otolaryngology, 12(5), 595-604.

Clynes, M. (1969). The dynamics of evoked vertex potentials: the R-M brain function. In E. Donchin & D. B. Lindsley (Eds.), Average Evoked Potentials. Methods, Results and Evaluations. NASA Special Publication SP-191 (pp. 363-374). U.S. Government Printing Office, Washington DC 20402.

Dimitrijevic, A., Starr, A., Bhatt, S., et al. (2011). Auditory cortical N100 in preand post-synaptic auditory neuropathy to frequency or intensity changes of continuous tones. Clinical Neurophysiology, 122(3),594-604.

Hyde, M. (1997). The N1 response and its applications. Audiology and Neurotology, 2 (5), 281-307

Ishida, I., Stapells, D., & Small, S. (personal communication, S. Small, 2013).

Michalewski, H., Starr, A,, Nguyen, T., Kong, Y., Zeng, F. (2005). Auditory temporal processes in normal-hearing individuals and in patients with auditory neuropathy. Clinical Neurophysiology, 113(3), 669-680.

Santarelli, R., Scimemi, P., Dal Monte, E., & Arslan, E. (2006). Cochlear microphonic potential recorded by transtympanic electrocochleography in normally-hearing and hearing-impaired ears. Acta Otorhinolaryngolica Italica, 26(2), 78-95.

Shi, W., Ji, F., Lan, L., Liang, S., Ding, H., Wang, H., Li, N., et al. (2012). Characteristics of cochlear microphonics in infants and young children with auditory neuropathy. Acta Oto-Laryngologica, 132(2), 188-196.

Stapells, D. (2001). Cortical event-related potentials to auditory stimuli. In J. Katz, R. Burkard & L. Medwetsky (Eds.) Handbook of Clinical Audiology, 5th Ed. (pp. 378-406). Baltimore, MD: Lippincott, Williams & Wilkins

Stapells, D. (2011). Frequency-specific threshold assessment in young infants using the transient ABR and the brainstem ASSR. In R. Seewald & A. M. Tharpe (Eds.) Comprehensive Handbook of Pediatric Audiology, (pp. 409-448). San Diego, CA: Plural Publishing.

Taguchi, K., Picton, T., Orpin, J., & Goodman, W. (1969).Evoked Response Audiometry in newborn infants.

Acta Oto-Laryngologica, Suppl. 252, 5-17.

Withnell, R.H. (2001) Brief report: the cochlear microphonic as an indication of outer hair cell function. Ear & Hearing, 22, 75-77.

C H A P T E R  T H R E E

Children Who Are Hard of Hearing: Still Forgotten?

Mary Pat Moeller, Ph.D. Sophie E. Ambrose, Ph.D. J. Bruce Tomblin, Ph.D

Abstract

In the 1970’s, Dr. Julia Davis called attention to major gaps in research and service delivery for children who are hard of hearing. She referred to this group as “Our Forgotten Children” and many of the issues she raised then remain true today. The need to address these gaps is paramount in an era where children are identified in infancy and have access to early interventions. Although it is presumed that these service innovations will lead to improved outcomes, there is a critical need for research to determine if earlier interventions are bringing about expected results for the majority of children. In an effort to address research gaps and strengthen the evidence guiding practice, a multi-site, longitudinal study of the outcomes of children with mild to severe hearing loss (Outcomes of Children with Hearing Loss; OCHL) was implemented. The aims of this chapter are to 1) describe the goals and the design of this multi-site project, 2) discuss the research team’s working hypothesis that inconsistent access to linguistic input places some children and some aspects of development at increased risk for communication delays, and 3) summarize selected main findings regarding outcomes and influential factors. Implications for service delivery are described.

This article focuses on the needs of children who are hard of hearing (HH); specifically those with bilateral, persistent hearing losses in the mild through moderately-severe range, who are fit with hearing aids (HAs) and rely on spoken language for communication and learning. Historically, HH children have been identified around 2 years of age or later (Halpin, Smith, Widen, & Chertoff, 2010), underrepresented in research (Moeller, Tomblin, Yoshinaga-Itano, Connor, & Jerger, 2007), and underserved in regular educational settings (Davis, 1977). Recent evidence shows that the practice of universal newborn hearing screening (NHS) has been effective in reducing the ages of diagnosis for infants with varying degrees of hearing loss (Durieux-Smith, Fitzpatrick,

& Whittingham, 2008). NHS has also led to increased opportunities to study HH children in infancy and renewed interest in addressing existing research gaps. Research specific to HH children is needed to understand ways in which the presence of partial hearing loss may impact early linguistic development. Such work is essential for building an evidence base to guide clinical and educational practices.

Davis and colleagues (1977) used the term “Our Forgotten Children” to describe students who are HH. It is of value to consider the historical concerns in light of current practices to determine which issues remain unresolved. Davis observed that the sole responsibility for educating HH children in the schools typically was assigned to regular education teachers, who frequently lacked specific training or understanding of the subtle consequences of hearing loss on learning. She described a tendency for adults to underestimate HH children’s needs. This may occur if teachers experience successful communication during face-to-face interactions with HH students, thus leading the teachers to underestimate the extent to which noise and subtle language gaps may serve as barriers to learning in classroom settings. Consequently, teachers may ascribe children’s difficulties to behaviors unrelated to hearing loss (see Lewis, Spaulding, & Valente, this volume) as evidenced by frequent reports to clinicians that a HH child “hears me fine, but just does not pay attention.” This attitude fits with previous research documenting limited vigilance in monitoring HH children’s language and academic outcomes (Davis, Stelmachowicz, Shepard, & Gorga, 1981) and amplification needs. However, based on a classic study of the outcomes of 40 HH children, it was concluded that any degree of hearing loss may place a child at risk for language delays (Davis, Elfenbein, Schum, & Bentler, 1986). A recent study showed that 25 4and 5-year-old HH children were delayed in speech and language skills, on average, compared to peers with normal hearing (Fitzpatrick, Crawford, Ni, & Durieux-Smith, 2011). These collective concerns underscore the importance of prospectively examining the outcomes of a large cohort of preschool-aged HH children to understand sources of risk for language delays as well as protective factors that can be emphasized to prevent later challenges. Without such data, this group may remain “our forgotten children.”

It has been estimated by the National Institutes on Deafness and Other Communication Disorders (NIDCD) that 30,000 children in the U.S. under the age of 6 years have persistent, mild-to-severe hearing loss. In spite of this fairly high prevalence, there has been limited investment in research that provides a clear description of the unique needs of this group (Eisenberg et al., 2007). Because of research gaps, there remains disagreement and skepticism in the professional community about the needs of HH children, especially those on the mildest end of the continuum. In response to these issues, the NIDCD funded two prospective, longitudinal studies focused on understanding the outcomes of young HH children. The Outcomes of Children with Hearing Loss project, described in this chapter, was one of the funded multi-site studies. It is a collaborative effort of researchers at the University of Iowa, Boys Town National Research Hospital, and the University of North Carolina at Chapel Hill. There are three primary aims guiding this multidisciplinary research endeavor:

1. Describe the characteristics of the children and families, their intervention receipt, and factors associated with variations in services.

2. Measure a range of child & family outcomes and compare child outcomes to a well-matched group of children with normal hearing (NH).

3. Explore how variations in child, family, and intervention factors influence children’s outcomes, using multivariate analyses.

Design and Methods

The OCHL study design and methods have been described elsewhere (Holte et al., 2012), and therefore will only be summarized briefly in this chapter. The research goals were addressed through an accelerated longitudinal design. This design served the project goals well, allowing the team to maximize the amount of longitudinal and cross-sectional data accrued during the 5-year grant period. If the team had started all children in infancy and followed them prospectively, the sample size would have been limited and insufficient to address multivariate analyses. Instead, the team worked in the first two years of the grant to identify all children who met the following criteria 1) current age within the range of 6 months to 6 years, 11 months, 2) persistent, bilateral hearing loss, 3) better-ear pure tone average (BEPTA at .5, 1, 2, and 4 kHz) ranging from 25 to 75 dB HL, 4) no significant secondary disabilities that would preclude participation in testing, and 5) at least one primary caregiver using spoken English in the home setting. Children were recruited with assistance from state EHDI coordinators, early intervention specialists, audiologists, and educators. Children who met the criteria entered the study for a baseline visit and then were followed prospectively on an annual basis for at least 3 years. Those who were enrolled as infants or toddlers were seen every 6 months until 24 months of age and annually thereafter. A comprehensive set of audiological, speech, language, pre-literacy, cognitive, and psychosocial outcome measures were collected at each visit. Relevant retrospective records were collected to complement the prospective data. The research team maintained regular contact with parents and established community-based collaborations to minimize attrition rates (8.1% for the 5-year project).

The team was successful in enrolling 316 HH children from 13 states. The mean BEPTA for the HH group at the baseline visit was 48.61 dB HL (SD = 13.52). A comparison group of 115 NH children were enrolled. The two groups (NH, HH) were matched on age, cognitive abilities (both groups within the average range), and home characteristics (i.e., use of spoken English, maternal education/socioeconomic status). The research team made a concerted effort to recruit samples that reflected a typical distribution of socioeconomic levels. In the end, the NH and HH samples in the OCHL study are well matched on this dimension, but are more advantaged than a typical U.S. sample. This is a common challenge in longitudinal studies, but needs to be taken into consideration when interpreting the results. Selected results will be highlighted in this chapter, and the sample sizes will vary, depending on the research question and age group(s) analyzed.

A Hypothesis About Factors Influencing Outcomes

A positive finding from the OCHL project to date is that many HH children achieve better speech and language outcomes than were demonstrated by previous generations of children who were HH. Depending on the measure administered, as many as 70% of 5 year olds presented with speech and language scores with the average range compared to test standardization samples (Tomblin, Oleson, Ambrose, Walker, & Moeller, 2014). An important caveat, however, is that on some of these same measures, the average score for HH children was significantly lower than that of the matched comparison group of NH children, who came from families with similar backgrounds and resources. This fits with findings of previous research showing that children with mild hearing loss fell behind their NH classmates, who presumably came from similar family backgrounds (Blair, Peterson, & Viehweg, 1985). Of more concern is the finding that 25-30% of the HH children in the OCHL study performed one standard deviation or more below the level of the standardization sample and their matched peers. This is higher than the 7% rate of language problems that would be expected in a NH group (Tomblin et al., 1997). There is also considerable variation in the outcomes of HH children in the lower-performing group, suggesting that selected children are particularly vulnerable to the effects of hearing loss. Furthermore, the data reveal that selected aspects of linguistic development, such as articulation and morphology, seem to be more susceptible than others to the influence of hearing loss. Thus, the challenge ahead is to determine what factors explain individual differences in outcomes and why some aspects of language learning may represent vulnerable domains.

The OCHL research team has hypothesized that hearing loss may interfere with the consistency and quality of children’s access to linguistic exposure in the environment. Access to input is regarded as a critical factor influencing acquisition both for typical children (Slobin, 1985) and for children with specific language impairment (SLI; Leonard, 1989). An inconsistent access hypothesis leads to some specific predictions about language development. First, inconsistent or reduced access would contribute to a reduction in overall input frequency. It is known that input frequency influences how early certain linguistic forms are acquired in NH children (Hsieh, Leonard & Swanson, 1999). Thus, a reduction in the frequency of exposure to certain forms might slow the rate of language development. Second, the inconsistent access hypothesis suggests that aspects of development that are most dependent on the fidelity of the speech signal (e.g., articulation, morphology) may be most vulnerable to the effects of hearing loss on language development. The current work seeks to identify variables beyond the hearing loss that impact audibility and access.

Severity of hearing loss would be expected to influence linguistic access. Studies examining outcomes in groups comprising only HH children do not always find an effect of degree of hearing loss (Davis, et al., 1986; Gilbertson & Kamhi, 1995). However, to adequately explore this question there is a need for a sample of sufficient size with adequate variance in degrees of loss, and not inclusive of children with severe and profound hearing loss. The influence of BEPTA on articulation skills was examined in a subset of OCHL participants; 3 year olds who were HH (n = 110) or NH (n = 45). Results suggested strong and systematic effects of degree of hearing loss on speech outcomes (see Figure 1). Greater degrees of hearing loss were associated with poorer speech outcomes on the Goldman-Fristoe Test of Articulation (Goldman & Fristoe, 2000). Note that the effect sizes (bolded squares in Figure 1) increase as degree of hearing loss increases.

Figure 1. Goldman-Fristoe Test of Articulation (GFTA) standard scores for 3 year olds plotted as a function of hearing level in 10 dB increments compared to age-matched children with NH. Lines in the box plots signify median score, whereas filled circles represent means. Effect sizes (Cohen’s d) are shown in the bolded rectangles above the distributions.

Results also suggested that children with hearing loss greater than 45 dB HL were at greater risk for delays in speech than children with hearing loss less than 45 dB HL. Examination of the interquartile ranges in Figure 1 reveals considerable overlap across the categories, however, with some children functioning within normal limits and others well below. This suggests that other influential factors are at play and further supports the need to go beyond BEPTA to understand what may be impacting children’s access to the input.

Reduced or inconsistent access to input may occur for a number of reasons beyond severity of loss. First, infants who are HH experience periods without amplification. Even in an era of newborn hearing screening, the average age of HA fitting for infants with mild to severe hearing loss is approximately 6 to 11 months of age (Spivak, Sokol, Auerbach, & Gershkovich, 2009; Walker et al., 2013). This suggests that infants who are HH have a period of restricted auditory access prior to HA fitting. Once HAs are fit, infants experience variations in their daily use of the technology, especially during the second year of life (Walker, et al., 2013). Additionally, HAs themselves have limitations, including restricted bandwidth that limits access to consonants with energy in the high frequency range, especially for child or female talkers (Stelmachowicz, Pittman, Hoover,& Lewis, 2001). Furthermore, young children do not live in well-controlled acoustic environments. Rather, they go in and out of noisy and reverberant settings. Noise and reverberation levels present in typical settings are known to negatively affect speech perception even in children with NH (Klatte, Lachmann, & Meis, 2010), representing a further source of limited access to input for HH children. The OCHL research team suspects that these multiple factors combine to impact the child’s access to input and, ultimately, the child’s cumulative auditory experience. These issues, in turn, have consequences for child language development.

A global profile of HH children’s outcomes at 3 years of age (see Figure 2) lends support to the proposal that selected domains of language learning may be especially vulnerable to the effects of hearing loss. This profile was generated based on work by Tomblin et al. (2014) that explored the contributions of aided hearing to children’s speech and language outcomes. Compared to the standardization sample for selected tests, children with moderate to moderately-severe hearing loss demonstrated relative weaknesses in syntax (M = 84.48; SD = 13.89) and articulation skills (M = 83.20; SD = 19.04), two areas that would appear to be dependent on processing fine details in the input. Although the performance of children with mild hearing loss compares more favorably to the standardization samples note that their standard scores trended toward the lower end of the average range for syntax (M = 90.84; SD = 12.65) and articulation (M = 93.00; SD = 12.97). In contrast, performance of both HH groups was within the average range on basic concepts and pragmatics.

Figure 2. Standard scores for HH children on the Comprehensive Assessment of Spoken Language (basic concepts [n = 72], syntax [n = 70], and pragmatics [n=70]) and the Goldman-Fristoe Test of Articulation [n = 74] at 3 years of age plotted as a profile on the normal distribution. Mean scores for children with mild hearing loss (triangles) are differentiated from those with moderate and moderately-severe hearing loss (circles).

The OCHL team has recently been exploring whether these early-observed vulnerabilities resolve with age or whether they persist into the school-age years. Recent research from the OCHL team suggests that some children demonstrate persistent vulnerability in grammatical morphology (Koehlinger, Owen Van Horne, & Moeller, 2013). Accuracy of production of grammatical markers on verbs was evaluated by coding the use of grammatical word endings in spontaneous language samples from

145 HH children and 40 NH children who were 3 or 6 years of age. Significant between-group differences were found with HH children making more errors than the NH children at both ages. Although many children in the HH group performed like their NH peers, some HH children (38%-63%) fell more than 1 standard deviation below the NH group at both ages. The HH children in the 6-year-old group were identified as having hearing loss on average two years later than the 3 year olds, which is important to consider. The question about whether early deficits resolve needs to be addressed using longitudinal rather than cross sectional data, which is a future goal of the OCHL team. In this same study, after controlling for age, auditory variables (BEPTA and audibility measures) contributed to morpheme production accuracy. It may be that children who are HH are at higher risk than NH children for delays in morphology due to reduced or inconsistent exposure to the grammatical morphemes; HH children may sometimes hear morphemes and at other times do not (McGuckian & Henry, 2007). In addition, the fricatives /s/ and /z/ have a prominent role in spoken English grammar, and are challenging for HH children to perceive (Stelmachowicz, Pittman, Hoover, & Lewis, 2002) and produce (Elfenbein, Hardin-Jones, & Davis, 1994).

Similar concern for persistent vulnerability in specific domains is seen in preliminary cross-sectional data from the Goldman-Fristoe Test of Articulation. As shown in Figure 3, significant between-group differences were observed in articulation skills at 3, 5, and 7 years of age (p values < .001). It is clear from examining the distribution of scores at age seven that some children are at particular risk for persistent delays in speech production. These data support the view that some HH children and selected aspects of development are particularly vulnerable in the context of early hearing loss.

Figure 3. Standard scores on the Goldman-Fristoe Test of Articulation (GFTA) at 3, 5, and 7 years of age for both NH and HH groups.

Modeling Factors That Impact Access to

Linguistic Input

The OCHL research team is working to develop a model to guide the identification of factors that link the presence of hearing loss to poor linguistic outcomes in some cases and not others. Although the model continues to evolve, three factors have garnered attention from the research team: 1) audibility of the speech spectrum with amplification, 2) consistency and duration of HA use, and 3) quantity and quality of linguistic input in the home environment.

The OCHL team was interested in studying audibility, but wanted to specifically isolate the contribution of children’s hearing aids to outcomes in 180 HH preschoolers (Tomblin, et al., 2014). The contribution of the hearing aids is evaluated using the Speech Intelligibility Index (SII), which is a weighted measure of the proportion of the speech spectrum that is audible to the child with or without hearing aids (ANSI, 1997). It is measured on a scale of 0 (meaning nothing is audible) to 1.0 (fully audible). Isolating the unique contribution of the hearing aids is challenging, however, because the degree to which they can boost the audibility is constrained by the degree of hearing loss; less audibility is possible on the more severe end of the degree of hearing loss continuum. In response to this confound, Tomblin and colleagues derived a solution involving a new variable called the residualized SII (rSII). They removed the variance of the unaided SII that was shared with the aided SII using linear regressions. The residual variance produced by two linear functions in the regression formed the rSII. This new rSII measure reflects the audible hearing provided by the HA independent of unaided hearing. Tomblin et al. found that audibility provided by the HAs was significantly associated with speech and language outcomes and that benefits were inclusive of children with mild and moderate-to-severe hearing loss. These results extend the findings of Stiles, Bentler, and McGregor (2012) who found associations of SII with language outcomes in school-age HH children.

Inconsistent HA use would also be expected to impact children’s audibility and access to linguistic input. Consistency of hearing aid use was found to be more challenging at younger ages (i.e., toddlers), with milder degrees of hearing loss, and in families with lower levels of education (Walker, et al., 2013). These findings also speak to the need to provide unique supports to families with children who experience challenges with hearing aid use (Moeller, Hoover, Peterson, & Stelmachowicz,2009). A related variable exerting influence on audibility benefits appears to be the duration of HA experience. The reader is referred to Tomblin et al. (2014), who demonstrated that the amount of benefit from aided hearing interacted with the duration of the child’s hearing aid experience. With longer periods of hearing aid use, audibility provided by the hearing aid became more reliably associated with better outcomes. This finding fits with the view that duration of auditory experience influences language development.

If HH children have inconsistent access to linguistic input, a way to buffer the effects is to provide rich language exposure in the home environment. In fact, many practices in early intervention strive to achieve this very goal. As part of the OCHL project, a subset of families participated in a project where the children wore a digital language processor, the Language ENvironment Analysis (LENA) device, which gathered full day recordings in the home environment. Characteristics of the child’s home language environment were examined using LENA automated analyses. Families of 22 HH children, aged 24 – 36 months were compared to eight families with NH children on measures of amount of talk. The groups did not differ in the numbers of words that adults used or in the number of conversational turns. For the HH group, the numbers of conversational turns taken by adults with the HH child, but not adult word counts, were associated with children’s receptive language outcomes (VanDam, Ambrose, & Moeller, 2012). The results underscore the importance of qualitative aspects of parent-child interaction in promoting language development. In a more recent examination of data from 28 of the HH toddlers who used the LENA device, the research team found further support for the influence of conversational turns on children’s language outcomes. They also found that higher amounts of television time (electronic media) were associated with a reduction in the conversational exchanges known to promote language (Ambrose, VanDam, & Moeller, 2013). These findings suggest the value of cautioning parents about the potentially negative effects of television exposure on the frequency of parent-child interactions. Qualitative aspects of parent-child interactions are currently being further explored by OCHL researchers using video recorded samples.

Summary of Protective Factors

The findings to date have led the researchers to consider factors that provide protection for children against the risks associated with early and persistent bilateral hearing loss. To summarize, better speech and language outcomes are associated with the following factors: 1) milder degrees of hearing loss, 2) better aided audibility, 3) well-fit hearing aids (see McCreery, Walker, & Spratford in this volume), 4) longer duration of HA fitting, 5) more consistent use of amplification, 6) higher quantity and quality of language interactions, and 7) higher levels of maternal education. Several of these factors can be addressed by adhering to best practices.

Clinical Implications

Several clinical implications can be derived from the results to date. Importantly, OCHL results support the audiological practice of optimizing children’s audibility with HAs. It is beneficial to provide children with the best possible access to the speech spectrum to support speech and language development. It appears from this work that the benefits of audibility will be increasingly apparent as children gain auditory experience from longer durations of device use, and this supports the practice of early hearing aid fitting. Audiologists routinely promote consistent HA use with families, but OCHL results suggest that families with toddlers, less educated parents, and parents of children with mild hearing loss encounter unique barriers to regular use. Novel counseling strategies that are adapted to the specific needs of these families are required. Audiologists are encouraged to ask questions that are tailored to identifying these unique needs and then provide responsive resources for families. Finally, audiologists are encouraged to support families in their provision of nurturing language interactions, which includes reducing auditory distractions to enhance the child’s access to parental-child conversations. Through such practices, children who are HH may no longer be described as “forgotten.”

Acknowledgments

This work was supported by National Institutes of Health Grants NIH/NIDCD 5 ROI DC009560 (co-principal investigators, J. Bruce Tomblin, University of Iowa and Mary Pat Moeller, Boys Town National Research Hospital) and T32 DC000013. The content of this project is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Deafness and Other Communication Disorders or the National Institutes of Health. The authors thank the children and families who participated in this project, Beth Walker for comments on an earlier version of the manuscript, and all of the members of the OCHL team for their contributions to the work.

References

Ambrose, S. E., VanDam, M., & Moeller, M. P. (2013). Linguistic input, electronic media, and communication outcomes of toddlers with hearing loss. Ear & Hearing, 35(2), 139-147.

ANSI. (1997). Methods for calculation of the speech intelligibility index. Technical Report S3.5-1997. American National Standards Institute, New York, NY.

Blair, J. C., Peterson, M. E., & Viehweg, S. H. (1985). The effects of mild sensorineural hearing loss on academic performance of young school-age children. Volta Review, 87, 87-93.

Davis, J. M. (1977). Our forgotten children: Hard-of-hearing pupils in the schools. Minneapolis, MN: University of Minnesota.

Davis, J. M., Elfenbein, J., Schum, R., & Bentler, R. A. (1986). Effects of mild and moderate hearing impairments on language, educational, and psychosocial behavior of children. Journal of Speech and Hearing Disorders, 51(1), 53-62.

Davis, J. M., Stelmachowicz, P. G., Shepard, N. T., & Gorga, M. P. (1981). Characteristics of hearing-impaired children in the public schools: Part II--Psychoeducational data. Journal of Speech and Hearing Disorders, 46(2), 130-137.

Durieux-Smith, A., Fitzpatrick, E., & Whittingham, J. (2008). Universal newborn hearing screening: A question of evidence. International Journal of Audiology, 47(1), 1-10. doi: 10.1080/14992020701703547

Eisenberg, L. S., Widen, J. E., Yoshinaga-Itano, C., Norton, S., Thal, D., Niparko, J. K., & Vohr, B. (2007). Current state of knowledge: Implications for developmental research--key issues. Ear and Hearing, 28(6), 773-777.

Elfenbein, J. L., Hardin-Jones, M. A., & Davis, J. M. (1994). Oral communication skills of children who are hard of hearing. Journal of Speech and Hearing Research, 37(1), 216-226.

Fitzpatrick, E. M., Crawford, L., Ni, A., & Durieux-Smith, A. (2011). A descriptive analysis of language and speech skills in 4to 5-yr-old children with hearing loss. Ear and Hearing, 32(5), 605-616. doi: 10.1097/ AUD.0b013e31821348ae

Gilbertson, M., & Kamhi, A. G. (1995). Novel word learning in children with hearing impairment. Journal of Speech and Hearing Research, 38(3), 630-642.

Goldman, R., & Fristoe, M. (2000). Goldman-Fristoe Test of Articulation-2. Circle Pines, MN: American Guidance Service.

Halpin, K. S., Smith, K. Y., Widen, J. E., & Chertoff, M. E. (2010). Effects of universal newborn hearing screening on an early intervention program for children with hearing loss, birth to 3 yr of age. Journal of the American Academy of Audiology, 21(3), 169-175. doi: 10.3766/jaaa.21.3.5

Holte, L., Walker, E., Oleson, J., Spratford, M., Moeller, M. P., Roush, P., . . . Tomblin, J. B. (2012). Factors influencing follow-up to newborn hearing screening for infants who are hard of hearing. American Journal of Audiology, 21(2), 163-174. doi:10.1044/1059-

0889(2012/12-0016)

Klatte, M., Lachmann, T., & Meis, M. (2010). Effects of noise and reverberation on speech perception and listening comprehension of children and adults in a classroom-like setting. Noise and Health, 12(49), 270-282.

Koehlinger, K. M., Owen Van Horne, A. J., & Moeller, M. P. (2013). Grammatical outcomes of 3 & 6 year old children who are hard of hearing. Journal of Speech, Language, and Hearing Research, 56(5). doi: 10.1044/1092-4388(2013/12-0188)

Leonard, L. B. (1989). Language learnability and specific language impairment in children. Applied Psycholinguistics, 10(2), 179-202.

McGuckian, M., & Henry, A. (2007). The grammatical morpheme deficit in moderate hearing impairment. International Journal of Language & Communication Disorders, 42(S1), 17-36.

Moeller, M. P., Hoover, B., Peterson, B., & Stelmachowicz, P. G. (2009). Consistency of hearing aid use in infants with early-identified hearing loss. American Journal of Audiology, 18(1), 14-23. doi: 10.1044/1059-0889(2008/08-0010)

Moeller, M. P., Tomblin, J. B., Yoshinaga-Itano, C., Connor, C. M., & Jerger, S. (2007). Current state of knowledge: Language and literacy of children with hearing impairment. Ear and Hearing, 28(6), 740-753. doi: 10.1097/AUD.0b013e318157f07f

Slobin, D. I. (1985). Crosslinguistic evidence for the language-making capacity. In D. I. Slobin (Ed.), The crosslinguistic study of language acquisition (Vol. 2, pp. 1157-1256). Hillsdale, NJ: Lawrence Erlbaum Associates.

Spivak, L., Sokol, H., Auerbach, C., & Gershkovich, S. (2009). Newborn hearing screening follow-up: Factors affecting hearing aid fitting by 6 months of age. American Journal of Audiology, 18(1), 24-33. doi: 10.1044/1059-0889(2008/08-0015)

Stelmachowicz, P. G., Pittman, A., Hoover, B., & Lewis, D. (2001). Effect of stimulus bandwidth on the perception of /s/ in normal-and hearing-impaired children and adults. Journal of the Acoustical Society of America, 110, 2183-2190. doi: 10.1121/1.1400757

Stelmachowicz, P. G., Pittman, A., Hoover, B., & Lewis, D. (2002). Aided perception of /s/ and /z/ by hearing-impaired children. Ear and Hearing, 23(4), 316-324.

Stiles, D. J., McGregor, K. K., & Bentler, R. A. (2012). Vocabulary and working memory in children fit with hearing aids. Journal of Speech, Language, and Hearing Research, 55(1), 154-167. doi: 10.1044/1092-4388(2011/11-0021)

Tomblin, J. B., Oleson, J., Ambrose, S. E., Walker, E. A., & Moeller, M. P. (2014). The influence of hearing aids on speech and language development in children with hearing loss. JAMA Otolaryngology Head and Neck Surgery, 140(5), 403-409. doi:10.1001/jamaoto.2014.

Tomblin, J. B., Oleson, J., Ambrose, S. E., Walker, E. A.,& Moeller, M. P. The influence of hearing aids on speech and language development in children with hearing loss. JAMA Otolaryngology.

Tomblin, J. B., Records, N. L., Buckwalter, P., Zhang, X., Smith, E., & O’Brien, M. (1997). Prevalence of specific language impairment in kindergarten children. Journal of Speech, Language, and Hearing Research, 40(6), 1245-1260.

VanDam, M., Ambrose, S. E., & Moeller, M. P. (2012). Quantity of parental language in the home environments of hard-of-hearing 2-year-olds. Journal of Deaf Studies and Deaf Education, 17(4), 402-420. doi: 10.1093/deafed/ens025

Walker, E. A., Spratford, M., Moeller, M. P., Oleson, J., Ou, H., Roush, P., & Jacobs, S. (2013). Predictors of hearing aid use time in children with mild-to-severe hearing loss. Language, Speech, and Hearing Services in the Schools, 44(1), 73-88. doi: 10.1044/0161-

1461(2012/12-0005)

C H A P T E R  F O U R

Are We on Target With Our

Pediatric Hearing Aid Fittings?

Ryan W. McCreery, Ph.D. Elizabeth Walker, Ph.D. Meredith Spratford, Au.D.

Abstract

Children who are hard of hearing rely on amplification to provide audibility that supports positive developmental outcomes. Previous investigations have used milestones such as age of identification with hearing loss or age at which amplification was received to quantify the impact of amplification on development. However, these milestones do not adequately reflect the variability in cumulative auditory experience that may occur related to differences in aided audibility of speech or the amount of hearing aid use either across children or over time. The impact of aided audibility of speech and hearing aid use on developmental outcomes is presented. Clinical suggestions for maximizing audibility and hearing aid use for children who are hardof-hearing are also discussed.

Children with permanent hearing loss either at birth or during childhood have historically experienced delays in speech and language development, diminished social opportunities and limited academic achievement. Prior to the adoption of universal newborn hearing screening programs and early hearing detection and intervention programs in the United States, the age of identification for children with hearing loss was often not until 18-24 months of age (Moeller, 2000). Many early studies of developmental outcomes in children with hearing loss revealed substantial delays in development (Davis et al. 1986). Hearing loss not only limits immediate access to the acoustic cues needed for communication, but also alters the cumulative auditory experience of children. For this reason, hearing aids must not only restore audibility, but be used consistently during early childhood in order to minimize the likelihood of developmental delays. Previous studies regarding the development of children with hearing loss who use amplification have not routinely described how much audibility was provided by the fitting and how much children used their hearing aids. The goals of this article are to review what is known about aided audibility of speech and hearing aid use among children with hearing loss, and provide clinicians with practical strategies for maximizing these positive predictors of developmental outcomes.

Speech Audibility

Audibility describes how much of the speech signal can be heard. The speech intelligibility index (SII; ANSI S3.5-1997) is a standardized method of quantifying audibility. The SII is expressed as a proportion (between 0 and 1) or percentage (between 0% and 100%), where higher values represent greater audibility of the speech signal. The primary purpose of the SII with children with hearing loss is to quantify the amount of speech information that is audible to the child with and without their hearing aids. Unaided audibility is often used to quantify the effects of hearing loss or noise on the audibility of speech without amplification. Aided audibility describes how much of the speech signal is audible when the speech spectrum is amplified. Both measures should be documented as part of the hearing aid verification process. Speech audibility can be graphically estimated using an SPL-o-gram. The SPL-o-gram plots dB sound pressure level (SPL) as a function of frequency in Hertz. The speech spectrum is represented on the SPL-o-gram using the long-term average speech spectrum (LTASS). The LTASS represents the frequency range and level for a speech signal averaged over time and is plotted relative to the hearing thresholds in SPL. The proportion of the LTASS that is above the hearing thresholds represents the audible portion of the speech spectrum. The LTASS is usually referenced to an average conversational level for speech from 1 meter away, which is usually equivalent to an overall level of 60 or 65 dB SPL, but can also be used to represent speech at other levels (soft at 50 dB SPL and loud at 75 dB SPL).

The impact of aided audibility on outcomes has recently been highlighted by several studies of speech and language development in children who are hard of hearing. Development of vocabulary (Stiles et al. 2012) and the structural aspects of language, including morphology and syntax (Koehlinger, Van Horne, & Moeller, 2013), have been shown to be higher in children with higher aided audibility than for peers who wear hearing aids that provide less aided audibility. The amount of the speech signal that is audible to children with amplification can directly impact auditory access and subsequent speech and language outcomes and is thus, a key component in the clinical assessment of amplification. However, previous longitudinal studies of outcomes have often used other variables to represent the impact of amplification on developmental outcomes, including age of identification of hearing loss (Moeller, 2000; Yoshinaga-Itano, 2003; Kennedy et al. 2006), age of fitting with amplification (Wake et al. 2004; Ching et al. 2013; Sininger et al. 2010) and pure tone average (Ching et al. 2013; Sininger et al. 2010). While these variables may indirectly reflect the duration or amount of cumulative auditory experience children have with amplification, each also has specific limitations as an indicator of cumulative auditory exposure.

Age of identification with hearing loss or age of fitting with amplification have been the most frequently identified factors used to predict outcomes in children with hearing loss. Prior to universal newborn hearing screening, the age of identification or hearing aid fitting was often used to reflect the duration of auditory deprivation that children experienced prior to amplification. Children with later ages of identification or fitting would be expected to have limited access to sound during sensitive developmental periods and also be predicted to have poorer outcomes. Age of identification (Moeller, 2000; Yoshinaga-Itano, 2003; Kennedy et al. 2006) was an influential predictor of developmental outcomes prior to newborn hearing screening, primarily because the ages at which children were identified with hearing loss and enrolled in intervention varied considerably. For example, Moeller (2000) reported data from a sample that included both earlyand later-identified children with hearing loss and found a range of age of identification from birth to 4.5 years. As newborn hearing screening has become more widely available, the age of identification of hearing loss has decreased and become more uniform among states (Holte et al. 2012). While the decreasing age of identification has undoubtedly had a positive impact on outcomes, greater uniformity in age of identification and the related milestone of age of hearing aid fitting have made these variables less able to predict variability in outcomes. Age of hearing aid fitting, for example, has been positively related to some speech and language outcomes in one investigation (Sininger et al. 2010), but has not been predictive of outcomes in others (Wake et al. 2004; Ching et al. 2013).

Another limitation of age of identification or amplification as a predictor of outcomes is that these variables assume that audibility for children with hearing loss is binary. Specifically, these variables assume that the period of time prior to intervention had little or no contribution to the child’s development and also that once the child is diagnosed with hearing loss, the benefits of amplification are fully activated and constant thereafter. While this may reflect the experience of children with profound hearing loss prior to amplification, the amount of audibility received by children with mild to severe hearing loss, with and without amplification depends on their degree of hearing loss and how well their hearing aids are fit. Some studies have attempted to take this variability into account by using the pure tone average as a predictor of audiological outcomes. The pure tone average is an average of either three or four mid-frequency audiometric frequencies. The most common frequencies used to calculate pure tone average are 500, 1000 and 2000 Hz or those three frequencies plus 4000 Hz.

However, pure tone average has had mixed results predicting variability in outcomes with some studies finding greater pure tone averages associated with poorer outcomes (Sininger et al. 2010) and other studies finding no relationship (Moeller, 2000) or only a relationship with specific developmental outcomes (Ching et al. 2013). Although pure tone average provides a single numerical estimate of the degree of hearing loss, this variable does not represent how much the child is able to hear with amplification, particularly since children with the same pure tone average may have varying degrees of aided audibility through their hearing aids depending on how closely the hearing aids are fit to prescriptive targets (McCreery et al. 2013). Interestingly, one recent study that found a correspondence between pure tone average and language outcomes was a study where all of the children were fit with amplification that was verified to provide optimal audibility (Sininger et al. 2010); thus, the relationship between pure tone average and aided audibility was so consistent that aided audibility had to be excluded from statistical models. Other investigations have shown that the children with hearing loss in clinical populations do not have consistent aided audibility (Strauss & van Dijk, 2008; McCreery et al. 2013). Therefore, the amount of aided audibility depends not only on the degree of hearing loss, but also on whether or not amplification is programmed and verified to provide adequate audibility. Children with higher aided audibility and well-fit amplification are predicted to have a more optimal auditory experience, which should help to mitigate the negative effects of hearing loss on development.

Hearing Aid Use

As described above, recent studies suggest that increased aided audibility with hearing aids influences language outcomes (Koehlinger, Van Horne, & Moeller,

2013; Stiles, Bentler, & McGregor, 2012). Presumably, however, the advantages of appropriately-fit hearing aids will only occur if children wear their devices on a consistent basis. There are two clinically-useful objective and subjective strategies for determining how frequently children wear their devices: data logging and parent report measures. Investigations utilizing these methods demonstrate that there is variability in hearing aid use time in young children (Jones & Launer, 2011; Moeller, Hoover, Peterson, & Stelmachowicz, 2009; Walker et al., 2013). These methods may also be appropriate when counseling parents on how to achieve consistent hearing aid use over time.

Data Logging

Many current hearing aid models now have data logging, an automatic feature built into the hearing aid which records information about the hearing aids over time, including average hours of daily use. Investigations using data logging features have shed new light on everyday practices for children with hearing aids. Walker et al. (2013) collected data logging information on 133 children, ranging in age from 8 months to 8 years. On average, data logging indicated that children wore hearing aids 8.3 hours per day, but usage varied across participants from 0 to 16 hours. Nineteen percent wore hearing aids for 4 hours or less per day and 12% were “full-time hearing aid users” (more than 12 hours per day). In a separate study, Jones and Launer (2011) obtained data logging on approximately 5000 children, ages birth to 19 years. The average use time for the entire sample was 5.5 hours per day, with wide variation across participants. Forty percent wore hearing aids for 4 hours or less, and 10% were full-time hearing aid users (more than 12 hours per day). Results for both of these studies lend support for the notion that there are individual differences in the amount of daily hearing aid use in children with hearing loss, and a number of children are not achieving full-time use with hearing aids.

Parent Report Measures

Moeller, Hoover, Peterson, and Stelmachowicz (2009) were among the first to explore individual variations in parent-report for pediatric hearing aid compliance. They conducted longitudinal interviews with mothers of seven early-identified infants with mild to moderate hearing loss (age range = 11 to 28.5 months). Rather than asking mothers to estimate average daily hearing aid use, the researchers evaluated hearing aid use with a Likert scale for different situations (e.g., in the car, book sharing, at the playground, etc.). Results showed that the infants were inconsistent hearing aid users for most situations prior to two years of age. Only two out of the seven parents were able to establish early, consistent usage across all contexts. Over time, consistency of use increased, although even at 28 months, there were still some unsupervised situations that parents found problematic, such as riding in the car.

Walker et al. (2013) used a similar parent-report rating scale with a larger number of participants (n = 272) and wider age range (5 months to 7 years, 3 months). Results were consistent with the findings from Moeller et al. (2009); amount of hearing aid use increased with chronological age and unsupervised situations were more challenging than supervised situations. In addition, children with more severe hearing loss (greater than 50 dB HL) were reported to wear hearing aids more consistently across different contexts than children with milder hearing loss (less than 50 dB HL). The use of parent-report consistency ratings across different listening situations provides insight into circumstances that were challenging for families. These rating scales may be useful as a counseling tool, in conjunction with data logging measures, to help parents become more aware of situations in which consistent hearing aid use is difficult to achieve. This awareness, in turn, could help parents be better prepared to cope with problematic contexts and increase consistent usage in these contexts.

Predictors of Variation in Hearing

Aid Use

Both the Jones and Launer (2011) and Moeller et al. (2009) studies were limited in that they could not identify childor family-specific factors that influenced individual differences in average daily hearing aid use. Such information has clinical value, because it could help direct audiological counseling practices. Walker et al. (2013) addressed the question of predictors of average daily hearing aid use with a cross-sectional sample of 272 children who were hard of hearing, between the ages of 5 months to 7 years, 3 months. Results from a multiple regression analysis showed that longer daily hearing aid use (based on subjective parent report) was related to older age, poorer hearing, and higher maternal education level. These results suggest a possible need for more counseling with families of pediatric hearing aid recipients, particularly children with milder hearing loss and families with lower education levels.

Both aided audibility and the amount of hearing aid use are predicted to reflect cumulative auditory experience in children with hearing loss. Children who use hearing aids that provide adequate audibility on a consistent basis are likely to experience better developmental outcomes than children who either have poor aided audibility or do not consistently use amplification. Speech recognition in noise data from the Outcomes for Children with Hearing Loss study are presented as an example of how audibility and hearing aid use may impact outcomes. Figure 1 shows aided and unaided word and phoneme recognition in steady-state noise from the Computer-Aided Speech Perception Assessment (CASPA) collected on a group of 7 year-old children who wear hearing aids compared to a group of age-matched children with normal hearing. Figure 2 shows the relationship between aided audibility and word recognition and average hours of hearing aid use per day and word recognition. Linear regression was used to predict word recognition using aided audibility and hearing aid use, while controlling for degree of hearing loss. Aided audibility was a significant predictor of word recognition in noise; however, average amount of hearing aid use was not found to predict word recognition after controlling for degree of hearing loss.

Figure 1. Word (Left panel) and Phoneme (Right panel) recognition for 7 year-old children at -5 dB, 10 dB and 20 dB signal-to-noise ratios (SNR). Triangles represent the means for unaided conditions for children who are hard of hearing (CHH) and hourglasses represent the means for aided conditions. Error bars represent +/one standard deviation. The cross-hatched area represents the range of performance for children with normal hearing.

Figure 2. Word recognition as a function of aided audibility (Left panel) and average hours of hearing aid use (Right panel). Regression line represents the bivariate relationship between word recognition and each variable. The R2 values in each panel represent the linear regression model with each variable as a predictor of word recognition, controlling for unaided audibility (SII).

The example highlights the challenges of using hearing aid use to predict complex outcomes like speech recognition. Hearing aid use and degree of hearing loss are positively associated; children who have greater degrees of hearing loss use their hearing aids more hours per day on average than children with less hearing loss. Additionally, the majority of the children in the sample were consistent hearing aid users by age 7, which means that the amount of hearing aid use in the sample may have been sufficient to support the skills needed to develop speech recognition in noise. Further analyses of these data will attempt to use longitudinal models to predict how audibility and hearing aid use earlier in childhood might impact outcomes in school-age children who wear hearing aids.

Clinical Implications

Audiologists and early intervention service providers are in a unique position to support parents and convey how amplification early in life may prevent communication delays. Parents are also in the best position to monitor the consistency of hearing aid use in everyday situations. Service providers can utilize parent ratings of hearing aid use consistency across situations as a tool for encouraging parents to increase overall use as their child grows and develops. The consistency ratings can also be used to point out specific circumstances where the child will potentially benefit from increased access to quality communication. Targeting these situations will help parents focus their efforts on giving their child access to sound that is meaningful to their development. For example, targeting device use at the breakfast table when all family members are engaging in conversation or during a vocabulary-rich book reading session at night may be more beneficial than using the hearing aids in the car where conversation is difficult to overhear and follow. Temperament, behavior, and infant state may be obstacles to consistent hearing aid use early in life. Likewise, there are situations that will not be realistic opportunities for consistent device use due to safety or equipment concerns, such as when unsupervised in the car or outdoors. Providers who understand these obstacles, and can offer coping strategies, will be better able to counsel parents on realistic expectations for device use in these challenging situations. Data logging features may be used in conjunction with parent reports of hearing aid use to make parents more aware of their children’s everyday listening environments. In addition to information obtained about the average number of hours of hearing aid use, current hearing aids may also provide environmental classifier information. Environmental classifiers calculate the percentage of time the hearing aid user spends in different listening contexts (e.g, quiet, speech only, speech in noise, and noise only). In the case of pediatric hearing aid users, environmental classifiers could be used to counsel parents about how much time their child spends in quiet or noisy situations. A recent study with the Outcomes for Children with Hearing Loss cohort showed that time spent in background noise (i.e., with the television or radio on) decreases opportunities for parent-child interaction, which has a negative effect on language outcomes for children with hearing loss (Ambrose et al., 2014). Parents may not be cognizant of how often the television or radio is on in the home, simply because it is background noise. Using the environmental classifier feature creates opportunities for discussion with parents and caregivers about minimizing background noise. Further research is needed to validate the accuracy of hearing aid classification schemes.

Additional counseling for families with lower educational levels should be given regarding the direct relationship between consistent hearing aid use, learning, and brain development. The emphasis on learning and brain development may help families better understand that achieving successful communication outcomes at a young age may lead to ease of learning in school and social activities later in life. Another subgroup of children that do not achieve consistent hearing aid use are those who have mild hearing loss. Children with mild hearing loss deserve pointed attention in terms of counseling. Some families (and audiologists) see the child responding to sound and developing speech and thus, feel the child does not need to wear their hearing aids. The evidence base now shows that audibility from hearing aids benefits children with mild hearing loss as much as for children with moderate and severe hearing loss. Thus, along with well-fit amplification, consistent use is vital to prevent delays in their development, just as it is for children with moderate and severe degrees of hearing loss.

Summary

Speech and language delays may be ameliorated with well-fit, consistently worn hearing aids. Children who are hard of hearing receive the most benefit from their hearing aids when audibility is optimally fit. Audiologists need to remain vigilant regarding developmental changes of their pediatric patients by consistently applying RECD measurements to programming gain adjustments. By verifying audibility at several levels of input with speech mapping and comparing to normative audibility data (Bagatto et al. 2011), audiologists can further ensure that soft and conversational speech are able to be heard. Furthermore, audiologists have several tools at their disposal to confirm that children are wearing hearing aids on a consistent basis. By using data logging and asking specific questions about the situations where hearing aid use is most beneficial and also most challenging, audiologists can help to support families in establishing consistent hearing aid use for their children.

Acknowledgement

This work was supported by NIH-NIDCD grants

R01DC009560 and R03DC012635

References

Ambrose, S. E., VanDam, M., & Moeller, M. P. (2014). Linguistic input, electronic media, and communication outcomes of toddlers with hearing loss. Ear and Hearing, 35(2), 139-147.

American National Standards Inst. (1997). ANSI S3.5-1997: American National Standard Methods for Calculation of the Speech Intelligibility Index. American National Standards Institute, New York.

Bagatto, M. P., Moodie, S. T., Malandrino, A. C., Richert, F. M., Clench, D. A., & Scollie, S. D. (2011). The University of Western Ontario pediatric audiological monitoring protocol (UWO PedAMP). Trends in Amplification, 15(1), 57-76.

Ching, T. Y., Dillon, H., Marnane, V., Hou, S., Day, J., Seeto, M., ... & Yeh, A. (2013). Outcomes of early-and late-identified children at 3 years of age: Findings from a prospective population-based study. Ear and Hearing, 34(5), 535-552.

Davis, J. M., Elfenbein, J. L., Schum, R. L., & Bentler, R. A. (1986). Effects of mild and moderate hearing impairments on language, educational, and psychosocial behavior of children. Journal of Speech & Hearing Disorders, 51, 53-62.

Holte, L., Walker, E., Oleson, J., Spratford, M., Moeller, M. P., Roush, P., ... & Tomblin, J. B. (2012). Factors influencing follow-up to newborn hearing screening for infants who are hard of hearing. American Journal of Audiology, 21(2), 163.

Jones, C., & Launer, S. (2011). Pediatric Fittings in 2010: The Sound Foundations Cuper project. In R. C. Seewald & J. M. Bamford (Eds.), A Sound Foundation through Early Amplification: Proceedings of the 2010 International Conference (pp. 187-192). Chicago, IL: Phonak AG.

Kennedy, C. R., McCann, D. C., Campbell, M. J., Law, C.M., Mullee, M., Petrou, S., ... & Stevenson, J. (2006). Language ability after early detection of permanent childhood hearing impairment. New England Journal of Medicine, 354(20), 2131-2141.

Koehlinger, K. M, Van Horne, J., Owen, A. & Moeller, M.P. (2013). Grammatical outcomes of 3-and 6-year-old children who are hard of hearing. Journal of Speech, Language, and Hearing Research, 56(5),1701-1714.

McCreery, R. W., Bentler, R. A., & Roush, P. A. (2013). The characteristics of hearing aid fittings in infants and young children. Ear and Hearing, 34, 701-710.

Moeller, M. P. (2000). Early intervention and language development in children who are deaf and hard of hearing. Pediatrics, 106(3), e43-e43.

Moeller, M. P., Hoover, B., Peterson, B., & Stelmachowicz, P. (2009). Consistency of hearing aid use in infants with early-identified hearing loss. American Journal of Audiology, 18(1), 14-23.

Sininger, Y. S., Grimes, A., & Christensen, E. (2010). Auditory development in early amplified children: factors influencing auditory-based communication outcomes in children with hearing loss. Ear and Hearing, 31(2), 166.

Stiles, D. J., Bentler, R. A., & McGregor, K. K. (2012).

The speech intelligibility index and the pure-tone average as predictors of lexical ability in children fit with hearing aids. Journal of Speech, Language and Hearing Research, 55(3), 764.

Strauss, S., van Dijk, C. (2008). Hearing instrument fittings of pre-school children: Do we meet the prescription goals? International Journal of Audiology,47(S1), S62-S71.

Wake, M., Hughes, E. K., Poulakis, Z., Collins, C., & Rickards, F. W. (2004). Outcomes of children with mild-profound congenital hearing loss at 7 to 8 years: a population study. Ear and Hearing, 25(1), 1-8.

Walker, E. A., Spratford, M., Moeller, M. P., Oleson, Ou, H., Roush, P., & Jacobs, S. (2013). Predictors of hearing aid use time in children with mild-to-severe hearing loss. Language, Speech, and Hearing Services in Schools, 44(1), 73-88.

Yoshinaga-Itano, C. (2003). From screening to early identification and intervention: Discovering predictors to successful outcomes for children with significant hearing loss. Journal of Deaf Studies and Deaf Education, 8(1), 11-30.

C H A P T E R  F I V E

Monitoring Outcomes of Infants and Children Who Wear Hearing Aids

Marlene P. Bagatto, Au.D., Ph.D.

Danielle Glista, Ph.D. Susan D. Scollie, Ph.D.

Abstract

Outcome measurement is a key component of the pediatric hearing aid fitting process that is often overlooked in clinical practice. An understanding of the types of outcome measures and how they can be implemented with children of various age groups and developmental abilities is necessary for successful clinical implementation. This chapter provides an overview of subjective and objective outcome measures used in our program with infants and children who wear hearing aids. The University of Western Ontario Pediatric Audiological Monitoring Protocol (UWO PedAMP) is a recently-developed guideline for evaluating auditory-related outcomes in infants and young children who wear hearing aids. It consists of functional outcome tools in the form of caregiver report questionnaires. These are supported by each child’s hearing aid fitting information (i.e., Speech Intelligibility Index [SII]). The Ling 6(HL) detection task and the UWO Plurals test are a subset of tests derived from laboratory tasks that focus on the detection of speech sounds. These outcome measures have calibrated stimuli recorded on a compact disk for use with clinical equipment. The details of these tools will be discussed in order to support their inclusion in routine clinical practice.

The process of pediatric hearing aid fitting consists of sequential stages to support evidence-based intervention. For infants and children identified as having permanent hearing loss these steps include: the accurate assessment of hearing and ear canal acoustics, calculation of prescriptive targets, the selection of hearing aids and verification that the prescriptive targets are being approximated. Suitable technology and evidence-based hearing aid fitting protocols support the accurate and safe application of these stages (e.g., American Academy of Audiology [AAA], 2013; Bagatto, Scollie, Hyde & Seewald, 2010; King, 2010). Another important aspect of the pediatric hearing aid fitting process is assessing the device(s) effectiveness in daily life. Monitoring functional auditory outcomes of infants and children who wear hearing aids has been supported as a critical component of hearing aid intervention for infants and children (Joint Committee on Infant Hearing [JCIH], 2013). Hearing aid outcome measurement can lead to a better understanding of the infant’s auditory progress, better family engagement and improved collaboration with other professionals. It may also assist with detecting issues with progress by identifying potential concerns before speech and language development is significantly affected. Outlining specific strategies to assess hearing aid(s) effectiveness in daily life may also facilitate the evaluation of overall Early Hearing Detection and Intervention (EHDI) program outcomes.

When considering clinical outcome measurement tools, it is important to keep in mind several factors. Firstly, ensure that the tools are suitable for the target population (i.e., infants and children who wear hearing aids). They should also be suitable for administration and interpretation by the managing audiologist to support successful clinical uptake. Statistical properties such as normative values, validity and reliability of the outcome measurement tools facilitate accurate interpretation of functional auditory outcomes. Finally, the clinical feasibility of an outcome measurement tool is a critical component of achieving the validation stage of the hearing aid fitting process. Outcome measurement tools should not be too time consuming for the clinician or child/family to complete and should result in meaningful information that can support the overall pediatric hearing aid fitting process. Tools that are appropriate for the developmental level of the child will also enable the application of outcome measures in a clinical context.

Outcome measurement tools can be designed to require the child’s direct participation or use observation through caregiver report. An example of a tool requiring participation is the child’s responses to low-level speech sounds in a sound treated room while wearing hearing aids. Also known as an objective measure, this strategy provides the clinician and family with an immediate demonstration of the child’s auditory function in a clinical setting. The success of objective outcome measurement relies on the child’s developmental level, mood and their ability to perform the task reliably for a period of time. In contrast, caregiver reports in the form of questionnaires offer a description of the child’s real-world auditory function. These subjective measures can be completed independently by the caregiver in the waiting room or while the clinician is assessing the child’s hearing aids. The developmental level of the child does not limit the completion of the tool. As a result, there is an opportunity to obtain a description of the auditory function of children with complex needs. Furthermore, it is important to administer questionnaires in the native language of the family and this may pose a barrier for some tools. However, offering interpretation services or a translated version of the questionnaire can alleviate this obstacle. For families with literacy issues, completing the questionnaire interview-style will gather the needed information to describe the child’s auditory function. A multifaceted approach to monitoring outcomes of infants and children who wear hearing aids provides caregivers and clinicians with a way to describe the child’s auditory function through the early months and into the later years of hearing aid use.

The purpose of this article is to outline some available outcome measurement tools that possess the necessary characteristics to support successful clinical administration and interpretation within the pediatric hearing aid fitting process. Both subjective and objective outcome measurement tools will be described, to cover a variety of strategies with which to monitor the auditory function of infants and children who wear hearing aids.

The University of Western Ontario

Pediatric Auditory Monitoring Protocol

An outcome measurement guideline for use with infants and children six years of age and younger is available for clinical use. The University of Western Ontario Pediatric Audiological Monitoring Protocol (UWO PedAMP) was developed and evaluated with the participation of a network of pediatric audiologists (Bagatto, Moodie & Scollie, 2010; Bagatto, Moodie, Malandrino, Richert, Clench & Scollie, 2011; Moodie, Bagatto, Miller, Kothari, Seewald & Scollie, 2011). In the development of these tools, the appropriate statistical properties were considered along with clinical feasibility and utility. The result is a guideline that has been implemented in a clinical context with few barriers. The UWO PedAMP consists of several tools that aim to measure auditory-related outcomes in infants and children who have permanent hearing loss and may or may not wear hearing aids. Specifically, these tools: 1) assess early auditory development and performance; 2) describe the acceptance and use of hearing aids; and 3) define the effectiveness of service delivery. The questionnaires are supported by each child’s hearing aid fitting information (i.e., real-ear-to-coupler difference (RECD), Speech Intelligibility Index [SII]) so that the quality of the hearing aid fitting can be involved in the overall interpretation of the functional outcomes obtained through the questionnaires. To maximize efficiency and clinical interpretation of results, visual tools to permit rapid scoring and data to support interpretation are available. A training manual, score sheets and a list of pertinent publications can be found at www.dslio.com.

The specific outcome measurement tools included within the UWO PedAMP are listed in Table 1. The Amplification Benefit Questionnaire is a satisfaction survey which assesses the caregiver’s acceptance and use of hearing aids and overall satisfaction with the management services provided (Bagatto et al., 2010). It consists of eleven items using a five-point rating scale. Normative values or a score sheet are not currently available; efforts are in progress to examine caregiver responses from an EHDI program in Ontario, Canada.

Table 1: Outcome measurement tools included within the UWO PedAMP.

The LittlEARS Auditory Questionnaire (Tsiakpini, Weichbold, Kuehn-Inacker, Coninx, D’Haese & Almadin, 2004) is a 35-item questionnaire that assesses receptive and semantic auditory behaviors and expressive vocal behavior. The caregiver responds to a yes/no paradigm and the overall score is compared to average and minimum age-dependent values which have been validated in several languages (Coninx, Weichbold, Tsiakpini et al., 2009; Bagatto, Brown, Moodie & Scollie, 2011; Wang, Sun, Liang, Chen & Zheng, 2013). An example of an infant’s outcome on the LittlEARS Auditory Questionnaire is presented in Figure 1. Since the score is within the 95% confidence intervals, it can be concluded that the child is meeting auditory development milestones for her age.

Figure 1: A ten month old infant’s outcome on the LittlEARS Auditory Questionnaire. The middle dashed line indicates average LittlEARS values for normal hearing children and the upper dashed line and lower solid line indicate the upper and lower bound 95% confidence intervals. The score, represented by the filled circle, falls within the non-shaded region and therefore indicates the infant is meeting auditory development milestones for her age.

A longitudinal clinical observation study was conducted using the LittlEARS as part of the UWO PedAMP (Bagatto, Moodie et al., 2011). Through this work, it was determined that caregivers and clinicians found it feasible to complete the questionnaire within a clinical setting (Moodie et al., 2011). In addition, the questionnaire has been shown to be sensitive to medical issues other than hearing loss (Bagatto, Moodie et al., 2011). Specifically, the majority of typically-developing children who have been fitted with hearing aids following an evidence-based protocol are meeting auditory development milestones similar to their normal hearing peers (Bagatto, Moodie et al., 2011). Children in this study who were identified as having other medical issues (i.e., cerebral palsy) or complicating factors that may impact auditory outcomes with hearing aids (i.e., inconsistent hearing aid use) demonstrated lower scores on the LittlEARS Auditory Questionnaire compared to average values (Bagatto, Moodie et al., 2011). Further data for these subgroups is required to obtain a better understanding of their auditory development. However, this work has provided important evidence about the functional auditory outcomes of infants and children fitted with hearing aids using an evidence-based process.

The UWO PedAMP supports the use of both the LittlEARS and Parents’ Evaluation of Aural/Oral Performance of Children (PEACH; Ching & Hill, 2005) in a two-stage process by developmental level. It is suggested that the LittlEARS be used for children from birth to approximately 48 months of age, depending on their score on the tool. During the development of the UWO PedAMP, a comparison of items on the LittlEARS and the PEACH, which has items more appropriate for older children, indicated a stopping rule was needed to make the application of these tools feasible to utilize in a clinical population. Therefore, when a minimum score of 27 or better is achieved on the LittlEARS, the child’s performance is considered to be at a ceiling score. If ceiling is reached, the tool should no longer be administered. Instead, the clinician can begin to administer the PEACH. Children who are younger than 24 months of age and achieve the ceiling score on the LittlEARS may not yet be in the developmental range of the PEACH (Bagatto, Moodie et al., 2011), therefore, the clinician may desire to continue to administer the LittlEARS until the child is 24 months of age, or interpret low scores on the PEACH knowing the child may not yet be within the developmental range of the tool as supported by recent work (Bagatto, Moodie et al., 2011).

The PEACH assesses functional auditory performance in quiet and noisy listening situations. There are 13 items rated by the caregivers using a five-point scale. The rating scale version has been shown to be more acceptable to clinicians and caregivers when compared to the diary version due to lower respondent and administrative burden (Moodie et al., 2011). As caregivers rate their child’s auditory performance over the past week, the overall score is summed, along with summed scores for the quiet and noise subscales. Total scores (overall, quiet, noise) are then converted to percentages. An accompanying score sheet provides assistance with interpretation of individual scores (Figure 2).

Figure 2: The PEACH Rating Scale score sheet from the UWO PedAMP. Percentage scores are listed on the y-axis and plotted within each subscale (overall, quiet, noise) on the x-axis. Scores plotted in the non-shaded region indicate typical auditory performance. Scores plotted in the shaded regions indicate aspects of hearing aid intervention should be reviewed.

Using the score sheet, percentages can be compared to those derived from children with hearing loss who wear hearing aids. This tool can assist in identifying whether a child is or is not performing typical auditory behaviors. Results from the clinical observation study indicate that the PEACH Rating Scale is appropriate for use within the UWO PedAMP with children who wear hearing aids after they have met a certain criteria on the LittlEARS Questionnaire (Bagatto, Moodie et al., 2011). In particular, the study revealed that the majority of typically-developing children with hearing aids who have good quality hearing aid fittings show typical auditory performance while children with hearing aids who have other medical issues or complex factors related to hearing aid use have lower scores on the PEACH (Bagatto, Moodie et al., 2011). The group differences were not statistically significant, though the trend was evident. Further evidence gathering is being pursued to characterize these important clinical subgroups.

The clinical observation study using the UWO PedAMP provided important information about the previous stages of the pediatric hearing aid fitting process: when a systematic, evidence-based protocol for the selection and fitting of hearing aids to infants and children is applied, good functional auditory outcomes are possible. The application of the UWO PedAMP in this work also supports the clinical feasibility of the tools included in this outcome measurement guideline. The UWO PedAMP contains mainly subjective outcome measurement tools which have several advantages. These tools provide rich and important real-world information for children with hearing loss and complex needs and can support more objective clinical testing. Very little equipment is required for the caregiver to complete a questionnaire and they can be accomplished while caregivers are waiting for the clinician to execute hearing tests or hearing aid verification procedures. This situation holds the possibility of adding information to the pediatric hearing aid fitting process without fully adding time and space requirements to the situation. In addition, by routinely completing auditory-related questionnaires, caregivers may become good observers of their child’s auditory behaviors and a shared language will be developed with the clinician. For infants and children who can reliably perform behavioral testing, there are some objective tests available for the validation of hearing aid fittings. These can be used in combination with questionnaires for some children as part of a comprehensive approach to monitoring hearing aid outcomes. Our ongoing program of research with the UWO PedAMP includes continuing to develop a large database of children from within a typical pediatric audiologist’s caseload. Our goals include the development of typical performance ranges by hearing level for children who use hearing aids.

Detection of Speech Sounds

For some children, we also use objective clinical outcome measures that have been derived from laboratory tasks: The Ling 6(HL) task (Scollie, Glista, Tenhaaf, Dunn, Malandrino, Keene & Folkeard, 2012) and the UWO Plurals test (Glista & Scollie, 2012). These two tests focus on the detection of speech sounds through tasks that are administered to the child in a clinical setting. Neither test assesses suprathreshold speech sound recognition or discrimination. The calibrated stimuli for these tests are available on a compact disk which can be obtained through Phonak. Calibration and administration instructions are also supplied. Each test serves a unique purpose, but both are considered objective outcome measurement tools which assess the child’s capacity to perform with their hearing aids in a controlled clinic environment.

The Ling 6 sounds, including /m/, /u/, /a/, /i/,/∫/, and /s/, have historically been used by therapists to probe whether the child can detect, discriminate or identify the sounds based on a hierarchy of listening (Ling, 1989). This can be done informally using live voice or be played through an audiometer using calibrated stimuli. The Ling 6(HL) task was developed to probe phoneme detection using pre-recorded female utterances; normative values are available (Scollie, et al., 2012). It has been successfully administered to children who are able to participate in visual reinforcement audiometry (VRA) and conditioned play audiometry (CPA). To support clinical uptake, the authors developed a score sheet which depicts normative ranges for comparison. Performance ranges for different degrees of hearing loss are currently under investigation as are the impact of different listening conditions (i.e., insert earphones and different speaker azimuths). This outcome measurement tool allows clinicians to confirm the reception of sound while the infant is wearing hearing aids in addition to demonstrating the efficacy of the devices to the caregiver. The Ling 6(HL) test supports reliable estimation of sound field speech sound detection thresholds using phonemes that span a broad frequncy range and may be used as a measure of hearing device outcome. In addition, the Ling 6(HL) task can been used to demonstrate if the hearing aid bandwidth or processing (e.g., frequency lowering technology) provides access to the all six Ling sounds. Finally, the Ling 6(HL) task has the potential to provide information about device function for bone conduction hearing aids or cochlear implants where the fitting cannot be verified using real-ear measurements. Although this outcome measurement tool does not assess speech sound discrimination or identification, future modifications may be available for these purposes.

The UWO Plurals test is based on research evaluating aided high-frequency hearing ability (Glista, Scollie, Bagatto, Seewald, Parsa & Johnson, 2009; Stelmachowicz, Pittman, Hoover & Lewis, 2002). It consists of 15 English nouns presented in the singular and plural form. The clinical version of the test includes pre-recorded lists of 30 stimuli to test the child’s ability to correctly identify word-final plurality. Picture flip cards accompany the stimuli to engage the child in the task and help the clinician record the child’s response. Children as young as four years old have been successful in completing this task. A score sheet presenting critical difference scores offer clinicians a systemtic way of comparing two different listening conditions (i.e, aided listening with and without frequency lowering active). The UWO Plurals test may offer a way of assessing performance of hearing aid technology designed to enhance audibility of high-frequency sounds beyond what conventional amplification can offer. Similar to the Ling 6(HL) task, the UWO Plurals test is limited to measuring speech sound detection and does not provide information regarding speech recognition or discrimination.

Outcome measurement tools such as these require the child’s participation and provide a direct measure of the child’s hearing in the aided and unaided conditions. They may also be used to help demonstrate auditory abilities to the the family (for example, through the use of an aided speech-sound audiogram-like chart). Another advantage of the tools mentioned above includes the clinical feasibility of such measures. Most clinics are already equipped with the necessary devices to execute the task, including an audiometer and CD player. The developmental level of the child may limit the administration of objective outcome measurement tools. Therefore, it is important to combine them with subjective tools to give a comprehensive description of the child’s auditory outcomes.

Summary

This document has offered several options for evaluating the impact of hearing aid intervention in infants and children with hearing loss. Characteristics of good outcome measurement tools were also highlighted to summarize key issues to consider in selecting an outcome measure. Although this set of tests does not probe all aspects of auditory development or aided hearing, they are examples of measures that we have been able to incorporate in routine practice, and that can provide helpful information for monitoring. Monitoring auditory outcomes following a pediatric hearing aid fitting is an important stage in the intervention process. Validation should involve a multi-dimensional approach of evidence-based and clinically feasible subjective and objective outcome measurement tools appropriate for children of various ages and developmental levels. A demonstration of the child’s progress with hearing aids supports a systematic monitoring schedule for the child with hearing loss, engages parents as participants in the process and allows for outcome evaluation of the program as a whole. These key aspects of the pediatric hearing aid fitting process have been suggested as components of a comprehensive program of care for children with permanent childhood hearing loss (AAA, 2013; JCIH, 2013).

Acknowledgements

This work was supported with funding from the Canadian Institutes of Health Research [Marlene Bagatto: 200811CGV-204713-174463 and Sheila Moodie: 200710CGD-188113-171346], the Ontario Research Fund, Early Researcher Award [Susan Scollie], the Children’s Corporate Systems Branch of Ontario’s Ministry of Children and Youth Services in Canada, Siemens Hearing Instruments, Canada, The Masonic Foundation of Ontario, Help-2-Hear Project, the American Academy of Audiology New Investigator’s Award [Danielle Glista] and Phonak AG.

References

American Academy of Audiology. (2013). American Academy of Audiology Pediatric Amplification Guidelines. Retrieved from http://www.audiology.org/ resources/documentlibrary/Documents/PediatricAmplificationGuidelines.pdf

Bagatto, M.P., Brown, C.L., Moodie, S.T., & Scollie, S.D. (2011). External validation of the LittlEARS® Auditory Questionnaire with English-speaking families of Canadian children with normal hearing. International Journal of Pediatric Otorhinolaryngology, 75(6), 815-817.

Bagatto, M.P., Moodie, S.T., Malandrino, A.C., Richert, F.M., Clench, D.A., & Scollie, S.D. (2011). The University of Western Ontario Pediatric Audiological Monitoring Protocol (UWO PedAMP). Trends in Amplification, 15(1), 57-76.

Bagatto, M.P., Moodie, S.T., & Scollie, S.D. (2010). The University of Western Ontario Pediatric Audiological Monitoring Protocol (UWO PedAMP): Version 1.0 Training Manual. The University of Western Ontario, London, Canada. www.dslio.com

Bagatto, M., Scollie, S., Hyde, M., & Seewald, R. (2010). Protocol for the provision of amplification within the Ontario Infant Hearing Program. International Journal of Audiology, 49, S70-S79.

Bagatto, M.P., Scollie, S.D., Seewald, R.C, Moodie, K.S.,& Hoover, B.M. (2002). Real-ear-to-coupler difference predictions as a function of age for two coupling procedures. Journal of the American Academy of Audiology. 13(8), 407-415.

Ching, T.Y. & Hill, M. (2005). The Parents’ Evaluation of Aural/Oral Performance of Children (PEACH) Rating Scale. Chatswood, New South Wales, Australia: Australian Hearing. Retrieved September from http://outcomes.nal.gov.au/Resources/Clinical Tools.

Coninx, F., Weichbold, V., Tsiakpini, L., et al. (2009). Validation of the LittlEARS® Auditory Questionnaire in children with normal hearing. International Journal of Pediatric Otorhinolaryngology, 73, 1761-1768.

Glista, D. & Scollie, S. (2012). English language measure of detection of word-final plurality markers: The University of Western Ontario Plurals Test. American Journal of Audiology, 21, 76-81.

Glista, D., Scollie, S., Bagatto, M., Seewald, R., Parsa, V., & Johnson, A. (2009). Evaluation of nonlinear frequency compression: Clinical outcomes. International Journal of Audiology, 48(9), 632-65-44.

Joint Committee on Infant Hearing. (2013). Supplement to the JCIH 2007 Position Statement: Principles and guidelines for early intervention after confirmation that a child is deaf or hard of hearing. Pediatrics, 131(4), e1324-e1349.

King, A.M. (2010). The national protocol for paediatric amplification in Australia. International Journal of Audiology, 49, S64-S69.

Ling, D. (1989). Foundations of spoken language for hearing-impaired children. Washington, D.C.: Alexander Graham Bell Association for the Deaf.

Moodie, S.T., Bagatto, M.P., Miller, L.T., Kothari, A., Seewald, R.C., & Scollie, S.D. (2011). An integrated knowledge translation experience: Use of the Network of Pediatric Audiologists of Canada to facilitate the development of the University of Western Ontario Pediatric Audiological Monitoring Protocol (UWO PedAMP v1.0). Trends in Amplification,15(1), 34-56.

Scollie, S., Glista, D., Tenhaaf, J., Dunn, A., Malandrino, A., Keene, K., & Folkeard, P. (2012). Stimuli and normative data for detection of Ling-6 sounds in hearing level. American Journal of Audiology, 21(2), 232-241.

Stelmachowicz, P., Pittman, A., Hoover, B., & Lewis, D. (2002). Aided perception of /s/ and /z/ by hearing-impaired children. Ear & Hearing, 23(4), 316-324.

Tsiakpini, L., Weichbold, V., Kuehn-Inacker, H., Coninx, F., D’Haese, P., & Almadin, S. (2004). LittlEARS Auditory Questionnaire. MED-EL. Innsbruck, Austria.

Wang, L., Sun, X., Liang, W., Chen, J., & Zheng, W. (2013). Validation of the Mandarin version of the LittlEARS Auditory Questionnaire. International Journal of Pediatric Otorhinolaryngology, 77(8), 1350-1354.

C H A P T E R  S I X

Where Are We Now and

Where Do We Need To Be?

A Perspective From New Zealand

David Foster

Abstract

We know that collaboration is important. But how does it happen in the real world? Can it be measured? And what would be measured if families truly had the opportunity to lead changes in the way education happens? New Zealand has one of the most devolved education systems in the world (OECD 2012). The real story that New Zealand has to offer the world is the unique operation of its special education systems and in particular the governance and leadership of its schools for Deaf the interaction with parents, the close collaboration between parents and professionals, the measurement systems used with the children and the constitution of the Board of Trustees. Parents’ feedback has confirmed the importance of four themes when developing and delivering services to Deaf and hard of hearing infants and their families: timing, relationships, processes and opportunities. This presentation explores what has been learned in a system where parents are genuinely in the driver’s seat.

New Zealand has one of the most devolved education systems in the world (Nusche, 2012). From the beginning of October 1989, New Zealand schools have been governed by parents, elected every three years by postal ballot. Parents as trustees have become the embedded paradigm for school governance. The function and powers of the Board of Trustees are clearly stated in the Education Act (1989):

• A school’s board must perform its functions and exercise its powers in such a way as to ensure that every student at the school is able to attain his or her highest possible standard in educational achievement.

• Except to the extent that any enactment or the general law of New Zealand provides otherwise, a school’s board has complete discretion to control the management of the school as it thinks fit.

In a New Zealand school, the Principal is the chief executive. The Principal has complete discretion to manage the school’s administration on a day to day basis provided that this power is executed within the laws of the land and follows the policy direction of the controlling board. Simply put, the Principal and staff are employed by parents to work for their children. The Principal and staff are required to report to the Parents and the Ministry of Education about the achievement of students.

In October of 2012 the Minister of Education approved a revised constitution for the governance of New Zealand’s two Deaf Education Centres. Under this constitution the governance of the two Deaf education Centres was consolidated under of a single nationally elected board of trustees. The Board of Trustees mandate was also extended to responsibility for all students enrolled at or receiving services from the two Centres. The decision to combine the Board and extend its mandate was enacted following nearly ten years of discussion at national consultation forums and eighteen months of community consultation specific to the proposed governance change. There is an adage that says, what gets measured, gets done, and in the New Zealand system parents have this opportunity. Parents get to decide what gets measured and therefore they get to decide what gets done.

The Combined Board has determined that four priorities will drive the activity of its first three year term of office:

1. The development of a national database of deaf students, both enrolled at and receiving services from, the Deaf Education Centres.

2. Reporting an accurate picture of deaf students’ achievement in this emerging national context.

3. Strengthening connections for students and staff through applied technology; and

4. Maintaining a community that celebrates the unique cultural and linguistic identity of deaf children.

Each Deaf Education Centre continues to execute its responsibilities on a geographical basis by providing five core services:

• The operation of a specialist school for the deaf

(Grade K through Grade 12).

• Residential hostels to facilitate attendance at the school.

• Itinerant (visiting) teacher services on a regional basis.

• Bilingual preschools; and

• Development and delivery of a range of specialist resource and technical services (including audiology for enrolled students and repair and maintenance of hearing aids and FM Systems for all students in the Centres geographical region).

Joint venture agreements are in place to ensure collaboration in the delivery of services for cochlear implanted students. A series of nationally coordinated pilot projects is currently monitoring the implementation of collaborative services for deaf infants identified through newborn hearing screening. Parents (the governing trustees) have an absolute expectation of involvement in all strategic and policy discussions related to the development and delivery of services to deaf students. Parents are present at all major decision making discussions led by the Ministry of Education.

Philosophical Perspective

In Maori there is a concept known as whakatauki which is both a traditional proverb and call to action:

Tungia te ururua Kia tupu whakaritorito Te papa o te harakeke

Translated this whakatauki challenges a community to ensure that they clear away anything that stops growth; it reminds one that growth comes only from the centre – the most vulnerable part of the plant; and that eventually the plant will return to the earth. Our KDEC staff subscribe to whakatauki as it provides a context that relates to the growth of the deaf child. The education community’s commitment to whakatauki is captured in the KDEC logo. The koru (symbol of growth ) at the Centre represents the children. The “leaves” to right and left form the New Zealand Sign Language hand-shape for communication and represent the partnership between parents and professionals that provides a caring learning environment. The weaving at the base of the logo acknowledges the strength of combined action and also captures the notion of collaboration as history and traditions. The open space at the top of the logo highlights achievements as a focus while the overall design is, in abstract, a letter “K”

The KDEC learning community comprised of children enrolled at, or receiving services from teachers of the deaf, multi-disciplinary specialist professional teams as well as administrative and para-professional staff. Every week the staff works with over 530 children; the vast majority of whom rely on audiology for their access to language, and therefore, their access to learning.

How Are We Doing?

This paper seeks to examine perspectives of parents. In the context outlined above this is a cohort of parents who have firmly held expectations of involvement with, and to a certain extent influence over, those who are providing services. In short New Zealand parents expect to be fully involved in every aspect of their child’s growth and development. In the context of audiology for young deaf children how would these expectations be expressed and how would services respond to these expectations? What would collaboration really look like – how does it happen in the real world? What would be measured if families truly had the opportunity to decide? Would their views change the way you worked?

Professionals generally exhibit a strong sense of identity in the language they use to describe their practice. The concepts evident in audiology professionals’ self-description are fascinating. There is a reliance on tools, skills and strategies that can be brought to bear in a given situation. Through the years, much of the Phonak Sound Foundations Conference series has been focused on technological advances, technical skills and professional practices and guidelines. Expertise in these areas is vital to advances in the field and the access of deaf children. This paper respectfully proposes that a different choice of words might emerge in the language used to describe success in audiology if a different group of people was asked to contribute to the definitions of effective practice (http://hearingcareblog.com/2013/10/22/ doctors-of-audiology-emphasize-care-options).

Four Themes

An increasing data base of empirical research is capturing the “narrative” of families in these changing times (Young and Tattersall, 2007) and articulates, on behalf of families, the expectations and experience of service for deaf infants and children. From this literature, based on family’s views, four themes emerge as significant to the discourse that needs to permeate the relationships between parents of deaf children and the professionals from whom they receive services.

The first theme is TIME; the time in which it is possible to identify a child’s deafness. In New Zealand prior to 2010 the average age of detection was in excess of 36 months! (Digby, Kelly and Purdy, 2010). Theoretically it is possible to identify and confirm deafness as early as nine weeks of age. Parents express positively the impact of their child’s deafness being “picked up” early.

This shift highlights a second theme, the PROCESS; the process by which parents arrive at confirmation of their child’s deafness. Prior to universal newborn screening, it was likely that parent’s observations of their child by 24 to 36 months of age, would suggest to them that their child might be deaf. Now, newborn hearing screening can speed parents to that place in one tenth of the time. While this change speeds up the possibility of action, it can also lead very quickly to a sense of frustration if parents perceive inactivity from those responsible for providing services.

Combined with more timely access to identification, and more active follow-up, the habilitation processes create the potential to positively impact on the fundamental familial RELATIONSHIP. This third theme of relationship is concerned with parents who formed relationships with their child whom they subsequently found to be deaf. By confirming their child’s hearing loss almost immediately at birth, parents have the chance to form a better relationship which acknowledges their child’s deafness, as they are learning to know their baby.

And finally, the fourth theme is OPPORTUNITIES; the knowledge that their baby is or deaf, coupled with the technologies of the 21st century, is shifting the expectations of relationships between parents and professionals. This compels us to view new opportunities for involvement within a new framework.

Parent’s Perspectives

In order to confirm these four theoretical perspectives, a range of parents were invited to consider and respond to two questions. Participants were invited to respond either as part of a group discussion (with Auckland Parents of Deaf Children, Inc.) or individually via a written survey. The responses were synthesised according to the theme that they challenged or reinforced.

1. Describe a time when you just knew that your audiologist “got it” when engaging with you or your deaf child?

2. What are the most important things for professionals to remember when dealing with families of deaf children?

Parents’ responses to these questions provide insight into how the four themes play out in the daily life and experience of a range of New Zealand parents over the past 12 years. The actual words of the parents, reprinted below, provide an opportunity for us to assess not only where we are as professionals, but also where we might need to be directing our future efforts:

Time

• It is hugely important for an audiologist to act fast, particularly when dealing with a pre-lingual child.

• They need to be careful to see the child and not just the condition. It is easy to put parents’ backs up by focusing solely on the deafness.

• Over the years I felt uneasy when hearing was being tested, how good was the equipment, did the audiologist have the experience to understand the testing. It’s important we know what each test is for and how the results are worked out.

• The audiologist and I were the primary participants at the appointments. The audiologist, began to shift the interaction so that she and my daughter, at about aged eight, were now the primary participants in the appointment.

• My child would be going to an audiologist for the rest of her life, as a parent I needed to begin to shift my participation to its’ right place as a support person.

Process

• Without any experience of hearing loss before, I was quite shell shocked when dealing with a groggy infant coming around from sedation and then to be delivered this news by the audiologist while we were in the recovery ward. He had to rush off and so he didn’t give us much information.

• Parents are very much still in shock about their child’s hearing loss. Often parents do not understand what is being said to them, the words and what it all means, they can only retain so much and learn so much, they go into overload.

• Whatever solutions are presented for a child, they have to be manageable for the family within their social contexts. It is reasonably common for fathers to go into denial about their child’s deafness.

• A relationship of trust between the audiologist and parents is one of the most essential elements of success with families. Without trust, families will not share essential information e.g. how much are our kids actually using their technology?

• Whenever I have received an answer or advice I haven’t been comfortable with I always say to myself would things be different if I stand my ground and refuse to leave until we’ve talked this through.

• Audiologists are people you have to trust...Audiologists may unintentionally project a negativity of the situation on to vulnerable parents.

• Please consider what language you are using: time of identification (NOT diagnosis), involvement (NOT intervention). Is deafness really bad news?

• Never say “Or” when discussing the options the child and family can use. Say “AND” this “and” that are options.

Relationships

• I think that audiologists should make it a priority to have the fathers along for the journey as soon as possible.

• Be incredibly careful to see the child as part of their family.

• Really listen to the instincts and issues raised by the parents of the deaf child and to take those concerns seriously. It is important for audiologists to understand the implications of hearing loss from the point of view of how my family needs function.

• The first audiologist was the most truthful and made the most difference for us, he answered my questions with complete honesty.

• My audiologist gave me the names of two families and after a few weeks I rang them. These parents gave me further determination. I have been actively involved in parents networks ever since!!

Opportunities

• My Daughter has the right amplification and she is effectively amplified for every waking moment of every day. Sadly so often I hear and see families whose children do not wear their hearing aids and or have not opened all the boxes the audiologist have given them.

• Parent’s need to be experts on the equipment. Parents should know that they need to be actively helping their child’s listening skills and acquisition of language.

• Every day counts in terms of making up for the delay in language development that may have occurred. We must deal with this as a matter of urgency.

• The audiologist in a really respectful way that helped me to understand that the most important ‘player’ at these appointments was my child .

• I recall my first positive dialogue with an audiologist was when we accessed the KDEC audiology clinic and worked with Leslie Searchfield.

Paediatric Audiologist at KDEC

Leslie Searchfield is the paediatric audiologist at KDEC. Leslie has generously agreed that this presentation may quote her testimonial on the four themes being explored:

On TIME: “I believe I can remember every child with a severe to profound hearing loss that I have identified.Sitting with families through all the assessment is time of significant highs and lows. The most important thing when working with families is to take things a bit slow and where possible go at the pace they set”

On PROCESS: “Prior to newborn screening, the parent generally knew the child was deaf. Put the child at the centre of all contact. Each family is unique. Although there will be similarities among many they all have their own background and perspective about deafness and you need to recognise and value this. Watching the family work through one bad news situation after another and still managing to function is an experience I will never forget!!”

On RELATIONSHIPS: “These experiences are very emotionally charged. Diagnosis of a brand new baby appears more difficult and shocking for the family, and it seems to take a bit longer for the family to accept. You need to be empathetic. Try to encourage family involvement. More than once I have had parents comment that I am the first professional who walked into the room and knelt down and engaged their child.”

On OPPORTUNITIES: “Take time to talk and interact with the child. The most important thing we can do is increase the self-esteem of both the child with hearing loss and their closest caregivers.”

Leslie recalls a rewarding moment with a young boy who was doing very well with his CI. Leslie was talking with the boy’s mum, but the young boy kept interrupting his mum’s conversation. Finally, the mum turned to her son and said, “Please be quiet. I am talking with your teacher.” Then the mum suddenly got dead silent, began tearing and laughing, and said to Leslie, “I never imagined that I would be telling him to be quiet!”

Concluding Remarks

It is easy to get distracted by career acknowledgement, reputational development, status and research, each of which can be good for business and professional growth. Professionals, whether Principals of Deaf Education Centres or Paediatric Audiologists, need to remember daily that their work is about deaf children, their relationships with their parents and the children’s futures. And, that these futures are brighter now than at any previous time in history.

Professionals in audiology and deaf education who want to maintain focus on the desired trajectory of services for deaf children need to base their work on the views of parents. Parents’ views will confirm that services need to honour the child as a member of a family group and the child as a viable participant in a community. Audiological access enables the deaf and hard-of-hearing child to participate more fully in their community and creates opportunities for increased language development and social engagement. Parents’ views will constantly remind professionals to describe technical development and research breakthroughs in terms of the improvements that can be gained for deaf children to be become well-adjusted deaf adults.

Deaf children have the same rights to participation and engagement as their hearing peers, but deaf children do have distinctive needs. They need access to services that recognise their individual and special needs and services that will promote them becoming independent and self-determining members of society. Education of deaf children is successful when based on a partnership between the children, their families and those responsible for the provision of services.

To conclude this reflection in the languages of Aotearoa / New Zealand is the call of our deaf children. It has brought us all together:

Ko te kaupapa ke hoki te ora tanga o nga tamariki turi

No reira kia ora mai ano tatou

Acknowledgement

As the Principal of Kelston Deaf Education Centre (KDEC) in Auckland, New Zealand, I wish to express my heartfelt thanks to the Phonak Sound Foundation Conference organising committee for the opportunity to share one perspective on a New Zealand education system.

Ki te Komiti whakahaere he mihi nui, he mihi aroha ki a koutou mo te karanga mai i ahau.

Ko David Foster taku ingoa te Tumuaki o te kura matua o Kerehana mo nga tamariki turi.

Tena koutou, tena koutou, tena koutou katoa

References

Digby, J.E., Kelly, A.S., Purdy, S.C. (2011). Hearing loss in New Zealand children: 2010. New Zealand Audiological Society, Auckland, New Zealand.

Education Act of New Zealand (1989). New Zealand Legislation. (http://www.legislation.govt.nz/act/public/1989/0080/latest/DLM179565.html.

Kelston Deaf Education Centre Audiology. (http://www. kdec.school.nz/education/specialist_services).

Nusche D. et al. (2012). OECD Reviews of Evaluation and Assessment in Education. New Zealand, 2011. OECD Publishing.

Young, A. and Tattersall, H. (2007). Universal newborn hearing screening and early identification of deafness: Parents’ responses to knowing early and their expectations of child communication development. Oxford Journal of Deaf Studies and Deaf Education. (http://idsde.oxfordjournals.org/content/ early/2007/02/02/deafed.en1033.full.

S E C T I O N  I I

Meeting the Diverse Listening Needs of Children in Today’s World:

The Environment and Technology

Session Chair: Andrea Bohnert (GER)

C H A P T E R  S E V E N

The Complexities of Listening

and Understanding in Children

with Minimal/Mild Hearing Loss

Dawna Lewis, Ph.D. Jody Spalding, M.A. Daniel Valente, Ph.D

Abstract

Numerous studies have shown that school-age children with minimal/mild hearing loss (MMHL) may experience difficulties in a variety of areas including speech perception in noise and reverberation, speech/language development, educational performance and social/emotional development. However, challenges experienced by this population are not always straightforward. Consequently, children with minimal and mild hearing loss may be overlooked and/or difficulties that are related to their hearing loss may be minimized, potentially influencing expectations, behaviors, and progress in a number of developmental areas. This paper will examine the impact of minimal and mild hearing loss on performance in complex listening environments and implications for real-world listening and understanding.

In 1986, Bess and colleagues published a series of studies that examined case history and performance data for 6-18 year-old children with unilateral hearing loss (UHL) who were selected from patient and educational files in middle Tennessee (Bess, 1986). The results of those studies were influential in advancing our understanding of children with UHL. Perhaps the most surprising finding from the case history data (Bess & Tharpe, 1986) was that 35% of the children with UHL had failed at least one grade and 13% required resource help. This percentage of grade failures was much higher than the district average (3.5%). While the highest percentage of grade failures for a single grade occurred in the first grade, findings indicated that children with UHL were failing grades from kindergarten through seventh grade. Similar grade-retention rates were reported by Oyler, Oyler, & Matkin (1988), who examined records for children with UHL in a large school district. They reported that 24% of the children with UHL had repeated at least one grade and 41% had received special services, compared to 2% and 8.6%, respectively, for district averages.

A little over 10 years later, Bess, Dodd-Murphy and Parker (1998) examined educational performance and functional status in a group of children in grades 3, 6 and 9 with minimal sensorineural hearing loss, which included children with UHL, bilateral hearing loss (BHL) and high-frequency hearing loss (HFHL). For this population, grade retention rates for children also were significantly higher than district averages at 29.2%, 36.4% and 47.4% for grades 3, 6 and 9, respectively. While district averages also rose across grades, none were above 10%.

Since those early studies, numerous studies have shown that school-age children with minimal and mild hearing loss (MMHL) may experience difficulties in a variety of areas that encompass communication, academics, cognition and psychosocial factors (Bess et al., 1998; Bess & Tharpe, 1986; Bess, Tharpe, & Gibler, 1986; Borton, S., Mauze, E., & Lieu, J., 2010; Crandell, 1993; Culbertson & Gilbert, 1986; English & Church, 1999; Johnson, Stein, Broadway, & Markwalter, 1997; Klee & Davis-Dansky, 1986; Lieu, Tye-Murray, Karxon, & Piccirillo, 2010; Newton, 1983; Porter, H., Sladen, D., Ampay, S., Rothpletz, A., & Bess, F., 2013; Ruscetta, Arjmand, & Pratt, 2005; Oyler et al., 1988). Many of these difficulties could be expected to influence the grade-retention results reported above. For example, MMHL, and in particular UHL may affect children’s localization ability (Bess et al., 1986; Newton, 1983). Such abilities can play a role in a child’s ability to follow conversations with multiple talkers and those in which not all talkers are visible. In addition, children with MMHL have shown difficulty understanding speech in adverse acoustic environments (Bess et al., 1986; Boney & Bess, 1984; Crandell, 1993).

In classrooms, where acoustic conditions can vary widely (Bradley, 1986; Knecht, Nelson, Whitelaw & Feth, 2002; Nelson, Smaldino, Erler, & Garstecki, 2008), the ability to hear and understand new information during educational activities may be compromised, impacting academic performance.

Numerous studies also have shown that children with MMHL may experience difficulties in areas such as self-esteem, stress, energy, peer relations, and social confidence (Bess et al., 1998; Culbertson & Gilbert, 1986; Keller & Bundy, 1980; Oyler et al., 1986). Psychosocial development may impact behaviors, interactions with teachers and peers and performance. In a study comparing children with MMHL and children with normal hearing (NH), Bess et al. (1998) examined the self-perceived functional status of 6th and 9th grade participants. In the 6th grade, significantly more children with MMHL demonstrated dysfunction compared to their peers with NH in the dimensions of self-esteem and energy. In the 9th grade, significantly more children with MMHL exhibited dysfunction in the dimensions of social support, stress and self-esteem. Further examination of the results also showed changes in patterns of dysfunction for the children with MMHL across the two grades. Comparatively more 9th graders exhibited high levels of dysfunction in school work, social support, stress, family and overall health. The only dimension in which dysfunction appeared to decrease across grades for children with MMHL was energy. These patterns suggest that difficulties across a variety of psychosocial areas may be greater for older children with MMHL than for younger school-age children (e.g., high-school versus elementary-school ages). Given that few of the children with MMHL were identified with hearing loss prior to the study, Bess et al. stated that the functional issues were unlikely to have been related simply to knowledge of the hearing loss by the children or by others (e.g., peers, educational personnel).

Although there is a large body of research showing that children with MMHL may experience greater difficulties than peers with normal hearing in a number of areas, research also has indicated similar performance in some areas (Bess et al., 1998; Borton et al., 2010; Crandell, 1993; Culbertson & Gilbert, 1986; Klee & DavisDansky, 1986; Lewis, Valente, & Spalding, to 2014; Lieu et al., 2010; Porter et al., 2013). Unlike children with greater degrees of hearing loss, children with MMHL often demonstrate speech recognition similar to their peers with NH when tested in quiet or in low levels of noise/reverberation (Boney & Bess, 1984; Crandell, 1993; Lewis, et al., in review). Comparable speech understanding under some acoustic conditions may lead educators to assume that these children will perform better than they actually do in classrooms where noise levels can vary significantly during the day. Despite issues with academic success for many children with MMHL, they also have been shown to perform within normal limits on numerous standardized measures of language and achievement (Blair, Peterson, & Viehweg, 1985; Keller & Bundy; 1980; Kiese-Himmel, 2002; Kiese-Himmel and Ohlwein, 2003; Wake, et al., 2006).

As the above research indicates, despite over 25 years of research examining the effects of MMHL, there is no consensus on the difficulties experienced by these children and thus no consensus on appropriate habilitative strategies. Because findings are not always straightforward, these children may be overlooked and/ or the difficulties they experience may be minimized. It is important examine potential sources of differences across studies as a step in the development of measures that will lead to improved evaluation and management. For the remainder of this paper, we will discuss three areas that may impact outcomes of studies examining performance of children with MMHL: heterogeneity of hearing loss configurations within this population, perceptions regarding the impact of MMHL, and tests used to examine that impact.

Heterogeneity of Hearing

Loss Configurations

The definition of MMHL can vary somewhat across studies (Bess et al., 1998; Crandell, 1993; Kiese-Himmel and Ohlwein, 2003; Lewis et al., in review; Wake, et al., 2006). Broadly defined, the degree and configuration of hearing loss in this heterogeneous population includes (1) bilateral (BHL; 3-frequency PTA between 20 and 45 dB HL), (2) unilateral (UHL; 3-frequency PTA >20 dB HL in the poorer ear and ≤15 dB HL in the better ear and (3) high-frequency (HFHL; thresholds >25 dB HL at one or more frequencies above 2 kHz in one or both ears). It is not surprising that degree and configuration of hearing loss within this population could impact outcomes. The following examples are provided to illustrate audibility issues that may impact speech understanding for two listeners with different configurations of MMHL.

Figures 1 and 2 illustrate audibility of average conversational speech for a 6 year-old child with mild-moderate UHL in the left ear. The graphs are taken from the Situational Hearing Aid Response Profile (SHARP;Stelmachowicz, Lewis, Karasek, & Creutz, 1994; Brennan, McCreery, Lewis, Creutz, & Stelmachowicz, 2013). In each graph, the symbols represent thresholds for the right (O) or left ears (X) and the light shaded area represents the portion of the speech spectrum that is audible to the listener. Inaudible portions of the speech spectrum fall below threshold at a given frequency and are not shaded. Softer levels are toward the bottom on the y-axis. In Figure 1, the upper left panel shows audibility of average conversational speech presented in quiet at 1 meter for the right (normal hearing) ear. In this ear, the entire speech spectrum is audible to the listener. The upper right panel shows audibility for the left (hearing loss) ear for the same input. In this ear, only the low-mid frequencies are audible. Thus, if speech was presented from the left side, the child would be expected to miss a large portion of the speech signal in that left ear. However, the lower panel shows the portion of a signal presented to the left side that would be audible in the right ear (head shadow). For this child, much of the signal from the left would be audible in the right ear. The picture changes, however, when noise is added (Figure 2). In this figure, an additional shaded area has been added to each graph to provide a simplified illustration of how noise (approximately 10 dB SNR) could affect audibility of the speech signal for this child. As can be seen in the upper left graph, only the average and peaks of the speech spectrum are audible in the right ear. In addition, the lower graph shows that the signal from the left side that is being heard at the right ear is now degraded, with only limited peak information available. Together, these figures suggest that audibility of conversational speech at 1 meter may not be an issue for this child with UHL in quiet, although speech understanding may be significantly compromised in noise.

Figure 1. Audibility of speech for a child with UHL in the left ear. In each panel, the dark line represents the average speech spectrum and the lighter lines represent the minimum and peaks of that spectrum. The lightly shaded portion of the spectrum represents speech that is audible and the unshaded portion is inaudible. The upper panels show average conversational speech at one meter for the right ear (O; left panel) and left ear (X; right panel). The lower panel shows audibility of speech at the right ear based on head shadow from the left side.

Figure 2. Same as Figure 1 with the addition of a darker shaded portion to represent the addition of noise at approximately 10 dB signal-to-noise ratio.

Figures 4 and 5 illustrate audibility of average conversational speech at 1 and 4 meters (upper and lower left panels) and of a classroom teacher at the same distances (upper and lower right panels) for a 6 year-old child with bilateral hearing loss. Figure 3 shows results for the right ear in quiet (left ear values would be the same in this illustration of BHL). Notice that for this child, audibility of average conversational speech at 1 meter is compromised in the high frequencies with only peaks audible above 3000 Hz. At that same distance,

the teacher’s voice remains audible across most of the frequency range, with the exception of the loss of some of the softer components at 4000 Hz and above. At 4 meters the audibility of average conversational speech is much poorer across the entire frequency range. The audibility of the teacher’s voice at this distance is greater and resembles that of average conversational speech at 1 meter. When noise is added (Figure 4), audibility of all speech signals is reduced. However, the teacher’s voice at 1 meter remains audible across a majority of the frequency range. Together, these figures illustrate how distance, vocal effort and noise can differentially impact audibility of speech for a child with bilateral MMHL.

Figure 3. Audibility of speech in the right ear for a child with bilateral MMHL. In each panel, the dark line represents the average speech spectrum and the lighter lines represent the minimum and peaks of that spectrum. The lightly shaded portion of the spectrum represents speech that is audible and the unshaded portion is inaudible. The upper panels show average conversational speech at one meter (left) and a classroom teacher’s voice at 1 meter (right). The lower panels show the same speech spectrums at 4 meters.

Perceptions Regarding the Impact of MMHL

Perceptions of the difficulties experienced by children with MMHL may influence expectations, behaviors, and progress in a number of developmental areas. At the same time, those perceptions may or may not accurately reflect the difficulties experienced by the child. It is possible that self-assessment by the person with MMHL will be affected by the fact that he/she does not realize what is being missed (e.g., Newton, 1983), suggesting that children may not always be the most accurate source to determine the effects of hearing loss on their auditory skills. Parents and teachers may also over/under estimate the difficulties experienced by these children (e.g., Dancer, Burl, & Waters, 1995; Oyler et al., 1988). Dancer et al. examined teacher perceptions of the effects of UHL for school-age children (5-17 yrs). The same measures were completed for one “average” student with NH from the same class as each subject with UHL. Although children with UHL scored significantly lower than their peers on most questions, there was no difference between groups in terms of teacher ratings of whether students were working to expectations. Such findings suggest that teachers may have had lower expectations for the children with UHL.

Figure 4. Same as Figure 3 with the addition of a darker shaded portion to represent the addition of noise at approximately 10 dB signal-tonoise ratio.

Lower expectations could affect both the teacher’s willingness to challenge the student academically and the student’s willingness to challenge him/herself.

Examining the child’s perception of the impact of MMHL as well as those of their parents/caregivers and teachers may provide a more complete picture of potential difficulties. In the Listening and Learning Laboratory at Boys Town National Research Hospital we addressed this issue by conducting structured interviews of 20 children with MMHL, one parent/guardian of each child and, when possible, one classroom teacher for each child (responses were obtained from 9 teachers). Analysis is ongoing and only preliminary data will be discussed here (Spalding & Lewis, 2012). Data is being analyzed using both qualitative and quantitative methods.

From transcribed responses of interviewees, three broad categories of potential challenges emerged for children with MMHL. Those categories included awareness/understanding, groups/noise, and limited visual access. We first examined whether groups of interviewees were more likely to state that the child did or did not experience challenges in each of the categories. Table 1 shows the percentage of coded responses in each category for which children, parents and teachers perceived that the child was experiencing or not experiencing challenges. Note that teachers represent lower percentages than either parents or children because fewer teachers agreed to participate. The overall patterns indicate that parents and children were more likely to state that the children experienced challenges in each of the coded categories.

Table 1. Percent of utterances coded as either challenge or no challenge within three response categories by the child, a parent or a teacher.

Teachers also were more likely to report challenges in awareness/understanding but their responses were more evenly distributed across challenge and no challenge in the other two categories. Examples statements from a parent, a child and a teacher regarding challenges are shown in the final row of the table. Overall, these finding suggest that the interviewees in this study perceived that the children with MMHL were experiencing challenges across a variety of areas.

Table 2. Sources other than hearing loss reported by parents and teachers to explain challenges experienced by children with mild and minimal hearing loss (MMHL).

However, within those areas there also were instances that were identified as not being challenging for the child. Further examination will help us identify how these overall perceptions relate to the individual children in the study.

An unexpected finding from the interviews was the number of times parents and teachers reported that the child with MMHL was experiencing challenges but that they did not believe those challenges were related to the hearing loss. The interview questions were structured to address areas where children with MMHL could be at risk for difficulties. While it is possible that for any given child there are alternate underlying sources for reported challenges, observed responses may also indicate that parents and teachers do not fully understand the implications of MMHL on the children’s performance in the challenge areas. Table 2 shows the alternative sources of difficulties and the number of times those comments occurred for parents and teachers. As an alternative to hearing loss, parents were most likely to attribute difficulties to attention followed by personality while teachers were most likely to attribute difficulties to behavior, again followed by personality.

While these findings are preliminary, they do suggest that perceptions are important. They are important as an indicator of understanding of potential implications of MMHL by families and educational personnel. Knowing how families and educators perceive MMHL and its potential impact on the child can be a useful tool for counseling and can assist in the development of habilitation strategies for that child.

Tests Used to Examine the Impact of

MMHL

As the research discussed thus far suggests, outcomes may differ depending on the measures that are used to assess the abilities of children with MMHL. These differences may reflect how MMHL differentially affects skill areas (e.g., speech perception, language, memory). For example, the Bess et al. (1998) study of children with MMHL in grades 3, 6, and 9 compared children with MMHL and children with NH using measures that assessed educational performance and functional status. Results revealed significantly poorer scores for children with MMHL on some measures but not others. In addition, differences on at least one measure were significant in the 3rd grade but not in the 6th and 9th grades.

It also is possible that differences or the lack of differences between children with MMHL and those with NH in some studies relate to the measurement tools that are being used. For example, some standardized measures may not be sensitive to the difficulties experienced by this population; difficulties that may be more subtle than would be seen in children with greater degrees of hearing loss. In addition, when attempting to understand the effect of acoustics on performance, the test environment can play an important role in results. Differences in speech understanding in noise and reverberation may occur as a function of testing being conducted in a sound booth with good reproducibility but only general representation of the real world versus testing being conducted in an actual classroom with students present, which is ecologically valid, but by its nature changes frequently, limiting reproducibility.

To examine the effects of both task and environment on speech perception of children with MMHL and children with NH we created a simulated classroom whereby we could control acoustics and task. That environment is described in detail in Valente, Plevinsky, Franco, Heinrichs & Lewis (2012), which also presents results for two experiments with children and adults with NH. This paper will briefly present results from a study of 18 children with MMHL and 18 children with normal hearing from 8-12 years of age (Lewis et al., to 2014). Children completed two tasks: classroom learning, sentence recognition. For the classroom learning task, video recordings were made of a teacher and four students reading lines from a 10 minute age-appropriate play. Those recordings were presented via loudspeakers and video monitors located around the child. The child was asked to listen to the play and answer a series of factual questions at the end to assess comprehension. He/she was allowed to look around as much or as little as needed during the course of the task. Looking behavior was monitored via a head-worn gyroscope. For the sentence recognition task, sentences with three key words spoken by a single talker were presented auditory-only from the five loudspeakers and the child was asked to repeat each sentence. For both tasks, speech was presented at 60dBA at the listener’s location. Neutral spectrum background noise was presented at 50dBA (10 SNR) and reverberation time was set to 600 msec.

Comprehension and sentence recognition scores are shown in Figure 5. For the sentence recognition task, scores were ≥89% for all children with the exception of two with MMHL. Thus, in acoustic conditions representative of a typical classroom, both children with MMHL and children with NH performed at or near ceiling on such a task. Although there was considerable variability in the scores for the comprehension task, statistical analysis (p<.05) revealed that children with MMHL performed more poorly than children with NH on this task. Speech recognition tasks using phonemes, words, and sentences have frequently been used to predict how children will perform under conditions of noise and reverberation. These results suggest that performance on basic speech recognition tasks may not predict performance for more complex listening tasks in the same acoustic environment.

Figure 5. Mean and standard deviation of comprehension and speech recognition scores for children with NH (unshaded) and children with MMHL (shaded).

Looking behavior during the classroom learning task was analyzed in two ways. First, we examined how often listeners looked directly at the talker as he/she was speaking (proportion of events visualized; POEV). Second, we examined overall looking behavior, defined as the standard deviation (SD) of head movement from the 0º position (looking straight ahead). For this measurement, greater standard deviations represent greater attempts to look at the five talkers.

POEV results are shown in Figure 6. There were no significant differences across groups, and both groups looked at talkers, on average, less than 50% of the time. While there can be multiple reasons for this finding (e.g., choosing not to look, timing of looking relative to talkers’ speaking times), these results suggest that the type of multi-talker interaction may impact whether children are looking at talkers as they speak.

Figure 6. Proportion of events visualized (POEV) for children with NH (unshaded) and children with MMHL (shaded).

Results of overall looking behavior for individual participants are shown in Figure 7. While there were no statistically significant differences across groups, there were some interesting trends in the patterns of individual results. At younger ages (8-10 years), the majority of the children in both groups showed similar patterns of looking, with patterns that were higher than those of most of the older children (10-12 years) with normal hearing. At the older ages the two groups differed, with more of the children with MMHL showing patterns that were similar to those of the younger children in both groups.

The findings from this study suggest that, despite performing at or near ceiling on a sentence recognition task, children with MMHL perform more poorly than children with normal hearing on more complex listening tasks. Across children, individual listening behaviors vary. It is possible that these differing behaviors may impact comprehension in that attempts to visualize rapidly changing talkers may inefficiently utilize cognitive resources that would otherwise be allocated for comprehension.

Figure 7. Individual overall looking behaviors measured in standard deviation (SD) for children with NH (circles) and children with MMHL (squares).

Summary

In summary, multiple factors can influence both the difficulties children with minimal and mild hearing loss will experience and how clinicians, parents and educators perceive those difficulties. Continued research is needed to more fully understand the underlying factors that influence performance for children with minimal and mild hearing loss in the real world. Such information can lead to service provision that optimizes communication access and educational achievement.

Acknowledgement

Research from the Listening and Learning Lab at BTNRH presented in this paper has been supported by NIH grants R03 DC009675, T32 DC000013, and P30 DC004662.

References

Bess, F. (Ed.). (1986). Unilateral Sensorineural Hearing Loss in Children. Ear & Hearing, 7(1).

Bess, F., Dodd-Murphy, J. & Parker, R. (1998). Children with minimal sensorineural hearing loss: prevalence, educational performance and functional status. Ear & Hearing, 19, 339-354.

Bess, F., & Tharpe, A.M. (1986). Case history data on unilaterally hearing-impaired children. Ear & Hearing, 7, 14-19.

Bess, F., Tharpe, A.M., & Gibler, A.M. (1986). Auditory performance of children with unilateral sensorineural hearing loss. Ear & Hearing, 7, 20-26.

Boney, S. & Bess., F. (1984). Noise and reverberation effects in minimal bilateral sensorineural hearing loss. Presented at the meeting of the American Speech-Language and Hearing Association, San Francisco, CA.

Blair, J., Peterson, M., & Viehweg, S. (1985). The effects of mild sensorineural hearing loss on academic performance of young school-age children. The Volta Review, February/March, 87-93.

Bradley, J. (1986). Predictors of speech intelligibility in rooms. Journal of the Acoustical Society of America, 80, 837-845.

Borton, S., Mauze, E., & Lieu, J. (2010). Quality of life in children with unilateral hearing loss: a pilot study. American Journal of Audiology, 19, 61-72.

Brennan, M., McCreery, R., Lewis, D., Creutz, T. J., and Stelmachowicz, P. G. (2013). The situational hearing aid response profile: An update. Poster presented at the American Auditory Society Meeting, Scottsdale, AZ.

Crandell, C. (1993). Speech recognition in noise by children with minimal degrees of sensorineural hearing loss. Ear & Hearing, 14, 210-216.

Culbertson, J.L. & Gilbert, L.E. (1986). Children with unilateral sensorineural hearing loss: cognitive, academic, and social development. Ear & Hearing, 7, 38-42.

Dancer, J., Burl, N., & Waters, S. (1995). Effects of unilateral hearing loss on teacher responses to the SIFTER. American Annals of the Deaf, 140, 291-294.

English, K., & Church, G. (1999). Unilateral hearing loss in children: An update for the 1990s. Language, Speech and Hearing Services in Schools, 30, 26-31.

Johnson, C.E., Stein, R., Broadway, A. & Markwalter, T. (1997). “Minimal” high-frequency hearing loss and school-age children: Speech recognition in a classroom Language, Speech and Hearing Services in Schools, 28, 77-85.

Keller, W. & Bundy, R. (1980). Effects of unilateral hearing loss upon educational achievement. Child: Care, Health and Development, 6, 93-100.

Kiese-Himmel, C. (2002). Unilateral sensorineural hearing impairment in childhood: analysis of 31 consecutive cases. International Journal of Audiology, 41, 57-63.

Kiese-Himmel., C. & Ohlwein, S. (2003). Characteristics of children with permanent mild hearing impairment. Folia Phoniatrica et Logopaedica, 55, 70-79.

Klee, T.M. & Davis-Dansky, E. (1986). A comparison of unilaterally hearing-impaired children and normal-hearing children on a battery of standardized language tests. Ear & Hearing, 7, 27-37.

Knecht, H., Nelson, P., Whitelaw, G. & Feth, L. (2002). Backround noise levels and reverberation times in unoccupied classrooms: Predictions and measurements. American Journal of Audiology, 11, 65-71.

Lewis, D., Valente, D.L., & Spalding, J. (to 2014). Effect of minimal/mild hearing loss on children’s speech understanding in a simulated classroom. Ear & Hearing. Accepted for publication.

Lieu, J., Tye-Murray, N., Karxon, R. & Piccirillo, J. (2010). Unilateral hearing loss is associated with worse speech-language scores in children. Pediatrics, 125, 2009-2448.

Nelson, E.L., Smaldino, J., Erler, S. & Garstecki, D. (2008). Background noise levels and reverberation times in old and new elementary school classrooms. Journal of Educational Audiology, 14, 12-18.

Newton, V.E. (1983). Sound localization in children with a severe unilateral hearing loss. Audiology, 22,189-198.

Oyler, R., Oyler, A., & Matkin, N. (1988). Unilateral hearing loss: Demographics and educational impact. Language, Speech and Hearing Services in Schools, 19, 201-210.

Porter, H., Sladen, S., Ampah, S., Rothpletz, A., & Bess, F. (2013). Developmental outcomes in early schoolage children with minimal hearing loss. American Journal of Audiology, 22, 263-270.

Ruscetta, M.N., Arjmand, E.M. & Pratt, R. Sr. (2005). Speech recognition abilities in noise for children with severe-to-profound unilateral hearing impairment. International Journal of Pediatric Otorhinolaryngology, 69, 771-779.

Spalding, J. & Lewis, D. (2012). Effects of Minimal/ Mild Hearing Loss: Children’s, Parents’, Teachers’ Perceptions. Poster presented at the American Auditory Society Meeting, Scottsdale, AZ.

Stelmachowicz, P., Lewis, D., Karasek, A. and Creutz, T. (1994). Situational hearing aid response profile (SHARP, version 2.0) user’s manual. Omaha, NE: Boys Town National Research Hospital.

Valente, D.L., Plevinsky, H., Franco, J., Heinrichs, E., & Lewis, D. (2012), Experimental investigation of the effects of the acoustical conditions in a simulated classroom on speech recognition and learning in children. Journal of the Acoustical Society of America, 131(1), 232-246.

Wake, M., Tobin, S., Cone-Wesson, B., Dahl, H-H., Gillam, L., McCormick, L. et al. (2006). Slight/mild sensorineural hearing loss in children. Pediatrics, 118, 1842-1851.

C H A P T E R  E I G H T

The Use of FM Technology for Pre-School Children

with Hearing Loss

Imran Mulla, Ph.D. Wendy McCracken, Ph.D

Abstract

The aim of this research was to evaluate and explore the benefits of FM technology with preschool hearing aided children. The research was of a longitudinal prospective design, including seven families of pre-school children. Daily diaries, data logging and questionnaires were used to collect quantitative data. Five of the seven families were able to establish regular FM use in a range of environments and settings with the most frequent being at home, in the car, at nursery, during shopping and when outdoors. Situational analysis of FM use was collected and improvements in listening in noise, auditory only and distance were identified over time. Six main themes were identified: access to speech, listening, communication, wellbeing, engagement/ ownership and practicalities of FM use. Overall the analysis highlighted the potential benefits, barriers and challenges to pre-school use of FM technology. The language environment analysis (LENA) system was used to compare differences in language environment with and without FM use. The acoustic environment results suggested that largest portion of children’s day was spent in environments where speech was at a significant distance or within background noise, thereby identifying areas that would benefit from the use of FM technology. The LENA Language Developmental Snapshot (LDS) results indicated that those children who started the study ‘at risk’ and had used FM technology, were within normal levels or close to normal limits, by the conclusion of the study.

In establishing the importance of early identification of hearing loss in children, very little attention has been given to how advanced FM technology may improve outcomes. Distance, noise and reverberation remain considerable challenges for individuals using hearing aids, more so in really young children. Given that infants tend to have a systematic progression in language acquisition they are more susceptible to environmental acoustic challenges. In general, young children with normal levels of hearing experience greater difficulty than adults in discriminating speech in noise (Bradley and Sato, 2008; Eisenberg et al., 2000; Neuman et al., 2010; Nishi et al., 2010; Valente et al., 2012; Yang and Bradley, 2009) and speech in reverberation (Neuman et al., 2010; Valente et al., 2012; Yang and Bradley, 2009).

The effects of reverberation and signal-to-noise ratio (SNR) on adult hearing aid users compared to normal hearing individuals have been well-substantiated (Finitzo-Hieber and Tillman, 1978; Hawkins and Yacullo 1984). A significant difference between the two groups was documented, with a disproportionately greater effect on the hearing aid users as acoustic conditions deteriorated. Acoustical conditions that are mild or moderately disruptive to normal listeners can result in severely reduced auditory perception in hearing impaired individuals. These challenges would expectedly be greater for younger children with hearing loss. Even mild to moderate sensorineural hearing losses alter a young child’s speech perception in quiet and noise and can impact linguistic development (Moeller et al., 1996)

The negative acoustic effects of distance, noise and reverberation can be overcome for children with hearing loss by the use of FM systems. FM systems transmit speech sounds directly from the speaker to the listener at a greater intensity then the surrounding noise. This enables an audible speech signal to be conveyed to the hearing aid user. FM systems have been widely used in academic settings to overcome problems associated with speaker to listener distance, reverberation and poor signal to noise ratio (Bess et al., 1996; Brackett et al. 1992). However, very little consideration has been given in the research to the use of FM technology in non academic settings especially with children who have not yet reached school age. A few studies (Moeller et al., 1996; Brackett, 1992; Gabbard et al., 2003; Statham and Cooper, 2009) have reported benefits on the use of FM technology with pre-school children, however little or no data on the actual use of FM were presented. Furthermore, the equipment used, especially in the study by Brackett (1992) and Moeller et al. (1996) was cumbersome and bulky making it unsuitable for younger children. Similarly, Statham and Cooper (2009) found even ear level receivers attached to hearing aids via audio shoes raised concerns for parents.

The lack of evidence available on the use of FM technology with pre-school hearing aided children is evident. With newborn hearing screening resulting in much earlier identification of hearing loss and the continuous advancements in FM amplification technology there is a critical need to evaluate this technology for pre-school children. The present research (Mulla, 2011) was aimed to address the gap in knowledge on FM use with preschool hearing aided children with three studies:

1. Quantitative evaluation of FM use with pre-school children;

2. Qualitative evaluation of FM use with pre-school children;

3. Language ENvironment Analysis (LENA) with and without FM.

Study 1: Quantitative Evaluation of FM

use with Pre-School Children

The primary aim of this study was to establish quantitative results on the daily usage of FM technology with pre-school hearing aided children including the average duration of FM use, the total hours of FM use, the number of days FM was used as well as the environments and situations where the FM was utilized. Data logging was used to verify daily diaries and overall there was good consistency between the two reports. On occasions where there were discrepancies the more conservative measure was accepted.

The key findings from this study are described below:

• Five of the seven participants were able to establish regular use of FM technology in a variety of settings. For the two participants who did not establish regular use of the FM technology, age of the child (11 months at the outset) was identified as possible reasons that may have affected FM technology use. This was further explored through the qualitative analysis (next section).

• Overall the participants were involved in the study for a total of 1198 days from which 837 days (71%) of FM technology use was recorded. The total number of hours of recorded FM use was 2874 hours and 15 minutes. From the total hours of recorded FM use, parents reported 2801 hours of FM use were with benefit, 2 hours and 30 minutes of FM use without benefit and 73 hours and 45 minutes of FM use were where they were not sure of benefit. The average duration of FM use on days the device was utilised was 3 hours and 2 minutes.

• The home, nursery, car, shopping and outdoors categories were the most consistent settings for FM use. Although the largest percentage of hours used was recorded for the nursery setting, the highest number of days during which the FM was used in any setting was the home situation followed by the car environment and then the nursery setting.

• The FM Listening Evaluation for Children (FMLEC) questionnaire was conducted after one month of use and at the end of the study. The questionnaire evaluated children’s listening with FM in four situations: noise, quiet, distance and auditory only. The overall total scores for listening in all four environments improved over time for six of the seven participants. As expected the highest improvements from the four listening situations were reported for background noise and significant distance situations.

• The children’s language development over the duration of the study was assessed using the LENA Developmental Snapshot (LDS) questionnaire (Gilkerson and Richards, 2008). Results from the beginning, midway and end of the study were compared to identify any trends in language development associated with FM device use. Four children whose LDS scores were ‘within normal level’ or border line

‘within normal level’ at the beginning of the study did not show any significant improvements overtime. Of these four participants two had made regular use of FM technology and two had not. Three children whose LDS results were significantly ‘at risk’ at the start of the study made significant improvements in LDS scores by the end of the study. Two of the participants were ‘within normal limits’ and one close to ‘within normal limits’ at the end of the study. All three of the participants had made regular use of their FM technology. The results suggest pre-school hearing aided children who are significantly ‘at risk’ in their receptive and expressive language scores (as assessed by the LDS), may achieve better language development with the use of FM technology.

Study 2: Qualitative Evaluation of FM Use with Pre-School Children

The primary aim of this study was to qualitatively explore the views and experiences of parents and carers on the use of FM technology with pre-school hearing aided children. Although the quantitative methods described above do provide an insight into the use of FM technology with pre-school hearing aided children they cannot provide an insight into the meanings, views and perspectives of the users of the technology. The qualitative approach identifies what is meaningful based on what emerges as meaningful from experience and not by what may be decided as meaningful by researchers (Willig, 2001; Silverman, 2005). Caregivers completed an open ended diary on a weekly basis; semi-structured interviews were conducted at the end of the study to further explore views and experiences. Each individual was regarded as a ‘case’ rather than each of the seven interviews and eight diaries. Overall there were eight ‘cases’, seven of which included data from both diaries and interviews for each participant and the final eighth ‘case’ referred to the diary kept by the nursery. The key findings for this study were:

• The improved access to speech FM technology provided was highly valued, especially in situations where the child was not facing parents, i.e., in the car or pram, in noisy situations, at a distance and when hearing aid microphones were covered.

• Improved listening behaviours in the child were noted when using the FM including improved attending, locating of FM user, comprehension, improved concentration and reduced listening effort.

• The use of FM technology allowed access to intelligible speech over distances, in noise and more challenging listening situations. This provided more opportunities for overhearing which is important for children to acquire language and learn novel concepts (Akhtar et al., 2001; Akhtar, 2005; Floor and Akhtar, 2006).

• A theme of child-control FM use as well as parent’s abilities to identify when their child did not want to wear the FM device emerged. A clear sense of ownership and ability to establish preferred use of FM emerged even in children as young as 16 months of age.

• Improvements in language as a result of FM use were reported with more copying, more accurate intonation and increased clarity of speech being described.

• Improved well-being was a strong theme reflective of the use of FM technology resulting in positive emotions for the children. Children were also reported to have been calmer and more comforted with FM technology in use. Increased engagement and participation in activities at the child’s nursery and outdoors was noted with children described to have an increased sense of social belonging. Parents reported children being more confident when parents used the FM device and of their children using the technology as a “safety blanket” when engaging in new activities.

• Parents of two of the children who had not established consistent use of their hearing aids found it difficult to introduce FM technology into their regular routines. These parents highlighted age of the child, ear infections, earmold issues and the child not keeping hearing aids in place as reasons for not establishing consistent hearing aid use. However, in contrast, two other participants reported that the introduction of FM technology helped overcome the difficulties associated with the child not keeping hearing aids in place. This resulted in an increase in hearing aid use by these children to the extent that the children started requesting their hearing aids. This finding suggests the use of FM technology may increase the use of hearing aids by children with hearing loss.

• The addition of FM technology was reported to have been “easy to use” and parents were able to establish daily FM management routines with ease. The FM transmitter was likened to a simplified “mobile phone” and the advanced features were easily accessed and used by parents.

• Remembering to mute the FM device was identified by parents as a challenge when using FM technology. Parents were able to identify situations where they forgot to mute the FM system and they acknowledged the need to be more careful when using the FM technology. On many occasions the child overhearing adult discussions made parents aware that the FM device was, in fact, turned on and working.

Study 3: Language ENvironment Analysis

(LENA)

The LENA device is a small recorder that is attached to a garment worn by the child over a minimum of 12 hours in their natural environment. The results of the recording are transferred to a computer with LENA software to analyse the child’s language environment. The analysis includes detailed report counts on the number of adult words (AWC) spoken in the vicinity of the child; the number of conversational turns (CT) taken by the child with another child or adult; and the number of the child’s personal vocalisations (CV) during the 12 hour recording. Furthermore, the software provides detailed analysis on the acoustic environments the child was in during the entire recording period. The software defines five acoustic categories: ‘meaningful’, ‘distant’, ‘silence and background’, ‘TV’ and ‘noise’. The primary aim of this study was to compare the language environment of pre-school hearing aided children in the home setting and in the outdoors setting, with and without FM technology use. The key findings from this study are highlighted below:

• When comparing the AWC’s, CT’s and CV’s, with and without the use of FM technology, the unfortunate caveat was that the LENA system was not sensitive enough to fully detect potential FM benefits at a significant distance. All report counts (AWC, CV and CT) were generated using only the ‘meaningful’ category which referred to speech occurring within six feet of the child without any ‘overlapping’ noise or competing speech present. Speech that may have occurred at a distance of over six feet or with ‘overlapping’ noise was categorised in the ‘distant’ category and any potential FM benefit was not analysed by the LENA system.

• Approximately 20% of speech in children’s language environment on a typical day was interpreted to be in the ‘meaningful’ category; whereas over 40% of speech was identified to be in the ‘distant’ category. These findings highlight the importance and increased need for FM use with pre-school hearing aided children. These findings also suggests participants in this study could have benefited from further use of the FM technology on a daily basis.

• Even with the limitations, the comparison of report counts for the different settings resulted in a significant difference in CT counts for the outdoor setting. This finding suggests that although no differences were detected in the ‘meaningful’ category for other report counts and in other situations, the benefits of FM use for this particular setting and report count were picked up within the ‘meaningful’ category. This may be a result of increased conversations in the car and pram settings where the child is within six feet of the parent. Although ‘overlapping’ noise may be expected in these settings, the noise may have been at a minimum.

• Children with hearing loss in this study had language exposure that was near the 50th percentile or better when compared to their hearing peers. This finding was contrary to the suggestions of previous literature where it was expected that children with hearing loss may have less exposure to language. However it needs to be noted that because distant speech was not included in the LENA counts, this may have a bearing on comparing results from the previous literature.

• The language exposure percentiles are the only report count where all four participants’ percentiles were below the median 50th percentile for CTs in the outdoors recording condition without FM use. In comparison, with FM use, three participants’ CT counts ranged from the 59th to 68th percentile. Although one participant’s CTs were below median at the 36th percentile, this child showed an increase in CTs in the ‘with FM’ condition compared to the ‘without FM’ condition (22nd percentile). This further highlights the potential benefits of FM use in the outdoors setting to facilitate conversations with hearing aided children. As a result of FM use, their CT environment in outdoor conditions could increase to the percentile levels of their hearing peers.

Discussion

There has been little exploration of FM technology use with early identified children with hearing-impairment. Three previous studies that explored FM use with pre-school children did not report data on daily usage of FM technology (Moeller et al., 1996; Brackett, 1992; Gabbard et al., 2003; Statham and Cooper, 2009). Moeller et al., (1996) required parents to complete daily use logs, which documented device function and hours of amplification use (FM use, HA use and no amplification periods). This study was unique in that it examined daily usage of FM technology, capturing not only data related to the duration and frequency of FM use, but also the varied and complex listening situations of young children. The detail with which usage data has been captured, including the number of days FM is used, how long FM is used, where FM is used and whether parents felt FM was useful in that situation has previously not been reported.

While the value of early access to well-fitted and evidence-based amplification parameters has been established, both in relation to hearing aids (Yoshinago-Itano et al., 1998; Moeller, 2000) and cochlear implants (Sharma et al., 2002), there is little understanding of ‘early’ in the use of FM technology. Logically, it can be argued that once a child reaches the developmental phase of crawling, close microphone distance is potentially lost. Given the importance of access to speech in the first years of life (Moeller et al. 2009; Cole and Flexer, 2011), any distance between the speaker and the microphone will degrade the quality of the signal. Integrated FM technology, which overcomes the ergonomic restraints of traditional FM systems, both in respect of body-worn and shoe-based FM technology, potentially offers significant benefits. It is unclear at what developmental point it is most appropriate to introduce FM technology from the perspective of children and their families. Findings from the present studies identify the fact that families of children as young as 15 months are able to include FM technology in their child’s daily routines. Future studies might benefit from including a more representative sample of the pediatric hearing impaired population to help understand and define ‘early’ in the use of FM amplification.

All seven study families reported very few hours of use where they felt the FM device was not helpful. Although a high percentage of benefit with FM use was reported by parents (97%), this finding is more indicative of parents being able to recognise where they would prefer to use the FM system and where they were finding most FM benefit. Once this was established for these parents in their daily routines, they were able to make regular use of the FM, resulting in highly positive feedback to the authors. It would be counter intuitive for parents to carry on using the FM in settings where they felt minimal or no benefit was being achieved. As a result, the feedback in the daily diaries for “no benefit” and “not sure of benefit” was indeed minimal compared to the overall device use.

The two participants who did not establish consistent use of the FM technology with their children did not identify any situation where they felt the FM was not beneficial. Although they noted in their diaries when they felt they were not sure of benefit, the majority of their recorded FM use was logged as “beneficial.” These results appear counter intuitive because these two participants reported the use of the FM device beneficial, yet their recorded use of the FM technology was low. Both sets of parents indicated that they felt their child’s age was a barrier to the use of FM. One mother explained that because her child was pre-verbal, the benefits of the FM were limited; apparently she was unable to establish a conversation with her child. This is an important point and suggests the value and importance of contingent language was not fully understood by the mother. Although it is natural for a mother instigating a conversation with an 11-month old child to expect some reaction, it is unclear whether this specific mother was sensitive to her young child’s non-verbal responses. This is an important area that could be a focus of parental guidance by the professionals working with the family. The second set of parents also mentioned age as a barrier to hearing aid and FM use. Both sets of parents explained that ear molds not fitting properly, ear infections and the child not keeping the hearing aids in place, resulted in inconsistent use of the hearing aids, thereby limiting the opportunities for FM use.

To conclude, research on the use of FM technology with pre-school hearing aided children is both timely and topical. The current research has provided a unique contribution to the existing literature and research base and provides a basis upon which further research in this area can be taken forward. It is anticipated that this work, together with future research, can lead to the provision of FM technology to pre-school children with hearing loss as a standard part of early intervention programs.

Acknowledgement

This research was supported by a grant from the

Economics and Social Research Council.

References

Akhtar, N. (2005). The robustness of learning through overhearing. Developmental Science, 8(2), 199-209.

Akhtar, N., Jipson, J., & Callanan, M. A. (2001). Learning words through overhearing. Child Development, 72(2), 416-430.

Bess, F. H., Chase, P. A., Gravel, J. S. et al. (1996). Amplification for Infants and Children with Hearing Loss. American Journal of Audiology, 5(1), 53-60.

Brackett, D. (Ed.). (1992). Effects of early FM use on speech perception. In M. Ross (Ed.) FM auditory training systems: Characteristics, Selection and Use. Timomium, MD: York Press.

Bradley, J. S., & Sato, H. (2008). The intelligibility of speech in elementary school classrooms. Journal of the Acoustical Society of America, 123(4), 2078-2086.

Cole, E. B., & Flexer, C. (2011). Children with Hearing Loss Developing Listening and Talking. San Diego: Plural Publishing.

Eisenberg, L. S., Shannon, R. V., Martinez, A. S., Wygonski, J., & Boothroyd, A. (2000) Speech recognition with reduced spectral cues as a function of age. Journal of the Acoustical Society of America, 107(5 I), 2704-2710.

Finitzo-Hieber, T., & Tillman, T. W. (1978). Room acoustics effects on mono-syllabic word discrimination ability for normal and hearing impaired children. Journal of Speech and Hearing Research, 21, 440-458.

Floor, P., & Akhtar, N. (2006). Can 18-month-old infants learn words by listening in on conversations? Infancy, 9(3), 327-339.

Gabbard, S. A. (2003). The use of FM technology in infants and young children. In Fabry D & Johnson CD (Eds.), Achieving Clear Communication Employing Sound Solutions. Stafa: Phonak AG.

Gilkerson, J., & Richards, J. (2008). LTR-07-2: The LENA Developmental Snapshot. Retrieved: http://www.lenafoundation.org/TechReport.aspx/Snapshot/ LTR-07-2

Hawkins, D. B., & Yacullo, W. S. (1984). Signal-to-noise ratio advantage of binaural hearing aids and directional microphones under different levels of reverberation. Journal of Speech and Hearing Disorders, 49, 278-286.

Moeller, M. (2000). Early intervention and language development in children who are deaf and hard of hearing. Pediatrics, 106(3): e43.

Moeller, M. P., Hoover, B., Peterson, B., & Stelmachowicz, P. (2009). Consistency of hearing aid use in infants with early-identified hearing loss. American Journal of Audiology, 18(1), 14-22.

Moeller, M., Donaghy, K. F., Beauchaine, K. L., Lewis, D. E., & Stelmachowicz, P. G. (1996). Longitudinal Study of FM System Use in Nonacademic Settings: Effects on Language Development. Ear and Hearing, 17(1), 28-41.

Mulla, I (2011) Pre-school use of FM technology. Unpublished PhD Thesis. School of Pshychological Sciences, University of Manchester

Neuman, A., Wroblewski, M., Hajicek, J., Rubinstein, A. (2010). Combined effects of noise and reverberation on speech recognition performance of normal-hearing children and adults. Ear and Hearing, 31, 336–344.

Nishi, K., Lewis, D., Hoover, B., Choi, S., & Stelmachowicz, P. (2010). Children’s recognition of American English consonants in noise. Journal of the Acoustical Society of America, 127 (5), 3177-3188.

Sharma, A., Dorman, M. F., & Spahr, A. J. A. (2002). Sensitive period for the development of the central auditory system in children with cochlear implants: Implications for age of implantation. Ear and Hearing, 23(6), 532-539.

Silverman, D. (2005). Doing Qualitative Research Second Edition. London: Sage.

Statham, C., & Cooper, H. (2009). Our experiences of introducing FM systems in the early years. BATOD, January: 18-20.

Valente, D., Plevinsky, H., Franco, J., Heinrichs-Graham, E., & Lewis, D. (2012). Experimental investigation of the effects of the acoustical conditions in a simulated classroom on speech recognition and learning in children. Journal of the Acoustical Society of America,

131(1), 232-246.

Willig, C. (2001). Introducing Qualitative Research in Psychology: Adventures in Theory and Method. Buckingham: Open University Press.

Yang, W. & Bradley, J. (2009). Effects of room acoustics on the intelligibility of speech in classrooms for young children, Journal of the Acoustical Society of America, 125 (2), 922-933

Yoshinaga-Itano, C., Sedey, A. L., Coulter, D. K., & Mehl, A. L. (1998). Language of earlyand later-identified children with hearing loss. Pediatrics , 102(5), 1161-1171.

C H A P T E R  N I N E

Flying to the Moon on Radio Waves:

Optimizing Outcomes with RF Technologies

Jace Wolfe, Ph.D

Abstract

Given the difficulties that children with hearing loss experience in noisy and reverberant environments, along with the proven benefits of remote microphone radio frequency (RF) technology in improving performance in these situations, pediatric audiologists should strongly consider RF technology for use with all children who use hearing aid or cochlear implant technology. This article highlights several recent advances in digital RF technology and focuses on the potential clinical benefit of these technologies. Specifically, this article addresses the fundamental concepts of digital RF transmission, the potential advantages of adaptive digital RF technology, results of recent studies examining the benefits of adaptive digital RF technologies, as well as the basic characteristics and potential benefits of digital, near-field magnetic induction.

Children with hearing loss often experience substantial difficulty understanding speech in noisy and reverberant conditions (Boothroyd, 1998; Finitzo-Hieber & Tillman, 1978; Wolfe et al., in press). These children also typically encounter greater difficulty than adults with understanding low-level speech (e.g., soft speech or speech spoken from a talker located more than a few feet away) (Nozza, 1998; Scollie et al., 2005). Wireless remote microphone (radio frequency – RF) technology has been shown to be the most effective means to improve speech recognition in these difficult listening situations (Hawkins et al., 1984; Wolfe et al., 2009). Hawkins (1984) evaluated speech recognition in noise for nine children with mild to moderate hearing loss. He reported that performance with a personal remote microphone frequency modulation (FM) technology coupled to the children’s hearing aids was significantly better than performance obtained with directional hearing aids alone. More recently, Wolfe et al (in press) studied speech recognition in quiet and in noise for children and adults with normal hearing and 15 children with moderate-to-moderately severe hearing loss. The speech recognition of the children with hearing loss was evaluated while they used only their hearing aids and also while they used personal remote microphone FM systems coupled to their personal hearing aids. When sentence recognition was assessed at a 0 dB signal-to-noise ratio (SNR), the children’s performance with use of the personal FM system improved by 50% compared to their performance with their hearing aids alone. Additionally, at a 0 dB SNR, the children’s sentence recognition with use of the personal FM system was actually better than that of the adult subjects with normal hearing.

Basic Characteristics of Wireless Radio

Frequency Technology

Wireless remote microphone technology for use with hearing aids and cochlear implants has evolved significantly over the past decade. In particular, one significant advance in wireless remote microphone technology was the commercial introduction of Dynamic FM (e.g., adaptive) technology in 2008. Personal, wireless remote microphone systems possess a parameter referred to as receiver gain, which refers to the strength of the signal that is delivered from the receiver to the user’s hearing aid or cochlear implant sound processor. With conventional remote microphone systems, the receiver gain is typically set at a fixed level such that 10 dB FM advantage is achieved (ASHA 2002; AAA, 2008). Lewis & Eiten (2004) showed that a fixed receiver advantage of 10 dB was likely too high in quiet environments when speech was not present but it was probably too low for environments with high levels of background noise (e.g., restaurants, school cafeteria, a noisy classroom or gymnasium, etc.). In fact, Lewis & Eiten (2004) reported that hearing aid users preferred an FM receiver advantage of 24 dB when listening in high-level noise.

Dynamic FM was developed to meet the wide range of user needs across a variety of listening environments. With Dynamic FM technology, the FM receiver is muted when no speech is present at the microphone of the FM transmitter. When speech is present in a quiet environment, a receiver advantage of 10 dB is provided, and as the noise level at the FM microphone increases above 57 dB SPL, the FM receiver advantage automatically increases from 10 dB to a maximum of 24 dB at an ambient noise level of approximately 80 dB SPL (Figure 1). Previous research has shown that Dynamic FM provides a significant improvement in speech recognition in noise when compared to traditional fixed-advantage FM. Specifically, improvements in speech recognition of up approximately 40% were observed at competing noise levels of 70-75 dB SPL (Thibodeau, 2010; Wolfe et al., 2009).

Figure 1. Diagram of SNR as a function of ambient noise level for various remote microphone technology conditions.

A more recent advance in wireless remote microphone technology is the development of digital radio frequency systems. Digital RF systems differ from FM systems in several respects. In order to adequately describe digital RF transmission, it is helpful to begin with a quick review of analog FM radio technology. Figure 2 provides an illustration of FM radio transmission. In short, FM radio transmission possesses a carrier wave used to deliver information from the transmitter to the receiver (see Figure 2b). The carrier wave is modulated by the speech signal (or some other signal of interest) that is captured by the FM transmitter unit. As shown in Figure 2c, the frequency of the modulated signal changes proportionally with the amplitude of the input signal.

Figure 2. An illustration of two types of radio waves: 2a) the original signal of interest, 2b) the carrier frequency of the radio wave, 2c) an example of an frequency modulated (FM) radio signal (i.e., the frequency of the carrier wave in figure 7b is modulated based on the amplitude of the original signal of interest.

For personal FM systems used with hearing aids and cochlear implants in the United States, the frequency of the carrier wave is within the 216-217 MHz bandwidth (i.e., 216 million cycles per second). With personal FM technology, the transmitter is set to a fixed carrier frequency (e.g., channel). For instance, channel 1 of the Phonak Inspiro FM transmitter corresponds to a carrier frequency of 216.0125, while channel 80 corresponds to a carrier frequency of 216.9875. When two children are using personal FM technology in adjacent classrooms, it is important that channels are selected that are spaced far apart from one another. When children use their personal FM systems in several classrooms within a school building, educational audiologists are often faced with a difficult task of appropriately managing channels of the different FM systems in order to prevent interference across systems in neighboring classrooms.

Digital RF transmission also utilizes a carrier wave to deliver the signal of interest from the transmitter to the receiver. However, this process is quite different from FM transmission. In all digital systems, the input signal to the transmitter is first converted to a digital code of “0s” and “1s.” The basic process of digital coding of the input signal is crudely illustrated in Figure 3.

Although the inherent property of transmitting a digital code is common across all digital RF systems, a variety of specific strategies may be used to transmit the digital information from the transmitter to the receiver. One of these techniques is referred to as amplitude shift keying (ASK) and is depicted in Figure 4. With ASK digital RF transmission, the digital string of “0s” and “1s” is delivered by pulsing the presence and absence of the carrier wave (see Figure 4). A “0” is represented by an absence of the carrier wave, while a “1” is represented by the presence of the carrier wave.

The ASK strategy is a technique that is used with several of the proprietary digital RF “streaming” systems offered by the manufacturers of hearing aid technology.

Figure 3. Digital coding in a 3-bit system.

Figure 4. An illustration of Amplitude Shift Keying (ASK) digital radio frequency transmission. The carrier wave is pulsed to deliver the digital code (i.e., a “0” is depicted by a cessation in the carrier wave, and a “1” is depicted by the presence of the carrier wave).

Another technique used in digital RF transmission is Gaussian frequency shift keying (GFSK) which shows for illustration purposes the simpler but similar case of Frequency Shift Keying (FSK). In GFSK, a cycle of the carrier wave is “dropped” to convey a “0,” while the cycles are preserved intact to convey a “1.” GFSK has been shown to be less susceptible to noise than the ASK technique. The GFSK strategy is commonly used in Bluetooth technology (although other modulation schemes are also used).

Regardless of whether ASK, GFSK, or another strategy (e.g., phase shift keying) is used, digital RF transmission offers several potential advantages relative to analog FM transmission. First, digital RF can remove the need to manage the transmitting channel a wearer uses to avoid interference from proximal RF systems. In short, along with the input signal captured by the RF transmitter, digital RF may also be used to deliver several additional types of information between the transmitter(s) and the receiver(s). This additional information is often referred to as control information, and can include digital passcodes, operation protocols, system optimization, etc. For instance, in a digital RF system, the transmitter and receiver are typically “connected” to one another. The reader may note that the “connecting” process is typically referred to as the “pairing” process when using Bluetooth systems. Pairing implies that two systems are wirelessly coupled to one another (i.e., a pair typically refers to two entities), while “connecting” may refer to multiple entities being wirelessly coupled to one another. In particular, connecting refers to a process in which a digital passcode is established between one or more transmitters and one or more receivers. Once the digital passcode is established between these receivers and transmitter(s), they will only transmit digital RF information within the connected network. In other words, the receivers will not accept RF signals from other transmitters and the system is essentially immune from interference from other transmitters that have not been connected into the network. This feature is one component of a digital RF system that frees the audiologist from having to worry about channel management to avoid interference from neighboring RF systems.

Another feature that contributes to digital RF’s resistance to interference is an ability to continuously “channel hop” while delivering the RF signal. Once a digital transmitter is connected to digital receivers, a protocol is established for the channels that will be used to transmit the signal as well as the order in which these channels will be used. As such, the receivers possess a “knowledge” of the channel on which the transmitter will be delivering from one moment to the next, and the receivers will accept the information delivered on that given channel at that point in time. Additionally, if receivers detect information from several digital RF sources on one particular channel, then the receivers may notify the transmitter to avoid that channel for future correspondence. Most contemporary digital RF systems operate on the 2.4 GHz band (e.g., a carrier wave with a frequency of 2.4 billion cycles per second). The 2.4 GHz band, which is a globally license-free band intended for use with industry, science and medical (ISM) applications, is much wider than the band used for analog FM transmission, and as a result, a much larger number of “transmitting channels” are available.

Digital RF provides additional theoretical advantages over analog FM transmission. For instance, because of FCC regulations, the bandwidth of personal FM technology for use with hearing aids and cochlear implants is approximately 5000 Hz (Platz, 2004). In contrast, digital RF may possess a higher bandwidth (e.g., 7500 Hz). This is likely to be a particularly important advantage for young children, as an abundance of published reports have shown the importance of high-frequency audibility (e.g., beyond 6000 Hz) for speech recognition, speech production, and language development of children with hearing loss (Moeller et al., 2007; Pittman, 2008; Stelmachowicz, Pittman, Hoover & Lewis, 2001). Furthermore, digital RF transmission will most likely provide a more robust signal with better audio quality over a longer transmission range when compared to personal FM systems. Finally, digital transmission of an RF signal potentially allows for a higher precision of control of the signal of interest. This may be beneficial in applications, such as Dynamic (e.g., adaptive) remote microphone technology (described earlier), because it theoretically allows for an improvement in the assignment of receiver gain as a function of the competing noise level.

Phonak Roger Technology

In 2013, Phonak introduced Roger technology, a proprietary digital RF system developed for use with hearing aids and cochlear implants. The Roger system uses the GFSK technique to deliver a digital RF signal on the 2.4 GHz band. Like other digital RF systems, it also features continuous channel hopping in an effort to avoid interference with neighboring digital RF systems. However, the Roger system possesses several features that are different from other digital RF systems. First, it is the only digital, Dynamic (adaptive) system available for use with hearing aids and cochlear implants. Secondly, the signal of interest is repeatedly broadcast on several channels within the 2.4 GHz band. As such, if one channel is occupied by a neighboring digital RF system, the information on that channel is discarded, but the remaining channels may be used to deliver the signal of interest. This feature reduces the likelihood of signal “drop-out.” The transmitter and receivers continually communicate with one another to locate unoccupied channels to provide a clear signal without interference. As a result, the Roger system is essentially interference-free and tapfree. Finally, the end-to-end delay of the signal from the transmitter to the receivers is about 17 milliseconds, which is considerably less than that which is found in other digital RF applications such as Bluetooth (e.g., typical end-to-end delay of approximately 40 milliseconds for Bluetooth audio streaming applications). Long delays can cause the audio signal to be out of synch with visual cues from the talker’s mouth.

Research with Adaptive Digital

Technology

A number of recent studies have explored the potential of adaptive digital technology to improve speech recognition in noise compared to analog Dynamic FM systems. Wolfe et al. (2013) evaluated sentence recognition in quiet and in the presence of classroom noise (Schafer & Thibodeau, 2006) of 44 older children and adult cochlear implant recipients. Performance was evaluated without the use of wireless remote microphone technology and with three different types of wireless remote microphone technology: 1) conventional fixed-gain personal FM (Phonak MLxS), 2) Dynamic (adaptive) personal FM (Phonak MLxi), and 3) Dynamic (adaptive) personal digital RF (Phonak Roger). The subjects experienced considerable difficulty understanding speech in noise without the use of remote microphone technology. Specifically, sentence recognition decreased by 20% from the quiet condition (95% correct) to the condition with 50 dBA of competing noise (i.e., approximately +15 dB signal-to-noise ratio), and at a SNR of approximately +5 dB, mean performance was about 25% (a 70% reduction from performance in quiet). However, at the +5 dB SNR, use of all three remote microphone technologies resulted in mean sentence recognition scores above 80% correct. Additionally, when the competing noise level was 65 dBA and higher, sentence recognition with the Roger system was significantly better than that which was obtained with the fixed-gain and Dynamic FM systems. In fact, performance with Roger was 40% better than performance with Dynamic FM at a competing noise level of 75 dBA.

Thibodeau (2012) conducted a similar study with adults and older children who had moderate to moderately severe hearing loss and who wore hearing aids. The test conditions of the Thibodeau (2013) study were very similar to the aforementioned conditions described for the Wolfe et al. (2013) study with cochlear implant users. Thibodeau (2012) also found that performance with Roger technology was significantly better than performance obtained with both fixed-gain and Dynamic FM technology. Specifically, use of Roger technology provided better sentence recognition in noise than fixedgain and Dynamic gain when the competing noise level was 65 dBA and higher. Furthermore, sentence recognition with use of Roger technology was almost 35% better at the 75 and 80 dBA competing noise levels when compared to performance with Dynamic FM.

Figure 5. An illustration of Gaussian Frequency Shift Keying (GFSK) digital radio frequency transmission. A positive frequency deviation within the carrier frequency is used to represent a binary one, and a negative frequency deviation within the carrier frequency is used to represent a binary zero.

Wolfe et al. (in press) also evaluated sentence recognition in quiet and in the presence of classroom noise for a group of adults and children with normal hearing and also for a group of school-age children who had moderate hearing loss and who wore hearing aids. Sentence recognition was evaluated for each of these groups without the use of remote microphone technology and also with the use of two different classroom audio distribution systems (CADS): 1) Audio Enhancement Elite II CADS with fixedgain, infrared transmission and four loudspeakers placed at the quartile locations in a classroom environment, and 2) Phonak DM5000 CADS with Dynamic (adaptive) digital RF from a tower of an array of 12 loudspeakers positioned in the front of the classroom adjacent to the loudspeaker used to present the target sentences. The subjects sat at the back of the classroom approximately 17 feet from the loudspeaker used to present the target sentences. It should also be noted that the subjects were seated approximately 19 feet away from the Phonak DM5000 CADS tower and approximately 7 feet away from the Audio Enhancement Elite II loudspeakers located toward the back of the classroom.

For both the adults and children with normal hearing as well as for the children with hearing loss, the use of the CADS system provided a significant improvement in sentence recognition in noise. Specifically, at a 5 dB SNR, use of the CADS resulted in greater than a 25% improvement in sentence recognition for the children with hearing loss. Additionally, the single-tower, Phonak DM5000 adaptive digital RF system provided significantly better sentence recognition in noise relative to the Audio Enhancement Elite II fixed-gain, multiple-loudspeaker system at the 70 and 75 dBA competing noise levels.

Additional Wireless Technologies

Over the past several years, a number of hearing aid manufacturers have begun to incorporate wireless hearing assistance technology into their products. These wireless accessories are often referred to as digital streaming devices and include numerous modes of application such as wireless streaming of an audio signal from a mobile telephone interface, a remote microphone, or a television interface directly to a user’s hearing aids. Wireless streaming may also be used to deliver wideband audio signals from one hearing aid to the hearing aid on the opposite ear. For detailed information related to the various streaming accessories located in the commercial hearing aid market, the interested reader is referred to these sources of information (Crose, Kuk, & Bindeballe, 2011; Groth & Pedersen, 2012; Jespersen & Laureyns, 2013; Kuk, Crose, Korhonen P, et al., 2010; Kuk, Crose, Kyhn, et al. 2011; Stender, 2012).

Wireless streaming devices typically transmit the signal of interest from a source object (e.g., mobile telephone, television, remote microphone, etc.) to the hearing aids via digital RF within the 2.4 GHz band. Some manufacturers have developed their own proprietary systems to transmit the signal of interest via proprietary digital RF within the 2.4 GHz band from a source (e.g., remote microphone, mobile telephone accessory, etc.) to a receiver integrated into the hearing aids as shown in Figure 6 (Crose, Kuk, & Bindeballe , 2011; Groth & Pedersen, 2012; Jespersen & Laureyns, 2013; Kuk, Crose, Korhonen P, et al., 2010; Kuk, Crose, Kyhn, et al. 2011; Stender, 2012). Other manufacturers have developed audio streaming systems in which the signal of interest is delivered via Bluetooth from the source (e.g., a remote microphone, a television accessory, or a Bluetooth-enabled mobile telephone) to a neck-worn interface, which relays the signal to the user’s hearing aids via digital near-field magnetic induction (Figure 7).

Figure 6. An example of a digital wireless “streaming” system in which the audio signal of interest is delivered from an external source (e.g., television interface, mobile telephone interface, remote microphone) to a hearing aid (Resound Alera) via proprietary digital RF on the 2.4 GHz bandwidth.

Figure 7. An illustration of a digital wireless “streaming” system in which the audio signal of interest is delivered from an external source (e.g., television interface, mobile telephone interface, remote microphone) to a streaming interface (Phonak ComPilot) via Bluetooth and then to a cochlear implant sound processor (Advanced Bionics Naida CI Q70) via digital near-field magnetic induction.

Digital Near-Field Magnetic Induction for Audio Streaming

The reader may ask why one system would stream directly to a receiver/antenna integrated into the body of the hearing aid, while another would incorporate a neckworn interface for streaming applications. As previously mentioned, the system that uses a neck-worn interface delivers the signal to the hearing aids via digital nearfield magnetic induction (DNFMI). DNFMI may be used to deliver wideband audio signals in the form of a digital code via magnetic induction over short distances (e.g., less than a meter) with minimal delay and low power requirements, which allows for audio signals, such as speech, to be streamed from one hearing aid to a hearing aid on the opposite ear. This feature, which Phonak commercially refers to as the Hearing Instrument Body Area Network (HIBAN), allows for several advanced forms of signal processing to be provided to assist the wearer in challenging listening situations.

For instance, the beam-forming that occurs at the directional microphone system of each hearing aid may be integrated across hearing aids to provide a higher-order beam-former that provides better performance in noisy environments compared to that which is obtained when the directional systems of two hearing aids work independently of one another (i.e., StereoZoom) (Latzel, 2012). Additionally, DNFMI can allow for signals arriving from one side of the wearer to be streamed to the opposite hearing aid (i.e., ZoomControl). Studies have shown that this application improves speech recognition when the signal of interest arrives from the side of a listener (e.g., in an automobile) (Nyffeler, 2009). Furthermore, the signal at each hearing aid can be compared across hearing aids to offer a significant improvement in speech recognition in wind noise (Latzel, 2012).

Another feature made possible by DNFMI is commercially referred to as the DuoPhone and involves the wireless delivery of the telephone signal captured at one hearing aid to the opposite hearing aid to allow for binaural hearing on the telephone. Picou & Ricketts (2011, 2013) have recently shown that binaural hearing on the telephone results in a 20-30% improvement in speech recognition on the telephone compared to performance in the monaural listening condition. Wolfe and colleagues (in press) also compared speech recognition over the telephone for a group of young children, who were assessed in the monaural condition and also in the binaural condition (e.g., DuoPhone). They found that speech recognition on the telephone with the DuoPhone feature was almost 30% better than performance in the monaural condition.

Case Study

The benefits and limitations of the aforementioned technologies are nicely exemplified in the following case study. A 48 year-old Advanced Bionics cochlear implant recipient has participated in a number of clinical studies evaluating wireless RF technology at our center. She served as a subject in a study evaluating sentence recognition in quiet and in noise without the use of wireless remote microphone technology and with a fixed-advantage FM personal FM system (Phonak MLxS), a Dynamic (adaptive) personal FM system (Phonak MLxi), and a Dynamic (adaptive) digital RF system (Phonak Roger). Her sentence recognition results are provided in Figure 8. As shown in Figure 8, she performed quite well without wireless remote microphone technology in quiet (95% correct), but in a noisy condition similar to what might be encountered in the real world (classroom noise at 60 dBA/5 dB SNR), she struggled substantially (23% correct).

Figure 8. Sentence recognition in quiet and at seven different competing noise levels for a bilateral Advanced Bionics cochlear implant recipient using different wireless remote microphone technologies.

However, with use of remote microphone technology, she scored over 90% correct in the same noise condition, and her performance with Roger at higher noise levels was significantly better than what she obtained with Dynamic (adaptive) FM or fixed-advantage technology.

She has also participated in a study in which performance was assessed with use of a digital RF streaming system similar to what is available from many manufacturers for use with hearing aids or cochlear implant sound processors. Sentence recognition in noise was evaluated using a Phonak Roger personal RF system and also with the Phonak RemoteMic and ComPilot streaming system (Figure 9). The Phonak RemoteMic is a fixed-gain wireless transmitter that uses Bluetooth to deliver the signal of interest to the ComPilot interface. The Phonak RemoteMic possesses an omni-directional microphone similar to what is found in the streaming systems of other hearing technology manufacturers. Additionally, it is not a Dynamic (adaptive) system. The ComPilot interface is worn around the neck of the user, and it captures the signal from the RemoteMic and delivers it to the wearer’s hearing aids via digital near-field magnetic induction. The subject’s sentence recognition results with each system are provided in Figure 9. Use of the Phonak RemoteMic/ComPilot system is clearly beneficial as evidenced by the fact that sentence recognition in noise is greatly improved compared to the condition in which no remote microphone technology was used. However, use of the Phonak Roger Dynamic (adaptive) digital system provided significantly better sentence recognition in noise when compared to the RemoteMic/ComPilot system. The better performance obtained with the Phonak Roger systems can most likely be attributed to several reasons: 1) the Roger system provides adaptive increases in receiver gain with increases in the competing noise, 2) the Phonak Roger system possesses beam-forming at the microphone of the transmitter, and 3) the Phonak Roger system possesses digital noise reduction at the transmitter.

Figure 9. Sentence recognition in noise for a bilateral Advanced Bionics cochlear implant recipient using a digital wireless “streaming” system and a digital adaptive personal RF system (e.g., Phonak Roger).

Finally, this subject also participated in a study examining recorded word recognition over the telephone. As shown in Figure 10, she experienced great difficulty understanding monosyllabic words in the monaural condition. However, her speech recognition improved significantly when she was able to receive the signal bilaterally with use of the DuoPhone feature. Furthermore, significant improvement in word recognition in noise over the telephone was observed in the DuoPhone feature when the telecoil was used to capture the telephone signal and the processor microphones were attenuated by 10 dB.

Figure 10. Word recognition scores for recorded monosyllabic words presented over the telephone to a bilateral Advanced Bionics cochlear implant recipient.

Children (and adults for that matter) frequently experience difficulty understanding speech in noisy and reverberant environments. They also often experience difficulty with understanding low-level speech (e.g., softspoken speech or speech that originates from more than a few feet away from the child) and speech that originates from a telephone. Use of digital, Dynamic (adaptive) RF technology (e.g., Phonak Roger) provides significant improvement in these difficult listening situations. Additionally, the binaural listening via the DuoPhone feature has the potential to substantially improve speech recognition over the telephone. Pediatric audiologists should consider digital, Dynamic (adaptive) RF technology, such as Roger, as imperative for use by all children with hearing loss, regardless of their age or the type of personal hearing technology (e.g., hearing aids or cochlear implants) they are using. Finally, pediatric audiologists should always strive to ensure that children with hearing loss are able to access important speech and environmental sounds with both ears.

Acknowledgement

This research was partially funded by a grant from Phonak AG.

References

American Academy of Audiology. (2008). Remote microphone hearing assistance technologies for children and youth. Reston, VA.

American Speech-Language-Hearing Association. (2002). Guidelines for fitting and evaluation of FM systems. Rockville, MD.

Crose, B., Kuk, F., Bindeballe, H. (2011). Digital wireless hearing aids, part 4: Interference. Hearing Review, 18(13), 30-39.

Finitzo-Hieber, T. & Tillman, T. (1978). Room acoustics effects on monosyllabic word discrimination ability for normal and hearing impaired children. Journal of Speech and Hearing Research, 21, 440-458.

Groth, J. & Pedersen, B.D. (2012). How user requirements affect technology choice for wireless hearing instruments. ReSound White Paper. Retrieved on January 28, 2014 at http://www.gnresound.com/~/media/DownloadLibrary/ReSound/White%20 papers/user-requirements-affects-choices-wireless-white-paper.pdf

Hawkins, D.B. (1984). Comparisons of speech recognition in noise by mildly-to-moderately hearing-impaired children using hearing aids and FM systems. Journal of Speech and Hearing Disorders, 49, 409-418.

Jespersen, C.T. & Laureyns, L. (2013). ReSound Unite Mini Microphone for maximum understanding. ReSound White Paper. Retrieved on January 28, 2014 at http://www.gnresound.com/~/media/DownloadLibrary/ReSound/White%20papers/verso/ReSound%20unite%20Mini%20MIcrophone.pdf

Kuk, F., Crose, B., Korhonen, P., et al. (2010). Digital wireless hearing aids: Part 1: A primer. Hearing Review, 17(3), 54-67.

Kuk, F., Crose, B., Kyhn, T., et al. (2011). Digital wireless hearing aids: Part 3: Audiological benefits. Hearing Review, 18(8), 48-56.

Kuk, F., Korhonen, P., Crose, B., et al. (2011). Digital wireless hearing aids: Part 2: Considerations in developing a new wireless platform. Hearing Review, 18(6), 46-53.

Latzel, M. (2012). Binaural VoiceStream Technology™ Intelligent binaural algorithms to improve speech understanding. Phonak Insight. Staefa, Switzerland: Phonak AG. Retrieved on January 28, 2014 at http://www.phonakpro.com/us/b2b/en/evidence/to-pics/auto-stereozoom.html

Lewis, D., & Eiten, L. (2004). Assessment of advanced hearing instrument and FM technology. In D.A. Fabry and C. DeConde Johnson (Eds.), ACCESS: Achieving Clear Communication Employing Sound Solutions-2003. Proceedings of the First International FM Conference. (pp. 167–174). Staefa, Switzerland: Phonak AG.

Moeller, M.P., Hoover, B., Putman, C., Arbataitis, K., Bohnenkamp, G., et al. (2007). Vocalizations of infants with hearing loss compared with infants with normal hearing: Part I phonetic development. Ear and Hearing, 28(5), 605-627.

Nozza, R.J. (1988). Auditory deficit in infants with otitis media: More than a “mild” hearing loss. In D. Lim, C. Bluestone, J. Klein, and J. Nelson (eds.), Recent Advances in Otitis Media: Proceedings of the Fourth International Symposium (pp 376-379). Toronto: BC Decker.

Nyffeler, M. (2010). Binaural directionality wireless communication opens the door to a completely new approach in directional multi-microphone systems. Phonak Insight. Phonak AG: 2010. Retrieved on January 28, 2014 at http://www.phonakpro.com/us/ b2b/en/evidence/topics/auto-stereozoom.html

Picou, E.M. & Ricketts, T.A. (2011). Comparison of wireless and acoustic hearing aid-based telephone listening strategies. Ear and Hearing, 32(2), 209-220.

Picou, E. & Ricketts, T. (2013). Efficacy of hearing-aid based telephone strategies for listeners with moderate-to-severe hearing loss. Journal of the American Academy of Audiology, 24, 59-70.

Platz, R. (2004). SNR advantage, FM advantage, and FM fitting. In D.A. Fabry and C. DeConde Johnson (Eds.), ACCESS: Achieving Clear Communication Employing Sound Solutions-2003. Proceedings of the First International FM Conference. (pp. 147–154). Staefa, Switzerland: Phonak AG.

Schafer, E.C. & Thibodeau, L.M. (2006). Speech recognition in noise in children with cochlear implants while listening in bilateral, bimodal, and FM system arrangements. American Journal of Audiology, 15(2), 114-126.

Scollie, S., Seewald, R., Cornelisse, L., Moodie, S., Bagatto, M., et al. (2005). The Desired Sensation Level Multistage Input/Output Algorithm. Trends in Amplification, 9, 159-197.

Stelmachowicz, P. G., Pittman, A. L., Hoover, B. M., & Lewis, D. E. (2001). Effect of stimulus bandwidth on the perception of /s/ in normaland hearing-impaired children and adults. Journal of the Acoustical Society of America, 110, 2183–2190.

Stender, T. (2012). ReSound Alera and the Unite wireless accessories – Connecting the hearing instrument user to the world. ReSound White Paper. Retrieved on January 28, 2014 at http://www.gnresound.com/~/media/DownloadLibrary/ReSound/00-local-downloads/US/ Global-Audiology-white papers/RESOUND%20ALERA%20AND%20THE%20UNITE%20WIRELESS%20ACCESSORIES.pdf

Thibodeau, L. (2010). Benefits of adaptive FM systems on speech recognition in noise for listeners who use hearing aids. American Journal of Audiology, 19(1), 36-45.

Thibodeau, L. (2012). Results with devices that utilize DM technology. Oral Presentation at the Phonak Advances in Audiology Conference. December 4, 2012, Las Vegas, NV.

Wolfe, J., Morais, M., Neumann, S., Schafer, E., Wells, N., et al. (in press, 2014). Evaluation of speech recognition with personal FM and classroom audio distribution systems. Journal of Educational Audiology Association.

Wolfe, J., Morais, M., Schafer, E., Mills, E., Mülder, H.E., et al., (2013). Evaluation of speech recognition of cochlear implant recipients using a personal digital adaptive radio frequency system. Journal of the American Academy of Audiology, 24(8), 714-724.

Wolfe, J., Schafer, E. C., Heldner, B., Mulder, H., Ward, E., and Vincent, B. (2009). Evaluation of speech recognition in noise with cochlear implants and dynamic FM. Journal of the American Academy of Audiology, 20(7), 409-421.

Wolfe, J., Schafer, E., Mills, E., J. A., Hudson, M., Anderson, S. (submitted 2014). Evaluation of the benefits of binaural hearing on the telephone for children with hearing loss. Journal of American Academy of Audiology.

S E C T I O N  I I I

Integration of Hearing Aids and Cochlear Implants

Session Chair: Susan Scollie (CAN)

C H A P T E R  T E N

Frequency Lowering Hearing Aids:

Procedures for Assessing Candidacy and Fine Tuning

Susan Scollie, Ph.D. Danielle Glista, Ph.D. Frances Richert, M.Sc.

Abstract

Frequency lowering signal processing is an increasingly common feature in modern hearing aids. New clinical guideline documents, such as the American Academy of Audiology Clinical Practice Guideline on Pediatric Amplification (2013) stress that electroacoustic verification of frequency lowering is an important part of fitting such devices for children who use hearing aids. Verification protocols should focus on how the processors affect the audibility of speech. This article presents a specific approach to this, along with a series of three case studies that illustrate the role of speech-based verification in considering fine tuning to optimize benefit, assessment of candidacy for frequency lowering, and the use of frequency lowering for asymmetrical hearing losses.

During the past decade, the use of frequency lowering signal processing in hearing aids has received considerable attention in terms of product development, research evaluation, and clinical application. The term “frequency lowering” is used to describe a diverse category of signal processors, which have in common the ability to transfer high frequency sound to a lower frequency within the hearing aid output. Detailed descriptions of the types of signal processors that provide frequency lowering are available from Alexander (2013) and in a recent threepart series of articles online (Alexander, 2013; Mueller, Alexander, & Scollie, 2013; Scollie, 2013). At this time, there are five brands of frequency lowering hearing aids on the market: listed in order of release to market these are: Widex (AudibilityExtender® or frequency transposition), Phonak/Unitron (SoundRecover® or nonlinear frequency compression), Starkey (SpectralIQ® or spectral warping), Siemens (nonlinear frequency compression) and Bernafon (FrequencyComposition®). The suggested clinical use of frequency lowering processors is to overcome limitations in audibility of high frequency sound by presenting them to the listener at a lower frequency. This use is important when sounds are inaudible due to limits imposed by the listener’s hearing thresholds or by limitations in the high frequency hearing aid output. It is often suggested that hearing specific high frequency phonemes, such as female utterances of “s” and “f”, require that the listener have access to speech energy above 4000 Hz. Specific studies comparing the performance of children with versus without audibility (via bandwidth changes, not via frequency lowering) above 4000 Hz reveal differences in a variety of perceptual outcome measures including rates of learning new words (Pittman, 2008; Stelmachowicz et al., 2004). Overall, studies of the effects of extended bandwidth of audible speech indicate that children benefit from hearing speech cues above 4000 Hz – in past studies that used a “full bandwidth” condition that includes energy to 9000 Hz. Clinically, our hearing aid fittings may roll off between 4000 and 9000 Hz. The exact cutoff of necessary audibility within this range (e.g., 6000 Hz, 8000 Hz) is not known at this time, and clear verification protocols for high frequency verification are not widely available. Regardless, our clinical fittings strive to provide as broad a bandwidth of audibility as possible. Improvements over the last few years, including changes in feedback control and prevention as well as microphone and receiver technologies and digital signal processing, have broadened the achievable bandwidth available in commercial hearing aids. Extended bandwidth hearing aid fitting is now more possible than ever before.

Even with improvements in technology, some fittings are still limited in audible bandwidth, to the point that access to specific phonemes (such as fricatives) remains limited. With this in mind, we may design a hearing aid fitting that allows input of the high frequency energy into the hearing aid microphone, sends the energy to a digital signal processor that transfers it downward in the frequency domain, and amplifies the frequency-lowered sound to audible levels. Fitting this type of hearing aid requires that the audiologist perform frequency-gain shaping to optimize speech audibility (as they would with conventional processing) and also to adjust the degree of frequency lowering. This article will describe one set of procedures that may be used to evaluate candidacy for frequency lowering signal processing, and also to verify its function and adjust it for the listening needs of the individual listener.

Recommended Protocols

A recent evidence-based Clinical Practice Guideline on Pediatric Amplification (AAA Task Force on Pediatric Amplification, 2013) provides some guidance on candidacy and fitting of frequency lowering signal processors. In terms of candidacy, this Guideline recommends that frequency lowering “. . .should not be prescribed until electroacoustic verification has revealed that high-frequency speech audibility cannot be restored through conventional means.” In terms of verification and fine tuning, the Guideline states, “The impact of hearing aid signal processing and features such as . . . frequency lowering on audibility should be verified. . . the impact of these features on audibility of speech should be evaluated.” Taken together, these statements indicate clearly that verification of speech audibility is the primary consideration in deciding whether and how to fit this type of processor.

In 2009, Glista & Scollie developed a suggested clinical verification protocol, summarized in Figure 1. This general protocol has been used to fit one specific form of frequency lowering, known as nonlinear frequency compression, in several studies of efficacy and effectiveness in children. These studies have investigated outcomes in children with a wide range of hearing losses (Bohnert et al., 2011; Glista et al., 2009; Wolfe et al., 2010), sound quality effects in adults and children (Parsa et al., 2013), and the acclimatization time course and/or long term outcomes in children and adolescents (Glista, Easwar, Purcell, & Scollie, 2012; Glista, Scollie, & Sulkers, 2012; Wolfe et al., 2011).

Fitting Steps for Frequency Lowering

Hearing Aids

1. Verify the shape and gain of the fitting without frequency lowering.

✓ To ensure best audible bandwidth of speech from gain & WDRC alone.

2. Verify the maximum power output (MPO)

✓ To ensure that high level sounds are limited appropriately.

✓ MPO measurements are not valid above cutoff frequency.

✓ It may be necessary to disable frequency lowering to measure MPO at all frequencies for some hearing aids and analyzers.

3. Start with the default frequency lowering setting

✓ Assess the need for frequency lowering by estimating high-frequency audibility with and without it.

✓ Use a moderate level (65 dB SPL) to test this above the compression threshold.

4. Measures of frequency-specific speech bands or phonemes can help evaluate:

✓ The amount of lowering that has been applied to the signal.

✓ The approximate sensation level of high-frequency speech sounds.

✓ The overlap between similar fricatives (S and SH). Too much overlap may lead to confusion.

✓ Perform a listening check and review outcomes:

✓ Consider sound quality judgments from the listener as well as the clinician.

✓ Consider outcomes and feedback from user, parents, and therapists.

6. Repeat steps to fine tune as needed.

[adapted from Glista & Scollie (2009) AudiologyOnline]

Figure 1. Steps to follow in the verification and fine tuning of pediatric hearing aid fittings, taking into consideration the application and strength of a frequency lowering signal processor.

The verification stimuli used in these studies have, however, varied to some degree. One specific hearing aid analyzer provides a filtered speech signal that supports evaluation of audibility and frequency lowering of a one-third octave band of speech (Glista & Scollie, 2009). An alternative to these third-octave bands are measures of specific fricatives (typically “s” and “sh”), measured either with live presentations by the fitter or with the use of pre-recorded fricatives presented at calibrated levels. More recent recommendations to use calibrated fricatives acknowledge that fricatives tend to be fairly broad in bandwidth compared to one-third bands of speech. For some fittings, verifying with realistic fricatives can reveal partial audibility from the lower shoulder of the fricative that acts as an important cue for the listener. Particularly for challenging fittings with steeply sloping hearing losses, this information can be important and provide a better prediction of aided outcomes. This important pattern of verification results has been illustrated in detail for specific cases from past studies (Glista, Scollie, & Sulkers, 2010; Scollie & Glista, 2011).

For these reasons, we have begun implementing verification with synthetic, calibrated fricatives. These stimuli are still under evaluation, but have the potential to make verification of frequency lowering faster and more repeatable, compared to verification with live voice stimuli. In the section below, the use of these stimuli is illustrated in several pediatric cases. These cases illustrate a range of issues we face with the use of frequency lowering signal processors, including making candidacy decisions, fine tuning, and relating verification measures to outcomes assessments.

Case 1: Tuning to Improve Benefit

In this example, we examine the hearing aid fitting provided to a young boy with a steeply sloping hearing loss. He was enrolled in a trial of frequency lowering hearing aids, in which we found that he had significant benefit from the processor. This case has been previously reported (Scollie & Glista, 2011), and is shown here with the hearing aids re-measured using calibrated synthetic “s” and “sh” stimuli, following the verification protocol in Figure 1. Although not shown here, his hearing aid response with frequency lowering disabled provided an amplified “s” that was 20 dB below his threshold at the peak of the “s”, which was consistent with his relatively poor ability to detect or recognize the “s” sound in objective testing. Therefore, the frequency lowering processor was enabled and fine-tuned by evaluating it across various strengths. In the example shown, two potential settings of his hearing aids were investigated to determine which setting should be provided. In this fine tuning process, the aids were adjusted away from default frequency lowering settings in an attempt to improve the audibility of “s” and “sh”.

Figure 2 shows verification results at both a weaker and a stronger setting. For the weaker setting, the “sh” is audible in the 1500 Hz region (along the sloping portion of the hearing threshold line). Additional “sh” audibility may be present between 2000 and 3000 Hz. The “s” is amplified and lowered in frequency, but is not within the auditory area for the weaker frequency lowering setting. In contrast, the stronger setting amplifies both fricatives to within the auditory area, along the sloping portion of the auditory thresholds. Some frequency separation between the two sounds is provided with this fitting, which we would expect to support differentiation of the two sounds. The impact of these two fittings was also assessed using three outcome measures: (1) a test of consonant recognition using all 21 consonants of English in a nonsense syllable format; (2) a three-alternative forced choice assessment of S-SH discrimination; and (3) an informal assessment of the child’s preference between these two settings. All three outcome measures indicated improved outcomes with the stronger setting. This case, and another similar case (Glista, et al., 2010) illustrate the importance of partial fricative cues: it is possible for a child to detect and learn to recognize these fricatives based on hearing the lower shoulder of the frication band. This type of fitting provides higher objective performance on speech sound detection and recognition tests, and may be preferred by the child, compared to a fitting in which the fricatives are inaudible.

Figure 2. Verification of the hearing aid fitting described for Case 1, with comparison of two strengths of frequency lowering signal processing. Outcome results for each strength are noted alongside each fitting.

Case 2: Verification to Determine

Candidacy

In our second case, we examine current candidacy for frequency lowering for a 10 year old boy with a stable flat (5 dB/octave) severe sensorineural hearing loss. He has been using frequency lowering hearing aids for several years, and was recently seen for refitting with new instruments. His old hearing aids had bandwidth limitations that restricted his access to high frequency fricatives, so his clinician provided and fine-tuned a frequency lowering processor to improve access to “s” and “sh”. He had been a regular user of these hearing aids for several years, and therefore is considered to have acclimatized to the processor. Because his new, more recently developed hearing aids have more high frequency gain and output than was available at his last fitting, verification results in steps 1-3 (Figure 1) show a different result than has been observed in previous sessions. His candidacy assessment for frequency lowering is shown in Figure 3. The “s” stimulus is 10 to 20 dB above threshold with frequency lowering turned off. The effect of enabling the frequency lowering processor certainly lowers the “s”, but is not needed to achieve audibility. The differences shown for “s” in Figure 3 would not be expected to enhance detection of “s”. His clinician was concerned about potential transition challenges in moving from frequency enabled to disabled, if the processor was turned off based on the results shown in Figure 3. After all, this child was a seasoned user of this processor, and it is possible that the processor might have benefits not revealed by this verification protocol. For example, what if the processor would allow detection of “s” in lower levels of speech than tested here (using a 65 dB SPL stimulus)? Would disabling frequency lowering then result in poorer outcomes? What if the child preferred to leave the processor on? Recalling that this child was ten years old, and able to complete outcomes assessments, his clinician completed an informal trial to determine the best settings for him.

Figure 3. Verification of the hearing aid fitting described for Case 2, with comparison of frequency lowering signal processing set to either off or on.

Over the next two appointments, she completed two measures of high frequency speech sound detection: the Ling 6(HL) threshold test and the UWO Plurals test (Glista & Scollie, 2012; Scollie et al., 2012). She also provided the child with a two-program hearing aid fitting (frequency lowering enabled and disabled, all other settings held constant) and queried him about his real world preferences following a trial period of about one month. Objective tests revealed that he had good and equal performance either with frequency lowering enabled or disabled. He had no preference for either setting, nor did he notice any important differences in his ability to hear in real world environments. In the end, she decided to disable the processor. Presentation of this case generated discussion among attendees at this conference, including discussion of ideas such as use of a weaker setting, or of progressively weakening the setting across appointments to “ease” the child out of the processor. Any of these strategies, including disabling the processor, are likely reasonable in this case. Further research is certainly needed on how ongoing development of extended bandwidths impacts candidacy for frequency lowering, including how best to verify and evaluate any changes in outcome. This case illustrates the roles of verification and careful monitoring of outcomes, as suggested by the AAA (2013) Guidelines, in the management of children, particularly when new devices are being considered.

Case 3: Asymmetrical Fittings

One frequently asked question in the topic of frequency lowering is how these processors should be fitted for asymmetrical hearing losses. Should the fitting be fine-tuned for each ear? Or, like the default settings in many hearing aid software systems, should the settings developed for the better ear be carried over to the poorer ear? The second strategy was used for most of the participants in our lab’s first trial of frequency compression (Glista et al., 2009). This was done as a conservative strategy in our first attempt to evaluate outcomes from this processor: creating an experimental design that compared asymmetrical to symmetrical settings was not within the scope of that trial. Recently, researchers have begun to explore outcomes for adults who have asymmetrical hearing losses (John et al., 2013). This study revealed some interesting and positive outcomes when audibility was provided on a per-ear basis rather than using the better ear’s weaker settings for the poorer ear.

Our third case illustrates the application of the perear strategy on a nine year old child with significant asymmetry between ears. Consideration of this type of case is highly relevant to pediatric hearing aid fittings given the incidence of asymmetric and oddly configured hearing losses in a pediatric caseload (Pittman, 2004). In this case, the clinician had previously provided a hearing aid fitting without frequency lowering to the better left ear, and had monitored the child over a period of use. A fitting goal for the poorer right ear included addressing lack of high frequency audibility and incorporating an acoustic vent. Over time, several barriers to the addition of a vent have been crossed. At a recent appointment, the child’s ear was large enough to accommodate a vent, a vented earmold had been ordered and fitted, and the child’s behaviour was adequate to support an on-ear verification with repeated fine tuning. The clinician decided to focus the fine tuning during this appointment on the poorer ear for several reasons: (1) the fitting on the better ear was well established, successful, and did not present any major concerns; (2) the fitting context now allowed the clinician to evaluate the effects of both venting (because vented on-ear measures were now possible) and frequency lowering, so a comprehensive verification and retuning of the poorer ear seemed like the best next step. The end result of this fitting session is shown in Figure 4.

Figure 4. Verification of the hearing aid fitting described for Case 3, with measures and setting completed independently for the left and right ears.

The better ear fitting has good access to high frequency fricatives, in part because of a region of better hearing in the 4 kHz area. The poorer ear has goodaccess to the low frequencies. Detailed verification of this is not shown, but the low frequency response is the result of both vent-transmitted and aid-transmitted sound. Frequency lowering has been enabled and tuned according to Figure 1, resulting in audibility of both “s” and “sh”, while ensuring some frequency separation between these two sounds. The child’s impressions at the time of fitting were documented in chart notes as “remarked immediately on improved audibility of sounds following today’s adjustments”. Because minor tuning was also done to the better left ear, we cannot attribute this comment only to the activation of frequency lowering. However, this fitting is highly asymmetrical in terms of hearing profile, frequency-gain response, and strength of frequency lowering, yet these differences were not barriers to perceived benefit. It is informative to observe that a per-ear fitting strategy was received as a positive improvement by this child. Further work in this area could allow us to better understand the complexities in fitting asymmetrical hearing losses.

Summary and Implications

Frequency lowering has become a widely available class of signal processing in hearing instruments designed for pediatric and high power hearing aid fittings. Research studies are now available that speak to the range of candidacy, effects, outcome measures, and fitting approaches for frequency lowering devices. As always, there is more to know, but consensus is emerging on acceptable, evidence-based approaches to candidacy evaluation, fine tuning, and outcome assessment for frequency lowering hearing aids. The recently issued AAA (2013) Guideline provides structured concepts for when to use it, and how to assess the impact of frequency lowering. This article presents ongoing work toward a specific protocol that would satisfy the AAA (2013) requirements. The three cases presented here illustrate typical challenges in a pediatric audiologist’s caseload, and specific assessment of frequency lowering candidacy and need for fine tuning. Electroacoustic tools are at the heart of both the Guideline and the protocol shown here: calibrated fricatives may be measured in the aided signal, and incorporated into the real ear verification protocols that are often used in pediatric hearing aid fitting.

References

American Academy of Audiology Task Force on Pediatric Amplification (2013). Clinical Practice Guidelines: Pediatric Amplification. Retrieved from http://www.audiology.org/resources/documentlibrary/Documents/PediatricAmplificationGuidelines.pdf

Alexander, J.M. (2013). Individual variability in recognition of frequency-lowered speech. Seminars in Hearing, 34, 86-109.

Alexander, J.M. (2013, April). 20Q: The Highs and lows of frequency lowering amplification. AudiologyOnline, Article #11772. Retrieved from: http://www.audiologyonline.com/

Bohnert, A. Nyffeler, M., Müller, S., Brantzen, P., & Keilmann, A. (2011). Use of nonlinear frequency compression for children with severe to profound hearing loss. In R.C. Seewald & J. Bamford (Eds.), A Sound Foundation Through Early Amplification: Proceedings of the Fifth International Conference. Stäefa Switzerland: Phonak AG (pp. 211-216).

Glista, D., Scollie, S., Bagatto, M., Seewald, R., Parsa, V., & Johnson, A. (2009). Evaluation of nonlinear frequency compression: Clinical outcomes. International Journal of Audiology, 48(9), 632-644.

Glista, D., & Scollie, S. (2009). Modified verification approaches for frequency lowering devices. AudiologyOnline. Retrieved from http://www.audiologyonline. com/articles.

Glista, D., & Scollie, S. (2012). Development and evaluation of an English language measure of detection of word-final plurality markers: The University of Western Ontario Plurals Test. American Journal of Audiology, 21, 76-81.

Glista, D., Scollie, S. & Sulkers, J. (2010). Nonlinear frequency compression hearing aids: Do children need an acclimatization time? In R. C. Seewald & J. M. Bamford (Eds.) A Sound Foundation Through Early Amplification 2010: Proceedings of the Fifth International Conference. Staefa, Switzerland: Phonak AG (pp. 205-210).

Glista, D., Scollie, S., & Sulkers, J. (2012). Perceptual Acclimatization Post Nonlinear Frequency Compression Hearing Aid Fitting in Older Children. Journal of Speech, Language, and Hearing Research, 55(6): 1765-1787.

Glista, D., Easwar, V., Purcell, D., & Scollie, S. (2012). A Pilot Study on Cortical Auditory Evoked Potentials (CAEPs) in Children: Aided CAEPs change with frequency compression hearing aid technology. International Journal of Otolaryngology. Published online Oct 31, 2012. doi: 10.1155/2012/982894.

John, A., Wolfe, J., Schafer, E., Hudson, M., Fox, K., Wheeler, J., & Wallace, H. (2013). Asymmetric high-frequency hearing loss, NLFC helps. The Hearing Journal: 66(9), 26-29. doi: 10.1097/01.HJ.0000434631.77316.87

Mueller, H.G., Alexander, J.M., & Scollie, S. (2013, June). 20Q: Frequency lowering the whole shebang. AudiologyOnline, Article #11913. Retrieved from http://www.audiologyonline.com/

Parsa, V. Scollie, S., Glista, D. & Seelisch, A. (2013). Nonlinear frequency compression: Effects on sound quality ratings of speech and music. Trends in Amplification, 17(1), 54-88.

Pittman, A. L. (2008). Short-term word learning rate in children with normal hearing and children with hearing loss in limited and extended high-frequency bandwidths. Journal of Speech, Language, and Hearing Research, 51, 785-797.

Pittman, A.L. (2004). Audiometric configurations in children. In A Sound Foundation Through Early Amplification 2004; Proceedings of the Third International Conference, R.C. Seewald & J.S. Gravel (Eds), Stäefa, Switzerland: Phonak AG.

Scollie, S. (2013, May). 20Q: The Ins and outs of frequency lowering amplification. AudiologyOnline, Article #11863. Retrieved from: http://www.audiologyonline. com/

Scollie, S., & Glista, D. (2011). Digital signal processing for access to high frequency sounds: Implications for children who use hearing aids. ENT & Audiology News, 20(5), 83-87.

Scollie, S., Glista, D., Tenhaaf Le Quelenec, J., Dunn, A., Malandrino, A., Keene, K., & Folkeard, P. (2012). Ling 6 stimuli and normative data for detection of Ling-6 sounds in hearing level. American Journal of Audiology, 21(2), 232-241.

Stelmachowicz, P. G., Pittman, A. L., Hoover, B. M., Lewis, D. L., & Moeller, M. P. (2004). The importance of high-frequency audibility in the speech and language development of children with hearing loss. Archives of Otolaryngology Head and Neck Surgery, 130, 556-562.

Wolfe, J., John, A., Schafer, E., Nyffeler, M., Boretzki, M., & Caraway, T. (2010). Evaluation of non-linear frequency compression for school-age children with moderate to moderately severe hearing loss. Journal of the American Academy of Audiology, 21(10), 618-628.

Wolfe, J., John, A., Schafer, E., Nyffeler, M., Boretzki, M., Caraway, T., & Hudson, M. (2011). Long-term effects of non-linear frequency compression for children with moderate hearing loss. International Journal of Audiology, 50(6), 396-404.

C H A P T E R  E L E V E N

What Do We Know About the Fitting and Daily Life

Usage of Hearing Instruments in Pediatrics?

Christine Jones, Au.D Manuela Feilner, Ph.D.

Abstract

This paper describes a national database to track hearing instrument performance and use by children with hearing loss. A data collection system was developed by Phonak was utilized to analyze hearing instrument fittings from 6,696 pediatric patients over 8 years from 44 sites. The system collected specific data including the initial hearing aid fitting gain and output prescriptions, features enabled and fine-tuning changes over time. The pediatric client datalog was also analyzed to describe hearing aid use time, use conditions, programs activated and user controls manipulated. These pediatric hearing aid usage profiles provide information to help audiologists make data-driven decisions resulting in improved and better hearing aid performance and pediatric patient outcomes.

There are powerful examples in medicine of great advances in care and outcomes being achieved through a dogged and detailed analysis of the current state of care. This continuous evolution of a best practice clinical pathway is a moving target and can only be achieved with a perpetual, high resolution lens by which to track and understand conditions, treatments and outcomes. Such a lens was developed in the early 1960s, with the introduction of the national database for cystic fibrosis. This pool of data was established to track treatments and outcomes for all patients treated in centers across the United States. The ability to aggregate and analyze a multitude of variables, interventions, and outcomes allows clinicians and researchers to connect these dots in meaningful ways and supports the development of best practices. It has resulted in substantial improvements in life expectancy for individuals with cystic fibrosis. At the inception of the database, the average life expectancy for a patient with cystic fibrosis was less than three years of age. Today cystic fibrosis patients are expected to live into their forties (Gewande, 2007).

Until now, we have had no database or archive that allows us to track hearing instrument performance and usage by children with hearing loss. This lack of visibility into the clinical pathway, prescribed hearing instrument parameters and device usage diminishes the audiologist’s potential for data-driven clinical decision making. For example, when a parent of a twelve month-old child with severe congenital sensorineural hearing loss returns to the clinic six months following the child’s initial hearing aid fitting, data logging from the hearing instruments might reveal that the aids are worn on average 4 hours per day. At the same time, the parent is concerned with the child’s progress. The audiologist’s inclination is to advise the parent that more use is likely to result in better hearing performance and outcomes. At this time we do not have published data definitely showing by age what average use per day is or should be. Nor can we connect patterns of auditory exposure to degree of loss and auditory outcomes. Furthermore, we have little insight into specific acoustic properties of the listening environments of children or the hearing instrument performance under these conditions. This information would be highly important in order to better understand how to optimize the hearing instruments for better meet the real-life listening needs of the children.

The project described in this paper is intended to provide that lens into pediatric hearing instrument fitting and usage of hearing instruments in daily life environments to support evidence-based clinical decision making and counseling, and eventually the evolution of more informed clinical pathways to support best outcomes for children with hearing loss.

Tools and Method

“Cuper” is a data collection system created by Phonak (Figure 1). This database warehouses hearing instrument fittings from multiple work stations and aggregates the data for later analysis. Individual clinicians must first consent to share their data by activating the fitting logging in their Target ™ software. The data package is anonymized and made HIPAA compliant on the clinician’s work station before it is transferred to the server. Two types of data are included for each patient. The client fitting log is all information pertaining to the hearing instrument fitting: what is the age of patient, what is the patient’s hearing loss, how many visits were logged, what was gain and output prescribed, what features were enabled and how was the device fine-tuned from the default settings over time. Every mouse click is logged in order to create a picture of the fitting and the clinical journey. A second stream of data, the client datalog, is coming from the hearing instruments through Target™ software. The hearing instruments are constantly accumulating data including use time, use conditions, programs activated, and user controls manipulated.

Figure 1. Illustration of the data flow included in this project. Datalogs that accumulated on pediatric hearing instruments were read into fitting stations, where they were combined with fitting logs that were sent to the central data repository, Cuper. Queries were then developed to facilitate better understand ing of current pediatric hearing instrument fitting and usage patterns.

Once the clinician agrees to participate in fitting logging, s/he must enter a unique identifier code in the software. This engages the process and at pre-set intervals, the anonymized data is streamed to a central server where fittings can be filtered and analyzed. For this report, there were 44 unique sites supplying fitting data. This included 36 pediatric clinics and 6 school-based audiology clinics. 6,696 patients were included in the data analysis over a time period of eight months. Data in this paper are often described as a function of three age ranges: Infants and young children (0-4 years), young school-aged children (5-8 years), and tweens and teens (9-18 years). These age groupings represent the three Junior Modes available in Target.™ The modes are designed to support streamlined, evidence-based fittings and to minimize time spent behind the computer, so clinicians can spend time in direct care and conversation with families.

Patient Profiles

Across the 44 sites, a programming session during the study timeframe triggered a patient’s inclusion in the data set. The distribution of patient ages can be seen in Figure 2. Depending on age, 80-90% of fittings were based on hearing loss that was purely sensorineural in nature. This is consistent with the audiometric findings for adult fittings in Cuper. The prevalence of conductive hearing loss would be somewhat higher than indicated here because this data only accounts for losses fitted with air conduction devices.

Figure 2. Distribution of hearing instrument fittings by age from the Sound Foundations Cuper 2013 project. This data set includes fittings from 44 unique pediatric sites throughout the United States.

Cuper shows that most children are fitted to the Desired Sensation Level (DSL) 5.0a Pediatric fitting formula (Scollie, et. al., 2005) and a majority of adults are fitted to the Phonak Adaptive Digital targets. DSL was prescribed in 83 percent of pediatric hearing instrument fittings. This is not a surprising finding since DSL is the Target™ software default for fittings when the entered birthdate qualifies the patient is 18 years or younger. Since children are often unable to provide adequate feedback about the hearing instrument settings, it is imperative that real ear or simulated real measures are used to verify that the settings maximally support auditory access and comfort. This is most easily done by using an evidence-based, independent prescription that can also be generated in the real ear system software. Since it is based on data describing speech sensation levels associated with comfortable listening levels, the DSL method aligns well to the goal of pediatric amplification supporting speech and language development. The Adaptive Phonak Digital Formula was chosen in 15 percent of pediatric fittings in general and 19 percent of teen fittings. It is unclear if clinicians are verifying settings with speech mapping to assess audibility and comfort. Of the adults fitted at the pediatric centers included in this study, 50 percent were fitted with Phonak Digital Formula. National Acoustics Lab Non-Linear Fitting procedure (NAL-NL1; Keidser, 2011) was applied in 26 percent of adult fittings.

Use of Hearing Instruments

While using an audibility-based prescriptive method is an important first step in providing adequate auditory exposure, the amount of time that the instruments are in use and the performance of those instruments in typical pediatric environments are equally critical factors for successful communication. The data loggs collected from the hearing instruments when in real life situations give us specific insight into how children wear the devices. The data logs are downloaded into Target™ software each time an aid is hooked up for re-programming. These logs are embedded in the fitting sessions and sent to the Cuper database, allowing us to understand hearing instrument use for different listening environments in the context of age, hearing loss and device parameters. The initial review of the data revealed that children were using their instruments for approximately four to five hours per day depending on age. This seemed low compared to our current understanding of hearing aid use. For example, Walker et. al. (2012) surveyed parents about hearing instrument use in children 8 months to 8 years old. In this study, parents reported an average of 10.8 hours of use per day during the week. Data logs from the hearing instruments worn by these children documented an average of 8.2 hours of use per day. The Cuper data was reanalyzed without the logs from patients who were essentially “non-users.”

Figure 3. Percentage of devices by age which were not in routine use. Routine use is defined as more than 30 minutes of average use time per day.

Figure 4. Average use time by age for normal users and non-users of hearing instruments. Children use hearing instruments about 5-7 hours per day on average, less than what is typical for adult and senior users.

Figure 5. Distribution of children as a function of average hearing instrument use time. Only 33 percent of children logged more than eight hours of average hearing instrument use time per day.

By age range, the percentage of “non-users,” defined as children who presented with less than 30 minutes of hearing aid use per day, can be found in Figure 3. The spike in teens rejecting the use of technology when academic rigors are typically increasing and academic performance has the strongest impact on future academic and career choices is concerning. Excluding non-users, the remaining children aid users, wore devices an average of 6.1 hours per day. This is still somewhat less than described by Walker et. al. The use time for infants and toddlers averaged 5.5 hours per day, slightly less than school – aged children and teens who accumulated almost 7 hours per day on average (Figure 4). By comparison, adults logs showed an average of use time 9 hours per day. Only 33 percent of children in our sample wore hearing instruments for more than 8 hours per day (Figure 5). The relatively light pediatric hearing instrument usage is somewhat concerning and certainly poses a challenge to pediatric fitters and manufacturers alike. In order to ensure best outcomes, we need to understand how use patterns correlate with speech and language development, academic success, and social and communicative ease. If our assumption that more is better proves true, then we now need to understand what are the barriers to more use and how can we overcome them.

Application of Styles and Features

There are a multiple factors that influence the level of technology selected for children beyond the family budget. Many children in the United States with hearing impairment qualify for Medicaid, which dictates by state the type and cost of hearing aids covered. Twenty states have provisions insurance coverage for pediatric hearing instruments and these mandates include varying amounts of coverage or reimbursement that also dictate or affect the device selected. (State Insurance Mandates, 2014). The devices that were available in the study market comprised three levels of technology. Table 1 summarizes the technologies typically included in each product segment at the time of this analysis. In our sample 63 percent of children under age nineteen were fitted with standard level products. This is exactly what was reported three years ago by Jones & Launer (2010). Advanced level devices were dispensed to teens more often than younger children. Advanced products comprised 20% of devices dispensed to teens. Still, children, including teens, are rarely fitted with premium technology, with these products comprising barely 2 percent of pediatric fittings. These product selections reveal that while all children in this sample had access to a directional microphone, non-linear frequency compression and a basic automatic, the use time were typically not provided ear to ear streaming (called DuoPhone) for improved understanding on phones, a base program for music to improve music appreciation or steerable directionality (ZoomControl, Auto ZoomControl).

As would be expected, most children are fitted with behind-the-ear (BTE) style devices (Figure 6). Almost 17% of teens were fitted with RIC or custom products. While this is far lower than what is seen in the adult market, it is up from only 6% three years ago (Jones & Launer, 2010). 13% of all pediatric fittings included a non-traditional BTE coupling including a slim tube, external receiver or custom shell. Non-traditional fittings jump to 26% of the solutions fitted to 9-18 year olds. By comparison, these coupling solutions comprise 45% of adult fittings.

Figure 6. Hearing aid fitting of device style by age group.

Table 1. Typical feature allocation across the three technology levels represented in data set.

When evaluating the use of features, it is important to understand where overt decisions were made versus a passive acceptance of Junior defaults. Table 2 depicts the default settings by age, showing that controls are disabled until nine years of age and infants and young children are given a single FM readycalm situation program. At age nine, the controls are reactivated and the start-up program transitions to SoundFlow, the automatic mode. Surprising to the authors, clinicians frequently changed these default settings. For all ages, the program toggle was activated more than half of the time (Figure 7), indicating that even very young children are provided with multiple program options.

Table 2. Phonak TargetTM Junior Mode default Settings.

Figure 7. Percentage of time as a function of age that the program toggle was enabled in pediatric hearing instrument fittings.

While there is some evidence (Ricketts, 2010) that directional microphone programs might have more benefit than detriment for children, there is not conclusive evidence that automatic program switching can improve listening comfort and comprehension for children. However, these data show that SoundFlow, the Phonak multi-base automatic program, was the most frequently chosen start-up program for children (Figure 8). This finding reveals that clinicians believe that a single program does not sufficiently meet children’s listening needs and that an automatic will select the optimal program a given for situation more reliably than a child will. While, according to Cuper data, an automatic is used by 90% percent of adult hearing aid users, it is less well understood how well the behavior of these devices meets the needs of the typical pediatric use cases and listening intentions of children.

In order to better understand the behavior and success of automatic program selection for students at school, one of the authors has begun a project to record the environments encountered by children throughout the day and track those environments in a time-locked way while simultaneously logging the behavior of the automatic functionality and a recording a child’s listening intent.

Figure 8. Distribution of start-up programs chosen in pediatric hear-

The premium tier of the current Phonak automatic classifier incorporates 5 base programs and the system can define the scene as any one of these environments: calm, noise, speech in noise, speech in loud noise, or music. The system can also blend the characteristics of these programs when the environment warrants such a combination. In order to best understand if there are opportunities to optimize the behaviors of the system for children, we have undertaken a project to analyze the output of the SoundFlow system for children over the course of the school day. In this project, an audio recorder is time-locked with the behavior of the actuators in the classifier. Later interviews with students allowed the investigators to further understand the students’ listening intent and judge the performance of the devices in this environment. This comprehensive approach to gaining authentic understanding of pediatric listening environments and pediatric listening intent as it relates to classifier behavior will allow us to further optimize this feature, already popular among pediatric audiologists, to meet the specific needs of children. Additionally, it will help us to better understand the characteristics of the listening environments children encounter in their daily life and to better counsel the care takers involved about the listening needs of the children.

Other Phonak advanced features can be tracked through Cuper such as non-linear frequency compression, known as Sound Recover. Cuper allows us to study how and when SoundRecover is engaged. The data show that depending on age, SoundRecover was activated in 65-70 percent of children. This rate is similar to usage in the adult population and less than what is seen in the elderly population (Figure 9). Since SoundRecover was developed in response to the literature revealing that the bandwidth of hearing instruments may not be sufficient for optimal speech and language development in children (Stelmachowicz, 2004; Pittman, 2008), this finding is somewhat surprising as clinicians tend to disable it for milder hearing losses. There is some support from Wolfe (submitted, 2013) that SoundRecover may results in improved perception of /s/ for individuals with mild hearing loss, however, the clinical reticence to apply it in these cases highlights a need for additional evidence in this area.

Figure 9. Percentage of patients for whom SoundRecover is activated, partially activated, and deactivated.

WorkFlow

The analysis of Cuper data gives us specific insight into the workflow of the audiologist and the clinical pathway and management of children with hearing loss. Both for pediatrics and adults, first fittings take about 14 minutes to complete in Target™ software. Assuming most appointments are booked for an hour, this means that there is a substantial amount of time remaining for counseling, real ear verification or further testing in the booth. Duration of follow up programming sessions, consistent with adult follow ups, average 10 minutes of programming time. We can also see that fewer than 10% of fittings included an entered real-ear-to-coupler difference (RECD). However, this may be because clinicians are aware than an age-based average RECD is automatically applied by the software whenever a child’s age is into the client profile. To improve the accuracy of the fitting, the average values can be overwritten by entering the child’s own measured RECD. In the 0-4 age range, a measured valued was entered 7% of the time. For young school-aged children, 5% of fittings included a measured value and for teens, 3% of fittings were based on an entered RECD. Since measured values provide a much more accurate fitting (Bagatto, et.al., 2002), it is presumed that clinicians are measuring this value more often than is represented by Cuper, but perhaps making a fine tuning adjustments in the software to match targets in the real ear system, rather than improving the first fit with the measured values. The decrease in measured RECD with age is consistent with the assumption that as a child becomes more cooperative with age, the clinician will transition from simulating real-ear measure with the RECD to performing actual real ear measures, rendering RECD measurement unnecessary. This disconnect between fittings software and real ear measurement equipment presents an opportunity to streamline and improve the pediatric fitting process.

Conclusions

The Cuper database provides us with a window into pediatric fittings and hearing instrument usage in daily life environments. By studying the behaviors of fitters and users, we can gain specific insights about what is well accepted and working well and where there exists opportunities for further improvement. For example, in this sample we observed that there are age and hearing loss specific use patterns in some cases that less than expected. This finding challenges us to determine what the barriers are to full time use and amend our counseling, change our fitting parameters or search for a less intrusive design to provide more consistent amplification for children. A next step might be to determine what factors or parameters separate the full time users from the light users. This would allow us to start understanding the factors that result in successful hearing instrument use. Cuper also allows us to see trends such as a greater adoption of non-traditional styles in the teen population. If the better cosmetics of the RIC and custom products improve compliance, then these trends could be important to improving outcomes.

SoundRecover remains a very successful strategy especially for moderate to profound hearing losses is applied in most fittings for these hearing instrument categories. However, we saw a trend of decreasing SoundRecover use, particularly with mild hearing loss. This spurs us to further our investigation of the benefits and limitations of this technology and continue to innovate in this area to develop the solutions that allow children to live a life without limits. To improve the power of this data collection system, we need to connect these findings to outcomes measured in clinical practice and daily life. This is a critical next step in applying this data to strengthen our evidence-based approach to pediatric hearing loss management.

Acknowledgments

The authors would like to express sincere gratitude to the Pediatric Centers that made this study possible by collecting and sharing their data. We would also like to acknowledge the instrumental Cuper support from Daniel Meier, Stefan Launer, and Katarina Mathes. Finally, thanks to the entire Phonak US pediatric team including Dane Bowers, Lisa Dyre, Shannon Motsett, Megan Quilter, Stacey Rich, Lindsey Roberts, Dawn Ruley, Miranda Weidle and Dave Wessell who go above and beyond every day.

References

Bagatto, M.P., Scollie, S.D., Seewald, R.C., Moodie, K.S., Hoover, B. (2002). Real-ear-to-coupler difference predictions as a function of age for two coupling procedures. Journal of the American Academy of Audiology, 13(8), 407-415.

Gewande, A. (2007). Better. New York, New York: Metropolitan Books.

Jones, C. & Launer, S. (2010). Pediatric Fittings in 2010: The Sound Foundations Cuper Project. In R.C. Seewald & J.M.Bamford (Eds.). A Sound Foundation through Early Amplification 2010: Proceedings of the Fifth International Conference. Stäfa, Switzerland: Phonak AG, (pp. 187–192).

Keidser, G., Dillon, H.R., Flax, M., et. al., (2011). The NAL-NL2 prescription procedure. Audiology Research, 1(1s), e24.

Pittman, A. (2008). Short term word-learning rate in children with normal hearing and children with hearing loss in limited and extended high frequency bandwidths. Journal of Speech Language and Hearing Research, 51, 785-797.

Ricketts, T., Picou, E.M., Galster, J.A., Federman, J., and Sladen, D. (2010). Potential for directional hearing aid benefit in classrooms: Field data. In R.C. Seewald & J.M. Bamford (Eds.). A Sound Foundation through Early Amplification 2010: Proceedings of the Fifth International Conference. Stäfa, Switzerland: Phonak AG.

Scollie, S., Seewald, R, Cornelisse, L, et,al. (2005). The Desired Sensation Level multistage input/output algorithm. Trends in Amplification, 9, 159-197.

State insurance mandates for hearing aids. (2014). Retrieved January 31, 2014, from http://www.asha. org/advocacy/state/issues/ha_reimbursement/

Stelmachowicz, P., Pittman, A., Hoover, B., et.al. (2004). The importance of high frequency audibility in the development of speech and language for children with hearing loss. Archives of Otolaryngology-Head & Neck Surgery. 130(5), 556-562.

Walker, E. A., Spratford, M., Moeller, M.P., Oleson, J., Ou, H., Roush, P., Jacobs, S. (2013). Predictors of hearing aid use time in children with mild-to-severe hearing loss. Journal of Language, Speech, and Hearing Services in Schools 44(1), 73-88

Wolfe, J, et al. (submitted 2013). Evaluation of wideband frequency responses and non-linear frequency compression for children with mild hearing loss.

C H A P T E R  T W E L V E

The Impact of Multiple Technologies on Families:

Considerations in Real Life

Janet DesGeorges

Abstract

This article seeks to articulate the complexity and use of technology in today’s world, the parent emotions attached to the experience, and the strategies that audiologists can use to support families as they move between the audiology sound booth and the ‘real world’. There have been many studies looking at the use and monitoring by parents of hearing aids in children. This article is written from the parent perspective on that topic. For those of us who provide parent-to-parent support and/or professional-to-parent support, we are the sacred holders of two ideas for families to help them through their day the miracle of technology and the limitations of technology.

As a parent of a child who is hard of hearing, I seemingly have a passion for describing to pediatric audiologists the limitations of technology in the ‘real world’… I can remember one day leaving the audiologist’s office with my 8 year old daughter who had just been fit with the latest digital hearing aids at the time. We spent over an hour of careful fitting and programming, with my daughter assuring our provider that everything sounded fine. I was experiencing new hope that this pair of hearing aids might deliver new sounds and new access opportunities. As we walked out to the car, my daughter said, “Can I take these out now? I hate them.” I wasn’t prepared for that. We made it home somehow, and through the adjustment period.

As I began to explore this topic on the limitations of technology, I felt it only fair to write about this subject in context to what myself and other parents have also used to describe the use of supports as the ‘miracle of technology’. Over the years, with many experiences of raising a child who is deaf/hard of hearing, I can ascribe to the fact that we have had both ‘miracle moments’ as well as the frustrations and limitations of technology available to us. We have had moments where my daughter responded to new hearing aids with directional microphone technology, “I can hear in really loud places for the first time!” We have had moments of discouragement knowing that while the technology for something existed, we couldn’t afford it. (i.e., water resistant hearing aids so swimming at the pool would create communication accessibility) We have also learned over the years that the sum experience of being deaf or hard of hearing cannot be defined or described only as what piece of technology my daughter uses. As we look at what led to her success in emerging adulthood – from advocating for a successful education, ensuring a good sense of self-esteem and pride in her Deafness, embracing her communication choices in speaking, listening, use of sign language, and different technologies – we have come to realize it wasn’t just one thing that led to success. It was being supported in the choices we made at different seasons of life for different reasons – understanding that the complexity of the deaf experience can never be summed up in one simple solution – such as brand new state of the art pink hearing aids….and ultimately, supporting the choices our own daughter now embraces in terms of technology and communication access. We know she will still face challenges in her life – but we also celebrate her success as a beautiful human being now that is a miracle!

Unlike any time in history, advancements are being made in terms of hearing technologies including the vast array of programmable digital hearing aids, cochlear implants, FM systems, streaming technologies and Bluetooth, etc. The availability and opportunity of ever expanding technology options has far exceeded the old days when a plain, beige, analog hearing aid was the ‘offer on the table’ in terms of technology solutions for young children with hearing loss.

What are the considerations about how all these new technology options impact families? Studies on hearing aid use and the acknowledgment of the multi-faceted challenges that families face suggest they may benefit from working in partnership with audiologists who have audiologic counseling strategies, to promote consistent device use across a variety of daily situations. (Moeller, Hoover, Peterson, & Stelmachowicz, 2009) Professionals can hone their skills to be sensitive to the possibility of overwhelming families with all the choices laid before them, and considering each family’s unique needs.

Or is it possible that audiologists simply recommend “the latest and greatest” in a broadly sweeping way as opposed to individualizing such recommendations? As technology is opening doors for children with hearing loss like never before, there are still day to day, real life considerations: age of the child, culture, cost, and the capacity of the average user to understand and utilize the current technology available. Additionally, technology in and of itself is not the only consideration towards successfully raising a child who is deaf or hard of hearing that needs recognition in the parenting experience, and by the audiologist who support them.

The Limitations of Technology and the Miracles of Technology

One of my favorite quotes comes from Stephanie Olson, an adult user of a cochlear implant who says, “My miracle only lasts as long as my battery supply.” When terms such as the ‘the miracle of technology’ are used to describe today’s generation of children who are deaf and hard of hearing, there is no denying that the quality of technology and hearing aid fitting in infants and young children has indeed come a long way. Comprehensive evidence-based guidance for clinicians with regard to maximizing modern hearing aid amplification outcomes for children now exists (Ching, 2012) Parents can be overwhelmed with the bombardment of branding and marketing of new products that promise everything they could possibly need for their child. It is particularly important for parents as they begin to move from identification and acceptance of hearing loss for their child, to communication and technology choices, that there will be clarity and realistic expectations of what technology may and may not be able to offer.

Considerations in Real Life

Realistic expectations and understanding the limitations of technology is not the only thing that parents must process. There are many factors when considering new technology and questions that should be considered. Some of these factors include:

• Parental Acceptance and Support – if there is resistance to use of technology by a family, is it the device itself or the feelings and emotions associated with its use?

• Cost – deciding what to buy, when/ waiting on newer technology, hidden costs.

• Understanding and using technology – will a parent be able to use complicated features they have paid for, once home and in day to day usage?

• Other health problems impacting the child – will success with technology be impacted when a child has additional health care needs and/or disabilities?

• Appropriate age range of products – which features benefit children at what age range?

• Short term use when waiting on next technologies – when is it time to invest in new technology and/or wait until next year’s version comes out?

• Technology in different settings – what is the most advantageous and useful features that a particular child in their unique setting might need?

How Audiologists Can Help: Relationship

Building

Every child and family is unique. It is important for audiologists to ensure that they are supporting the family’s individualized priorities, capabilities, and capacity when discussing new technology options and/or consistent use of currently owned products. In order to have a clear understanding of these things, a relationship of trust must be established. (Stonestreet, Johnston & Action, 1991) For parents, they need to feel safe in order to talk about what is and isn’t working with their professional partner and a feeling that they will not be judged for what they might perceive as ‘failure’.

Assumptions should not be made about what a parent can or cannot do. As an example of this, a clinician may label a parent ‘non-compliant with treatment recommendations’ when there is a realization that hearing aid use is not being used consistently. Upon further dialogue, and through the use of open ended questioning, for example, it may be found that particular setting-specific, child-temperament, or activity-related challenges are occurring, not the parent’s lack of follow through in keeping the hearing aids on a young child. Parents often report that things like riding in a car/car seat, loud restaurants, outdoor conditions (windy, wet, hot), and mealtimes are challenging for consistent use of hearing aids. When a child is fussy, tired, sick, mad/tantruming – these are realities in families lives. (Moeller, Hoover, Peterson, & Stelmachowicz, 2009). When families can talk about these things in a safe setting, strategies can be employed to help ensure that consistent use of technology is maximized.

Families may have emotional triggers regarding the use of technology. These can include both ends of the spectrum – unrealistic expectations (“this device will ‘fix’ the hearing loss”) to a belief that their child doesn’t need the technology (“my child can hear just fine without it”) In order for an audiologist to challenge these assumptions, the audiologist needs to take the time to ensure that families have the knowledge and understanding of the technology itself, with realistic expectations about what a particular hearing aid can or cannot do. Parental acceptance of the hearing loss is also a process for families. Parents can greatly benefit from parent-to-parent support in processing the impact of hearing loss on their child, and their choices in the journey. On reflection of the early intervention years, families rank parent-to-parent support as one of the strongest measures of family support (Jackson, 2009).

How Audiologists Can Help: Encourage

Family Involvement

Audiologists can support families by encouraging them to actively engage in advocacy out in the real world. They can:

• Partner with families in the educational setting – discussing technology linkages between the home and in the classroom (i.e., will the child’s personal hearing aid be compatible with a school purchased FM system?).

• Help families to understand the impact of background noise on speech recognition and hearing aid performance.

• Lend expertise as parents prepare for Educational (IEP) meetings with supporting documentation and testing results.

• Recommend testing that looks at functional hearing in real life settings such as the Functional Listening Evaluation (Johnson and Von Almen, 1997).

• Review student needs in the school based setting.

• Work collaboratively with school personnel.

The Story of Anthony

Lisa and Brian’s son, Anthony, is a middle school student who is hard of hearing with bilateral hearing aids. When Anthony joined the wrestling team, he advocated for his accessibility needs during wrestling matches. Anthony wore wrestling head gear during the meets which limited his access to some of his auditory surroundings, along with the noise in the gymnasium. Accommodations such as the referee using a hand signal when blowing the whistle at the start of a match were utilized, as well as educating Anthony’s coach on some strategies about how to communicate effectively in those settings when the use of technology had its limitations. (i.e. the coach demonstrating the needed move from the sideline instead of yelling the move from the sidelines). It wasn’t until after a match one night, as the family sat around the kitchen table reviewing a video that Lisa had taken from the stands that an ‘aha’ moment occurred – in different ways to different members of his family.

As the family watched the video, Anthony asked, while listening to the audio portion of the recording, “Were people cheering me on? Who is that person I hear?” Lisa replied, “Yes, we were all cheering you on. That’s me yelling from the stands”. “And that cheer?” he asked. “That is your Grandfather” she replied. “And that one?” he asked. She answered, “That was a woman behind me cheering you on. I don’t know who she was.”

For the first time, Anthony realized that there were people cheering for him during that meet. For his parents and siblings, it had never occurred to them that their support, encouragement, energy, and effort at attending the sporting events for their son may not have been fully realized by him due to the limitations of his technology in that setting. Anthony’s sisters, who in their day to day lives had gotten used to ‘how well he does with hearing aids’ were awakened to the idea that something so simple, and yet so important in a young athlete’s life cheering from the stands – may have escaped their brother’s notice.

While today’s technology has advanced and provides access to young children who are deaf and hard of hearing, the limitations of technology can impact a child in ways we underestimate. As quoted from her article, A Note to the Coach by L. Seaver (2005) “Although my child cannot hear you at the plate...on the mat... or from the field...please don’t stop yelling for him! Don’t let a player’s deafness or hearing loss stop you from cheering him or her on. Show that you care, and know that you are making an impact that will affect this kid positively during the game, during the rest of the school day, and one that will even be felt and recalled positively all his or her life.” Hearing a parent’s cheer from the stand is just a small example of the missed moments that no amount of technology will ever ‘cure’. To understand this as a parent opens up the mind to explore other ways to get information in the world to children who are deaf and hard of hearing. It may be the use of sign language, or taping the cheering to hear later on, or some other means. If missing out on the cheering section during a sporting event is impactful, then considering accessibility beyond the use of technology warrants a parent’s consideration, as well as the professionals who are supporting them.

Conclusion

Today’s generation of children who are deaf and hard of hearing have unique and unprecedented opportunities to benefit from the miracle of technology. And yet, it is incumbent upon parents and professionals alike to also take into consideration the limits of current technology, and to be open to ensuring appropriate communication access beyond technological solutions. These two truths can co-exist when families are given appropriate support from the professionals who serve them. And in the words of Albert Einstein, “There are only two ways to live your life. One is as though nothing is a miracle. The other is as though everything is a miracle.”

References

Ching, T.Y.C. (2012). Hearing aids for children. In Evidence-Based Practice in Audiology—Evaluating Interventions for Children and Adults With Hearing Impairment, Wong. L, & Hickson, L. (Eds.). San Diego: Plural Publishing (pp 93-118).

Jackson, C. W. (2009). Family support and resources for parents of children who are deaf or hard of hearing. Jacksonville: Florida State University. https://www.coloradogives.org/CoHandsVoices/programs

Johnson, C., & Von Almen, P. (1997). Functional Listening Evaluation. In C.D. Johnson, P.V. Benson, & J. B. Seaton, Educational Audiology Handbook, (pp. 336-339). San Diego, CA: Singular Press.

Moeller, M., Hoover B.,Peterson B., Stelmachowicz P., (2009) Consistency of Hearing Aid Use in Infants with Early-Identified Hearing Loss. American Journal of Audiology, 18, 14-23.

Seaver, L. (2005). A Note to the Coach. Hands & Voices, Boulder, CO. http://www.handsandvoices.org/articles/fam_perspectives/coach.htm.

Stonestreet, R.H., Johnston, R.G. & Action, S.J. (1991). Guidelines for real partnership with parents. Infant-Toddler Intervention: The Trans disciplinary Journal, 1:1.

S E C T I O N  IV

Challenges in Pediatric Service Delivery

Session Chair: Richard Seewald (CAN)

C H A P T E R  T H I R T E E N

Bimodal Hearing for Children:

Effect of Frequency Region

and Acoustic Bandwidth

René H. Gifford, Ph.D. Michelle Simha, B.S. Sterling W. Sheffield, Au.D.

Abstract

Speech recognition with cochlear implants (CIs) is limited by poor spectral resolution and loss of temporal fine structure associated with envelope-based signal processing strategies. Bimodal hearing, with a CI in one ear and hearing aid in the opposite ear, may afford greater spectral resolution and temporal fine structure cues via acoustic hearing in the lowto-mid-frequency region of the non-CI ear. The present study evaluated 20 children with normal hearing in a simulated CI listening task in an attempt to determine the acoustic bandwidth needed for optimal bimodal benefit. Significant bimodal benefit was found with 250 Hz of acoustic hearing in the “non-CI” ear; no increase in bimodal benefit was noted with the addition of acoustic hearing beyond 750 Hz.

Cochlear implants (CIs) provide substantial communicative benefit such that average auditory only word recognition is now in the range of 60 to 70% for both adult and pediatric recipients (Holden et al., 2013; Gifford et al., 2014; Davidson et al., 2010). Speech recognition is limited by poor spectral resolution and loss of temporal fine structure associated with envelope-based signal processing strategies. Bimodal hearing may afford greater spectral resolution and temporal fine structure cues via acoustic hearing in the lowto-mid-frequency region of the non-CI ear. This holds great promise for CI users as bimodal hearing is more prevalent than ever. Indeed, approximately 60 percent of modern-day, adult CI recipients have aidable acoustic hearing in the non-implanted ear with audiometric thresholds up to 80-85 dB HL at 250 Hz (Dorman & Gifford, 2010).

Numerous studies have demonstrated bimodal benefit in quiet and in noise for CI recipients and in vocoderbased simulations with normal-hearing listeners (Dunn et al. 2005; Kong et al. 2005; Kong & Carolyn 2007; Chang et al. 2006; Ching et al. 2006; Mok et al. 2006; Dorman et al. 2008; Brown & Bacon 2009; Zhang et al. 2010). In fact, very little acoustic hearing is required in order to derive benefit from bimodal hearing. Specifically, research has demonstrated significant bimodal benefit with acoustic bandwidths as narrow as 125 to 250 Hz (e.g., Brown & Bacon, 2010; Zhang et al., 2010; Sheffield & Gifford, 2014; Sheffield & Zeng, 2012). Maximum bimodal benefit has been documented for acoustic bandwidths up to 500 Hz in noise for adult listeners (Sheffield & Gifford, 2014).

All previous studies examining the acoustic bandwidth required for bimodal benefit have been conducted with adult CI recipients. Comparable data for pediatric bimodal listeners could provide diagnostically relevant information to aid clinical decision making regarding bimodal or bilateral CI candidacy. Identifying the optimal hearing condition is especially crucial for children who are developing speech and language and are more reliant on bottom-up processing cues than adults (Snedeker & Trueswell, 2004). Indeed, there have been a number of studies reporting that children with normal hearing and hearing aids require broader acoustic benefit than hearing-matched adults for rapid word learning and speech understanding (Stelmachowicz et al., 2004, 2007; Pitmann et al., 2005).

This brief report describes our ongoing research efforts aimed at defining the acoustic bandwidth needed for optimal bimodal benefit for pediatric CI recipients. Our primary hypothesis was that children will require wider acoustic bandwidth for maximum bimodal benefit than has been observed with adult bimodal listeners.

Experimental Details

Twenty children with normal hearing were recruited for participation. Participants ranged in age from 6 to 12 years with a mean of 9.2 years. Prior to testing, hearing was screened at 15 dB HL from 250 through 8000 Hz and tympanometry was completed to rule out middle ear effusion.

In order to simulate CI listening, a 15-channel vocoder was used (Litvak et al., 2007). Sentence recognition for the BabyBio corpus (Spahr et al., 2014) was completed at an individually determined signal-to-noise ratio (SNR). The SNR was chosen to yield approximately 50% correct in the simulated CI only condition. The mean SNR was 6.7 dB with a range of 2 to 15 dB. Acoustic hearing in the opposite ear was low-pass filtered with cutoffs of 250, 500, 750, 1000, and 1500 Hz. Bimodal benefit was defined as the difference in performance between the CI alone and CI plus acoustic (bimodal) conditions.

Results and Discussion

Figure 1 shows the bimodal benefit, in percentage points, for each of the bimodal conditions tested. Mean bimodal benefit increased with acoustic bandwidth such that there was a significant effect of condition [F(1, 18) = 201.9, p < 0.0001). Post hoc testing (Holm-Sidak) revealed that the bimodal 250 Hz condition was significantly better than the CI alone condition (t = 10.8, p < 0.001), and the maximum score is achieved in the bimodal 750 Hz condition (t = 5.3, p < 0.001).

Figure 1. Mean bimodal benefit in percentage points for each of the bimodal conditions tested. Mean bimodal benefit clearly increases with bandwidth. The bimodal 250 Hz condition is significantly better than the CI alone condition, while the maximum score was obtained in the bimodal 750 Hz condition.

Though the trends in the current dataset are similar to those for adults (Zhang et al., 2010; Sheffield & Gifford, 2014), adult CI listeners exhibit no further increases in bimodal performance beyond approximately 250 Hz. These data are consistent with our hypotheses that children would require a wider acoustic bandwidth than adults for maximum bimodal benefit and that bimodal benefit would increase with increasing bandwidth.

Summary

Significant bimodal benefit was observed with just 250 Hz of acoustic hearing in the “non-CI” ear for children listening to CI simulations. No significant increases in bimodal benefit were observed for the addition of acoustic hearing beyond the 750-Hz filter. This differs from what was seen in adults who reach a bimodal asymptote in the 250to 500-Hz range (Zhang et al., 2010; Sheffield & Gifford, 2014). The current data suggest that 1) pediatric CI recipients may benefit from minimal acoustic hearing (<250 Hz) in the non-implanted ear, 2) bimodal benefit increases with increasing bandwidth up to at least <750 Hz, and 3) pediatric CI recipients may be able to make use of wider bandwidths of residual hearing than adults. Knowledge of the effect of acoustic bandwidth on bimodal benefit may help with clinical decision making regarding a second CI or bimodal hearing for optimal benefit. Ongoing projects are currently examining this research question with pediatric CI recipients.

References

Brown, C. A. & Bacon, S. P. (2010). Fundamental frequency and speech intelligibility in background noise. Hearing Research, 266(1-2), 52-59.

Chang, J., Bai, J., & Zeng, F. G. (2006). Unintelligible low-frequency sound enhances simulated cochlear-implant speech recognition in noise. IEEE Transactions of Biomedical Engineering, 53, 2598–2601.

Ching, T., Incerti, P., Hill, M., et al. (2006). An overview of binaural advantages for children and adults who use binaural/bimodal devices. Audiology & Neurotology, 11, S1, 6–11.

Davidson, L. S., Geers, A. E., & Brenner, C. (2010). Cochlear implant characteristics and speech perception skills of adolescents with long-term device use. Otologic Neurotology. 31(8), 1310-1314.

Dorman, M. F., Gifford, R., Spahr, A., et al. (2008). The benefits of combining acoustic and electric stimulation for the recognition of speech, voice and melodies. Audiology and Neurotology, 13, 105–112.

Dorman, M., & Gifford, R. (2010). Combining acoustic and electric stimulation in the service of speech recognition. International Journal of Audiology, 49, 912-919.

Dunn, C. C., Tyler, R. S., & Witt, S. A. (2005). Benefit of wearing a hearing aid on the unimplanted ear in adult users of a cochlear implant. Journal of Speech, Language, and Hearing Research, 48, 668–680.

Gifford, R.H., Dorman, M.F., Sheffield, S.W., Teece, K., & Olund, A.P. (2014). Availability of binaural cues for bilateral implant recipients and bimodal listeners with and without preserved hearing in the implanted ear. Audiology and Neurotology, 19(1), 57-71.

Holden, L. K., Finley, C. C., Firszt, J. B., Holden, T. A., Brenner, C., Potts, L. G., Gotter, B. D., Vanderhoof, S. S., Mispagel, K., Heydebrand, G., Skinner, M. W. (2013). Factors affecting open-set word recognition in adults with cochlear implants. Ear and Hearing, 34(3), 342-360.

Kong, Y. Y., Stickney, G. S., & Zeng, F. G. (2005). Speech and melody recognition in binaurally combined acoustic and electric hearing. Journal of the Acoustical Society of America, 117, 1351–1361.

Kong, Y. Y., & Carlyon, R. P. (2007). Improved speech recognition in noise in simulated binaurally combined acoustic and electric stimulation. Journal of the Acoustical Society of America, 121, 3717–3727.

Litvak, L. M., Spahr, A. J., Saoji, A. A., & Fridman, G. Y. (2007). Relationship between perception of spectral ripple and speech recognition in cochlear implant and vocoder listeners. Journal of the Acoustical Society of America, 122(2), 982-991.

Mok, M., Grayden, D., Dowell, R., et al. (2006). Speech perception for adults who use hearing aids in conjunction with cochlear implants in opposite ears. Journal of Speech, Language, and Hearing Research, 49, 338–351.

Pittman, A. L., Lewis, D. E., Hoover, B. M., & Stelmachowicz, P. G. (2005). Rapid word-learning in normal-hearing and hearing-impaired children: effects of age, receptive vocabulary, and high-frequency amplification. Ear and Hearing, 26(6), 619-629.

Sheffield, S. W. & Gifford, R. H. (2014). The benefits of bimodal hearing: Effect of frequency region and acoustic bandwidth. Audiology & Neurotology, 19, 151-163.

Sheffield, B.M., Zeng, F.G. (2012). The relative phonetic contributions of a cochlear implant and residual acoustic hearing to bimodal speech perception. Journal of the Acoustical Society of America, 131(1), 518-530.

Snedeker, J. & Trueswell, J. C. (2004). The developing constraints on parsing decisions: The role of lexical-biases and referential scenes in child and adult sentence processing. Cognitive Psychology, 49, 238–299.

Spahr, A., Dorman, M., Litvak, L., Cook, S., Loiselle, L., DeJong, M., Hedley-Williams, A., Sunderhaus, L., Hayes, C., & Gifford, R. (2014). Development and validation of the Pediatric AzBio sentence lists. Ear and Hearing, ePub ahead of print.

Stelmachowicz, P.G., Pittman, A.L., Hoover, B.M., Lewis, D.E., Moeller, M.P. (2004). The importance of high-frequency audibility in the speech and language development of children with hearing loss. Archives of Otolaryngology – Head & Neck Surgery, 130(5), 556-562.

Stelmachowicz, P. G., Lewis, D. E., Choi, S., & Hoover, B. (2007). Effect of stimulus bandwidth on auditory skills in normal-hearing and hearing-impaired children. Ear and Hearing, 28(4), 483-94.

Zhang, T., Dorman, M. F., & Spahr, A. J. (2010). Information from the voice fundamental frequency (F0) accounts for the majority of the benefit when acoustic stimulation is added to electric stimulation. Ear and Hearing, 31(1), 63-69.

C H A P T E R  F O U R T E E N

Results in Individuals with Asymmetric Hearing

Loss Using a Cochlear Implant and a Hearing Aid

Jill B. Firszt, Ph.D. Ruth M. Reeder, M.A. Laura K. Holden, Au.D. Noël Y. Dwyer, Au.D. Jamie H. Cadieux, Au.D.

Abstract

Traditionally, cochlear implant (CI) recipients have had bilateral moderate-to-profound, severe, or profound hearing loss. Individuals with asymmetric hearing loss, who have at least a moderate-to-profound hearing loss in one ear but better hearing in the opposite ear, have not routinely been implanted because of their better hearing ear. Often these individuals do not benefit from amplification in the poorer hearing ear and have become unilateral listeners. Listening with just one ear presents many challenges in everyday communication. The overall goal of our research is to evaluate behavioral outcomes in individuals who have asymmetric hearing loss and receive a CI in the poorer hearing ear. To date, the findings explore a current clinical question in adults and children; that is, whether CI candidacy criteria should be expanded in cases of asymmetric hearing loss to include treatment of the poorer ear. In this chapter, we summarize three recent studies in adults and children with asymmetric hearing loss using measures of speech recognition, localization and hearing handicap.

Sound stimulation is necessary for normal development and function of the central auditory system. In animal models and humans, hearing loss affects the representation of sound to the central auditory system (Kral, 2013). The consequences of hearing loss depend, in part, on a combination of whether the loss is bilateral or unilateral and whether the degree is total or partial. In animals with congenital bilateral severe-to-profound hearing loss (SPHL), abnormalities occur that extend from the auditory nerve (Ryugo, Pongstaporn, Huchton, & Niparko, 1997; Ryugo, Rosenbaum, Kim, Niparko, & Saada, 1998) to the auditory cortex (Kral, Hartmann, Tillein, Heid, & Klinke, 2000). In humans, there are clear functional implications related to outcomes when the hearing loss is congenital, bilateral and severe to profound in degree. Treatment of SPHL with cochlear implantation in one or both ears has been well studied and several factors that are critical to successful outcomes have been identified. For example, age at implantation for children with congenital hearing loss is an important variable that affects communication function; the younger the child is at the time of implantation, the better the results (Nicholas & Geers, 2006, 2007). Likewise in adults, length of deafness is significantly correlated with speech recognition results (Blamey et al., 2013; Holden et al., 2013); the shorter the duration of deafness the better the outcomes.

Less is known, however, about unilateral or partial auditory deprivation. In the visual system in animals, unilateral deprivation early in life resulted in permanent impairment of binocular vision (Hubel & Wiesel, 1970). In the auditory system, animal studies have shown that when hearing loss was bilateral, the neural projections between the two sides of the pathway maintain a balance, although activity was reduced (Silverman & Clopton, 1977). Additionally, there was less effect on binaural interactions compared to monaural deprivation. In the latter case, a greater loss of binaural neural activity and a greater alteration of binaural interactions occurred than with bilateral deprivation.

Unilateral hearing loss (UHL) induces central auditory system reorganization in ways that differ from bilateral hearing loss. Typically stimulation of the intact ear in cases of UHL results in a change to the balance of hemispheric activity in the auditory cortex. Normally, stimulation creates an asymmetric activation pattern where one hemisphere (often the left) shows greater activation than the other hemisphere. With UHL, there is an increase in activity ipsilateral to the intact ear, resulting in symmetric hemispheric patterns rather than asymmetric (Burton, Firszt, Holden, Agato, & Uchanski,2012; Khosla et al., 2003; Maslin, Munro, & El-Deredy, 2013). Changes to the balance of activity are thought to modify binaural interactions and auditory system structures.

Traditionally, cochlear implant (CI) recipients have had moderate-to-profound, severe, or profound hearing loss in both ears. Individuals with asymmetric hearing loss, that is at least moderate-to-profound hearing loss in one ear and better hearing in the other ear, have not routinely been implanted because of their better hearing ear. Often these individuals discontinue amplification in the poorer hearing ear due to lack of benefit. In other words, they become unilateral listeners. Listening with just one ear results in poor speech understanding in noise in self-report studies (McLeod, Upfold, & Taylor, 2008; Wie, Pripp, & Tvete, 2010), the inability to localize sound (Abel, Alberti, Haythornthwaite, & Riko, 1982; Humes, Allen, & Bess, 1980), problems understanding when speech is directed toward the poorer ear (Giolas & Wark, 1967), and increased listening effort (Feuerstein, 1992) even when the better ear has normal hearing. Individuals with asymmetric hearing loss, as described here, are at an even greater disadvantage, because their better hearing ear does not have normal hearing.

Several studies are underway at Washington University School of Medicine in St. Louis and St. Louis Children’s Hospital to study the effects of hearing asymmetry. The overall goal of our research is to evaluate behavioral outcomes in individuals who have asymmetric hearing loss between ears and receive a CI in the poorer hearing ear. The findings to date explore a current clinical question in adults and children, that is, whether CI candidacy criteria should be expanded in cases of asymmetric hearing loss to include treatment of the poorer ear that has at least moderate-to-profound or severe hearing loss. In the following pages, we summarize three recent studies in adults and children with asymmetric hearing loss using measures of speech recognition, localization and hearing handicap.

Study 1: Asymmetric Hearing Loss – Adults

Ten adults with asymmetric hearing loss (one ear meeting CI candidacy criteria and the other ear with better hearing) were evaluated pre-implant and at six months post-implant. Participants were 26 to 82 years of age. Onset of SPHL was postlingual for seven participants and pre/perilingual for three participants. All except one pre/perilingual participant had long-term hearing aid (HA) use in the better hearing ear and all except one postlingual participant had discontinued or never worn a HA in the poorer hearing ear. The test protocol was designed to incorporate measures and conditions that simulated real-life listening challenges (e.g., background noise, varied speaker locations, different loudness levels, and multiple talkers).

Speech recognition measures and presentation levels were as follows: the Consonant-Vowel nucleus-Consonant test (CNC, Peterson & Lehiste, 1962) at 60 dB SPL, the Hearing In Noise Test (HINT, Nilsson, Soli, & Sullivan, 1994) at 60 dB SPL in the presence of four-talker babble (4TB) at a +8 dB signal-to-noise ratio (SNR), TIMIT sentences (Dorman, Spahr, Loizou, Dana, & Schmidt, 2005; King, Firszt, Reeder, Holden, & Strube, 2012; Lamel, Kassel, & Seneff, 1986) at 60 dB SPL with 4TB at a +8 dB SNR, and TIMIT sentences at 50 dB SPL in quiet. For these measures the sentences and noise (when used) were presented from zero degrees azimuth. HINT sentences were also presented in the R-Space laboratory sound system (Compton-Conley, Neuman, Killion, & Levitt, 2004; Revit, Schulein, & Julsrom, 2002) that uses eight loudspeakers surrounding the listener. For this measure restaurant noise was presented at 60 dB SPL from all eight loudspeakers and the sentences were presented from zero degrees azimuth; sentence level was adjusted adaptively based on the participants’ responses to obtain an SNR for 50% accuracy.

Localization was evaluated using 100 monosyllabic words presented pseudo-randomly from a 15 loudspeaker array (10 active and five inactive unbeknownst to the participant) at a roved 60 dB SPL (± 3 dB). The loudspeakers were arranged in a 140 degree arc in front of the participant, each 10 degrees apart. A root mean square (RMS) error was calculated based on participant responses. Additionally, a self-assessment of perceived communication function, the Speech Spatial and Qualities of Hearing Scale (SSQ, Gatehouse & Noble, 2004), was completed at each interval.

Figure 1 shows mean results for the postlingual group and the four fixed-level speech recognition measures. Pre-implant results are shown for the poorer hearing ear (with the participant’s or a clinic HA) in black, the better hearing ear (aided) in white, and the everyday listening condition (HA in the better ear for all participants except one, whose everyday listening condition was HAs in both ears) in gray. Post-implant results are shown for the poorer hearing ear with the CI in black, the better hearing ear (aided) in white, and the bimodal condition (CI plus HA) in gray. For adults with postlingual hearing loss, group mean results indicated significant open-set speech recognition in the implanted ear after six months for measures in quiet and noise. Furthermore, significant improvements in speech recognition and localization (see Figure 6 in Firszt et al., 2012 for localization results) were observed when comparing the 6-month bimodal condition to the pre-implant, everyday listening condition. For sentences at a soft level in quiet and localization the post-implant bimodal condition was significantly better than the better ear HA-alone condition.

Figure 1. Group mean speech recognition scores (CNC words, HINT sentences in noise, TIMIT sentences in noise, and TIMIT sentences in quiet) pre-implant and at 6 month post-implant are shown for the seven postlin¬gual participants. Scores are shown in black for the poorer-hearing ear that was implanted, in white for the better-hearing ear with a HA, and in gray for the participants’ everyday listening condition (bimodal at the postimplant interval). HINT, hearing in noise test; CNC, consonant-vowel nucleus-consonant; HA, hearing aid. (Reprinted with permission from Lippincott Williams and Wilkins/Wolters Kluwer Health: Firszt et al. 2012, Cochlear Implantation in Adults with Asymmetric Hearing Loss, (33)4, p. 526. Promotional and commercial use of the material in print, digital or mobile device format is prohibited without the permission from the publisher Lippincott Williams & Wilkins.)

For adults with prelingual hearing loss, speech recognition was limited in the CI-alone condition for words and sentences in quiet and sentences in noise. Figure 2 shows study results for the adaptive measure in the R-Space for the three pre/perilingual participants. For this measure of SNR, lower scores indicate better performance. None of the pre/perilingual participants were able to understand sentences in the presence of restaurant noise (thus they were given a score at the greatest SNR, +22, since they were unable to do the task). Across measures and pre/perilingual participants, very few bimodal benefits were seen compared to the HA-alone condition. Localization abilities also were not significantly improved bimodally over the HA-alone condition for the pre/perilingual participants.

Figure 2. Adaptive HINT scores in restaurant noise at the 6 mo interval for pre/perilingual participants are shown. Scores are expressed as SNR and are shown in black for the poorer-hearing ear that was implanted, in white for the better-hearing ear with a HA, and in gray for the participants’ everyday listening condition (bimodal at the postimplant interval). HINT, hearing in noise test; SNR, signal to noise ratio; HA, hearing aid. (Reprinted with permission from Lippincott Williams and Wilkins/Wolters Kluwer Health: Firszt et al. 2012, Cochlear Implantation in Adults with Asymmetric Hearing Loss, Vol 33, 4, p. 528. Promotional and commercial use of the material in print, digital or mobile device format is prohibited without the permission from the publisher Lippincott Williams & Wilkins.)

For all participants, including the pre/perilingual participants without documented bimodal benefit, mean questionnaire ratings indicated improved perceived communication function at six months post-implant compared to pre-implant. In summary, distinct patterns were observed for adults with postlingual versus pre/perilingual hearing loss. All postlingual adults had CI-alone speech recognition even when there was a prolonged period of deafness and no HA use. In contrast, pre/perilingual adults had minimal to no CI-alone speech recognition. Age at onset of hearing loss in childhood appears to be a significant factor, despite substantial hearing levels in the non-implanted better ear.

Study 2: Varied Forms of Asymmetric

Hearing – Adults

Three adult patient groups who were unilateral listeners with varied hearing modes were compared on the SSQ. The first group (UHL group; n = 30) had normal hearing in one ear and SPHL in the other ear. The second group (CI group; n = 20) had a CI in one ear and SPHL in the other ear. The third group (HA group; n = 16) used a HA in one ear and had SPHL in the other ear. In addition, participants of similar age with normal hearing bilaterally completed the SSQ (NH group; n = 21). The SSQ consists of 49 items that have respondents indicate their level of hearing ability/disability along a 10-point scale for each item; 10 indicates the greatest ability and 0 the greatest disability. Results were analyzed by domain (Gatehouse & Noble, 2004) and subscale (Gatehouse & Akeroyd, 2006). The three SSQ domains are Speech (14 items), Spatial (17 items) and Quality (19 items). Gatehouse & Akeroyd (2006) subdivided the domains into 10 subscales to provide greater detail when describing respondents’ communication function. Subscales of the Speech domain were Speech in Quiet (SiQ), Speech in Noise (SiN), Speech in Speech Contexts (SiSCont), and Multiple Speech Stream Processing and Switching (MultStream). Subscales of the Spatial domain were Localization (Loc), and Distance and Movement (DisMov). Subscales of the Qualities domain were Segregation of Sounds (SegSnds), Identification of Sound and Objects (IdSnd), Sound Quality and Naturalness (Qlty), and Listening Effort (Eff).

Figure 3 shows mean responses by domain and subscale for each of the participant groups, Speech domain in panel A, Spatial domain in panel B and Qualities domain in panel C. Responses are shown for the NH group in white, the UHL group in black, the CI group in dark gray, and the HA group in light gray. The NH group responses were significantly better than each of the three hearing-impaired groups for all subscales and domains. No matter the mode of hearing, all unilateral listening groups, even the UHL group with a normal hearing ear, perceived significant communication challenges in all areas addressed by the SSQ. Comparison of the three hearing-impaired groups identified few significant differences. The UHL group rated themselves significantly higher than the HA group for the Speech domain and four subscales (SiQ, SiSCont, IdSnd, and Qlty).

Figure 3. Group mean ratings are shown for subscales and domains (top panel Speech, middle panel Spatial, lower panel Qualities) for participants with NH, UHL, a CI, and an HA. Error bars represent standard error. Brackets and asterisks denote significant comparisons, ***p < 0.001, **p < 0.01, *p < 0.05. CI indicates cochlear implant; DisMov, Distance and Movement; Eff, Listening Effort; HA, hearing aid; IdSnd, Identification of Sound and Objects; Loc, Localization; MultStream, Multiple Speech Stream Processing and Switching; NH, normal hearing; Qlty, Sound Quality and Naturalness; SegSnds, Segregation of Sounds; SiQ, Speech in Quiet, SiN, Speech in Noise; SiSCont, Speech in Speech Contexts; SSQ, Speech, Spatial and Qualities of Hearing scale; UHL, unilateral hearing loss. (Reprinted with permission from Lippincott Williams and Wilkins/Wolters Kluwer Health: Dwyer et al. 2014, Effects of Unilateral Input and Mode of Hearing in the Better Ear: Self-reported Performance Using the Speech, Spatial and Qualities of Hearing Scale, (35)1, p. 131. Promotional and commercial use of the material in print, digital or mobile device format is prohibited without the permission from the publisher Lippincott Williams & Wilkins.)

The only statistically different rating between the UHL and CI groups was for IdSnd.

Overall, the results highlight the similarity in perceived ability among these three unilateral listening groups in spite of seemingly very different modes of hearing. For two domains (Spatial and Qualities) and for six subscales (SiN, MultiStream, Loc, DisMov, SegSnds and Eff) there were no significant differences in how the UHL, CI and HA groups rated themselves on the SSQ. Although these three groups perceive their daily communication experiences very similarly, clinical approaches for treatment are quite different. Individuals with a single CI and a contralateral SPHL ear are more routinely considered for a second ear CI. In contrast, individuals with substantial bilateral hearing loss that includes only one ear in the SPHL range or individuals with unilateral normal hearing and a contralateral SPHL ear are rarely considered CI candidates. In Dwyer et al. (2014) a majority of the CI and HA group participants went on to obtain a CI for the SPHL ear. Six-month post-treatment results were significantly higher than pre-treatment results for both groups on all three SSQ domains and all 10 subscales. Post treatment, the CI group (now bilateral CI recipients) rated themselves significantly higher than the UHL group on the Spatial domain and the SiQ, SiN, Loc, DisMov, and Eff subscales. Post treatment, the HA group (now bimodal recipients) rated themselves significantly higher than the UHL group on Loc and Eff. This suggests that bilateral/binaural hearing as well as mode and quality of hearing are significant contributors to successful daily communication as viewed by the individual.

Study 3: Asymmetric Hearing Loss – Children

A small group of five children and adolescents (10 – 19 years of age) with asymmetric hearing loss (one ear meeting CI candidacy criteria and the other ear with better hearing) received a CI based on clinical recommendations and were evaluated after at least six months of CI experience (six months to five years). (Cadieux, Firszt, & Reeder, 2013). All participants consistently used a HA on the non-implanted ear. Three of the participants had a more favorable hearing history for the ear that was implanted (either non-congenital SPHL onset and/or consistent HA use and three to five years of CI experience) than the other two participants (congenital SPHL onset, no HA use, and only six months of CI experience).

Testing was completed in three listening conditions: CI alone, HA alone, and bimodal. Test measures included CNC words at 50 dB SPL, CNC words at 60 dB SPL with 4TB at +8 dB SNR, HINT sentences in the R-Space with restaurant noise at 60 dB SPL (described above), and the Bamford-Kowal-Bench Speech in Noise test (BKBSIN, Etymotic Research, 2005) with 4TB at 65 dB SPL and the sentence level beginning at +21 dB SNR and incrementally decreasing to 6 dB SNR. Localization was also measured in the same manner as described above.

The three participants with the more favorable hearing history had significantly better bimodal scores compared to CI alone or HA alone on one or more of the speech recognition measures. All three participants had significantly improved localization when comparing bimodal to either the HAor CI-alone condition. The two participants with congenital SPHL onset, no HA experience and only six months CI use had limited or no CI-alone speech understanding. One of the two did significantly better bimodally than with either device alone for the R-Space. Neither had improved localization bimodally over the HA or CI alone.

Some children and adolescents with asymmetric hearing were able to benefit by receiving a CI for the poorer hearing ear and continuing to use a HA at the better hearing ear, becoming bimodal listeners. Reports by all five participants and their parents reported benefit in everyday listening situations with the addition of the CI compared to their previous unilateral listening condition with a HA. These study results suggest that additional study with a larger group of children is warranted to better understand the potential of cochlear implantation for this group of children.

Summary and Future Clinical Considerations

Continued study of the effects of unilateral input and subsequent treatment in this population is needed, including the effects of cochlear implantation. Implications of unilateral input that occurs early in life and whether binaural abilities can be accessed or developed later are not fully understood. To maximize the potential for those abilities dependent on binaural input, CI candidacy requirements need modification. Importantly, we should evaluate and consider treatment for each ear individually (i.e. optimizing hearing for both ears). Better hearing in one ear should not disqualify an individual for cochlear implantation of an ear with poor hearing and no HA benefit. This approach recognizes the binaural auditory system as a single system, rather than as two ears that are redundant. Current descriptions of these types of hearing profiles, for example, having one normal hearing ear and one deaf ear, should be changed to having an abnormal binaural system. There is clear evidence that what happens to one ear affects the function of the binaural system. As clinicians, we need to treat the entire system.

Acknowledgements

This work was supported by R01DC009010 and P30DC04665 from the National Institute on Deafness and Other Communication Disorders and a Collaborative Faculty-Staff Research Grant from St. Louis Children’s Hospital.

We acknowledge the following for assistance with data collection: Brenda Gotter, Karen Mispagel, Lisa Potts, and Sallie Vanderhoof from Washington University School of Medicine; Sarah Zlomke, Kristen Lewis and Heidi Frazier from Midwest Ear Institute in Kansas City, MO. We thank Chris Brenner and Megan Carter for assistance with data entry, Tim Holden for stimuli calibration and equipment support, Dorina Kallogjeri for statistical support, and our participants for their time and efforts during our studies.

References

Abel, S. M., Alberti, P. W., Haythornthwaite, C., & Riko, K. (1982). Speech intelligibility in noise: effects of fluency and hearing protector type. Journal of the Acoustical Society of America, 71(3), 708-715.

Blamey, P., Artieres, F., Baskent, D., Bergeron, F., Beynon, A., Burke, E., et al. (2013). Factors Affecting Auditory Performance of Postlinguistically Deaf Adults Using Cochlear Implants: An Update with 2251 Patients. Audiology and Neurotology, 18(1), 36-47.

Burton, H., Firszt, J. B., Holden, T., Agato, A., & Uchanski, R. M. (2012). Activation lateralization in human core, belt, and parabelt auditory fields with unilateral deafness compared to normal hearing. Brain Research, 1454, 33-47. doi: S0006-8993(12)00398-8 [pii]10.1016/j.brainres.2012.02.066

Cadieux, J. H., Firszt, J. B., & Reeder, R. M. (2013). Cochlear implantation in nontraditional candidates: preliminary results in adolescents with asymmetric hearing loss. Otology and Neurotology, 34(3), 408-415. doi: 10.1097/MAO.0b013e31827850b8

Compton-Conley, C. L., Neuman, A. C., Killion, M. C., & Levitt, H. (2004). Performance of directional microphones for hearing aids: real-world versus simulation. Journal of the American Academy of Audiology,15(6), 440-455.

Dorman, M. F., Spahr, A. J., Loizou, P. C., Dana, C. J., & Schmidt, J. S. (2005). Acoustic Simulations of Combined Electric and Acoustic Hearing (EAS). Ear and Hearing, 26(4), 371-380.

Dwyer, N. Y., Firszt, J. B., & Reeder, R. M. (2014). Effects of Unilateral Input and Mode of Hearing in the Better Ear: Self-reported Performance Using the Speech, Spatial and Qualities of Hearing Scale. Ear and Hearing, 35(1), 126-136. doi: 10.1097/ AUD.0b013e3182a3648b

Etymotic Research. (2005). BKB-SIN Speech-in-Noise Test, Version 1.03. Elk Grove Village, IL.

Feuerstein, J. F. (1992). Monaural versus binaural hearing: ease of listening, word recognition, and attentional effort. Ear and Hearing, 13(2), 80-86.

Firszt, J. B., Holden, L. K., Reeder, R. M., Cowdrey, L., & King, S. (2012). Cochlear implantation in adults with asymmetric hearing loss. Ear and Hearing, 33(4), 521-533. doi: 10.1097/AUD.0b013e31824b9dfc

Gatehouse, S., & Akeroyd, M. (2006). Two-eared listening in dynamic situations. International Journal of Audiology, 45, Suppl, 120-124.

Gatehouse, S., & Noble, W. (2004). The Speech, Spatial and Qualities of Hearing Scale (SSQ). International Journal of Audiology, 43(2), 85-99.

Giolas, T. G., & Wark, D. J. (1967). Communication problems associated with unilateral hearing loss. Journal of Speech and Hearing Disorders, 32(4), 336-343.

Holden, L. K., Finley, C. C., Firszt, J. B., Holden, T. A., Brenner, C., Potts, L. G., et al. (2013). Factors affecting open-set word recognition in adults with cochlear implants. Ear and Hearing, 34(3), 342-360. doi: 10.1097/AUD.0b013e3182741aa7

Hubel, D. H., & Wiesel, T. N. (1970). The period of susceptibility to the physiological effects of unilateral eye closure in kittens. Journal of Physiology, 206(2), 419-436.

Humes, L. E., Allen, S. K., & Bess, F. H. (1980). Horizontal sound localization skills of unilaterally hearing-impaired children. Audiology, 19(6), 508-518.

Khosla, D., Ponton, C. W., Eggermont, J. J., Kwong, B., Don, M., & Vasama, J. P. (2003). Differential ear effects of profound unilateral deafness on the adult human central auditory system. Journal of the Association of Research in Otolaryngology, 4(2), 235-249.

King, S. E., Firszt, J. B., Reeder, R. M., Holden, L. K., & Strube, M. J. (2012). Evaluation of TIMIT sentence list equivalency with adult cochlear implant recipi>ents. Journal of the American Academy of Audiology,23, 313-331.

Kral, A. (2013). Auditory critical periods: A review from system’s perspective. Neuroscience, 247,117-133. doi: http://dx.doi.org/10.1016/j.neuroscience.2013.05.021

Kral, A., Hartmann, R., Tillein, J., Heid, S., & Klinke, R. (2000). Congenital auditory deprivation reduces synaptic activity within the auditory cortex in a layer-specific manner. Cerebral Cortex, 10(7), 714-726.

Lamel, F. L., Kassel, R. H., & Seneff, S. (1986). Speech database developmentent: design and analysis of the acoustic-phonetic corpus. Proceedings of DARPA Speech Recognition Workshop, Report No. SAIC->86\1546.

Maslin, M. R. D., Munro, K. J., & El-Deredy, W. (2013). Source analysis reveals plasticity in the auditory cortex: Evidence for reduced hemispheric asymmetries following unilateral deafness. Clinical Neurophysiology, 124(2), 391-399. doi: http://dx.doi.org/10.1016/j.clinph.2012.07.016

McLeod, B., Upfold, L., & Taylor, A. (2008). Self reported hearing difficulties following excision of vestibular schwannoma. International Journal of Audiology, 47(7), 420-430. doi: 792164789 [pii] 10.1080/14992020802033083

Nicholas, J. G., & Geers, A. E. (2006). Effects of early auditory experience on the spoken language of deaf children at 3 years of age. Ear and Hearing, 27(3), 286-298.

Nicholas, J. G., & Geers, A. E. (2007). Will they catch up? The role of age at cochlear implantation in the spoken language development of children with severe to profound hearing loss. Journal of Speech, Language and Hear Research, 50(4), 1048-1062. doi: 50/4/1048 [pii]10.1044/1092-4388(2007/073)

Nilsson, M., Soli, S. D., & Sullivan, J. A. (1994). Development of the Hearing in Noise Test for the measurement of speech reception thresholds in quiet and in noise. Journal of the Acoustical Society of America,95(2), 1085-1099.

Peterson, G. E., & Lehiste, I. (1962). Revised CNC lists for auditory tests. Journal of Speech and Hearing Disorders, 27, 62-70.

Revit, L. J., Schulein, R. B., & Julsrom, S. D. (2002). Toward accurate assessment of real-world hearing aid benefit. Hearing Review, 9, 34-38, 51.

Ryugo, D. K., Pongstaporn, T., Huchton, D. M., & Niparko, J. K. (1997). Ultrastructural analysis of primary endings in deaf white cats: morphologic alterations in endbulbs of Held. Journal of Comparative Neurolology, 385(2), 230-244.

Ryugo, D. K., Rosenbaum, B. T., Kim, P. J., Niparko, J.K., & Saada, A. A. (1998). Single unit recordings in the auditory nerve of congenitally deaf white cats: morphological correlates in the cochlea and cochlear nucleus. Journal of Comparative Neurology, 397(4), 532-548.

Silverman, M. S., & Clopton, B. M. (1977). Plasticity of binaural interaction. I. Effect of early auditory deprivation. Journal of Neurophysiology, 40(6), 1266-1274.

Wie, O. B., Pripp, A. H., & Tvete, O. (2010). Unilateral deafness in adults: effects on communication and social interaction. The Annals of Otology, Rhinology, and Laryngology. 119(11), 772-781.

C H A P T E R  F I F T E E N

Fitting Bimodal Devices in Children – A Review

Lisa S. Davidson, PhD.

Abstract

Bimodal device use cochlear implant (CI) plus hearing aid (HA) on the non-implanted ear is one way to achieve some degree of binaural stimulation of the auditory pathways for children with severe to profound hearing loss requiring cochlear implantation. Bimodal devices are able to partially alleviate many of the listening challenges related to unilateral CI use. The numbers of children using bimodal devices will likely increase as children with more residual hearing are considered as candidates for cochlear implantation. The need for a coordinated fitting between the CI and the HA becomes more relevant as bimodal device users present with greater degrees of residual hearing at the non-implanted ear. This paper will summarize the issues related to fitting the cochlear implant and the hearing aid for bimodal use and review the research literature related to bimodal fittings.

The normal auditory system is highly reliant upon input from both ears for recognizing, localizing and understanding speech in everyday listening environments. For children with severe to profound sensorineural hearing losses requiring cochlear implantation, some degree of binaural stimulation of the auditory pathways may be achieved by wearing a cochlear implant (CI) coupled with a hearing aid (HA) at the non-implanted ear or a CI at both ears (Ching, van Wanrooy, & Dillon, 2007; Sammeth, Bundy, & Miller, 2011). Combining electrical hearing via a CI with acoustic hearing via a HA at the non-implanted ear is frequently referred to as bimodal device use. Bimodal fittings can at least partially alleviate many of the listening challenges encountered when listening with only one CI including localization and listening in noise. Bimodal benefits for children and adults have varied across studies and have included improved speech perception in quiet and noise, localization, speech quality, music appreciation/recognition & ease of listening (Ching et al., 2007; Sammeth et al., 2011; Schafer, Amlani, Paiva, Nozari, & Verret, 2011). In addition to improved listening skills, recent evidence suggests that a period of bimodal device use may result in improved language outcomes and emerging literacy skills for children receiving CIs (Nittrouer, Caldwell, Lowenstein, Tarr, & Holloman, 2012; Nittrouer & Chapman, 2009).

Although the mechanisms underlying bimodal benefits are not completely understood, most research suggests that low-frequency acoustic cues from the HA are primarily responsible for the improvements observed in speech perception (Ching et al., 2007; Dorman, Gifford, Spahr, & McKarns, 2008; Sheffied, 2011; Tyler et al., 2002). Furthermore, several studies have suggested that low frequency acoustic cues allow for transmission of a higher quality fundamental frequency (F0) than that provided by electrical stimulation with current CI systems (Brown & Bacon, 2009; Chang, Bai, & Zeng, 2006; Kong, Stickney, & Zeng, 2005; Qin & Oxenham, 2006; Turner, Gantz, Vidal, Behrens, & Henry, 2004; Vongphoe & Zeng, 2005). In addition, improved phoneme perception including consonant voicing and manner and transmission of low frequency phonemes such as nasals, diphthongs and glides have been documented in bimodal users (T. Ching et al., 2005; M. Mok, D. Grayden, R. C. Dowell, & D. Lawrence, 2006).

Consistent audibility in a variety of listening situations is a necessary prerequisite for spoken language development and it becomes paramount for children with congenital hearing loss (Bess, Dodd-Murphy, & Parker, 1998; Flexer, 1999; Ross, 1990). Children using unilateral CIs are at a great disadvantage for localizing sounds and for understanding speech in the presence of background noise, therefore many audiologists are considering either bimodal or bilateral CIs in their clinical fitting protocols. Bimodal fittings are likely to increase as cochlear implant candidacy guidelines expand to include individuals with a greater degree of residual hearing (Gifford, Dorman, Shallop, & Sydlowski, 2010). Adults and children with residual hearing thresholds that are within the CI Candidacy range for one ear (i.e. severe to profound), but have less severe losses at the opposite ear are now being considered for CIs in order to capitalize on binaural stimulation through bimodal device use (Cadieux, Firszt, & Reeder, 2013; Firszt, Holden, Reeder, Cowdrey, & King, 2012). The need for a coordinated fitting between the CI and the HA becomes more relevant as bimodal device users present with greater degrees of residual hearing at the non-implanted ear.

There are several obstacles related to fitting bimodal devices which combine acoustic and electric stimulation from the HA and CI respectively. These not only stem from psychophysical mismatches across the two devices for timing, intensity and frequency cues, but also mismatches in amplitude processing with current available commercial devices (Francart & McDermott, 2013). While there are no standardized or validated fitting protocols for bimodal devices, some studies suggest that a coordinated fitting between the two devices may be necessary for optimal benefit (Blamey, Dooley, James, & Parisi, 2000; T. Ching, Psarros, Hill, Dillon, & Incerti, 2001). Ching et al. (2001) reported on 16 children (age 6-18 years) with a Nucleus 22 or 24 CI who used a hearing aid in the non-implanted ear. Children were evaluated on several outcome measures including tests of speech perception, localization and surveys of communicative function. The HAs for the non-implanted ear were initially fit using National Acoustics Laboratories-Revised Profound [NAL-RP (Byrne, Parkinson, & Newall, 1991) targets and the frequency response was further adjusted so that the loudness between both devices was balanced. Results revealed that all children tested for binaural effects demonstrated benefit on at least one of the measures used when the individual fitting of the hearing aid was set to match the loudness of the cochlear implant. Subsequent studies have not directly examined the effects of coordinated loudness procedures on bimodal outcomes; however they have been careful to outline that some type of loudness balancing was done. A study conducted on 14 adult bimodal users reported on a fitting procedure where 7 of the participants adjusted the volume of the HA to match the overall loudness of the CI using running speech at conversation levels ~ 65 dB SPL. The HAs were initially set to match NAL-RP targets (M. Mok et al., 2006). A subsequent study of 8 adult and 12 pediatric bimodal participants (age 3 -14 years) outlined a fitting procedure where the HAs were initially set to meet Desired Sensation Level (DSL) targets (Cornelisse, Seewald, & Jameson, 1994). Loudness scaling procedures, speech perception testing and subjective reports were conducted with each device alone and both devices combined (bimodal) and adjustments were made to each device in an in an attempt to obtain a bimodal score that was superior to either device alone (Keilmann, Bohnert, Gosepath, & Mann, 2009). Notably, the authors reported that children age 10 years or older were able to complete the loudness scaling task required for the bimodal fitting and the total length of the fitting session lasted between 3-5 hours. The authors concluded that most adults and children that could undergo the fitting procedures showed bimodal benefit (i.e. CI+HA scores better than CI or HA alone).

While the reported procedures for balancing loudness between the two devices have varied and are not standardized, there is a general consensus that some form of loudness balancing may be beneficial. Determining how frequency information should be allocated to the CI and the HA is much less clear. For the audiologist fitting these devices this entails determining the degree of frequency overlap, if any, between the CI and HA. When parsing the benefits of bimodal devices according to the frequency information transmitted, it is generally accepted that the benefits of the HA are related to low frequency regions and the CI are related to high frequency regions. This seems reasonable given that the typical hearing threshold profile for the non-implanted ear (i.e. HA ear) show thresholds ranging from mild to severe in the low to mid frequency region (~250-1000 Hz) and severe to profound in the high frequency regions (2000-4000Hz). Earlier studies of frequency overlap between the CI and HA were conducted using combined acoustic and electric stimulation (EAS) at the same ear (sometimes called ipsi-lateral EAS). Fitting procedures, research methods and not surprisingly conclusions varied across theses studies with recommendations ranging from no frequency overlap to some degree of overlap (Gantz & Turner, 2004; James et al., 2006; Kiefer et al., 2005; Simpson, McDermott, Dowell, Sucher, & Briggs, 2009; Vermeire, Anderson, Flynn, & Van de Heyning, 2008). One study in particular stressed that the EAS fitting should take into account the degree and configuration of the acoustic thresholds (Vermeire et al., 2008).

Based on our basic understanding of bimodal mechanisms it seems reasonable for audiologists to primarily focus on the low frequency regions, or regions with the greater degree of residual hearing when setting the gain and output of the HA for bimodal fittings. This would be in contrast to routine bilateral HA fittings where audibility across the greatest frequency range is targeted. The results from studies to date have been inconclusive. A study of nine pediatric bimodal recipients found that better low frequency aided thresholds with the HA and poorer aided thresholds at 4000 Hz were associated with greater bimodal benefit for speech perception in quiet and noise (Mok, Galvin, Dowell, & McKay, 2010). The authors suggest that this may have been the result of frequency mismatch between the CI and HA, and that a possible solution would be to limit the gain of the HA at the higher frequency regions. Results from an earlier study with adult bimodal recipients demonstrated that poorer aided thresholds in the high frequency region were associated with greater bimodal benefits (Mansze Mok, David Grayden, Richard C. Dowell, & David Lawrence, 2006). Potts and colleagues (Potts, Skinner, Litovsky, Strube, & Kuk, 2009) found a different pattern of results for adult bimodal recipients for speech recognition and localization, showing that better audibility at 2000Hz was related to better performance. These studies, however did not systematically examine the effects of frequency overlap across devices.

A study of adult bimodal users examined the benefits of reducing the frequency overlap between the acoustic signal and the electric signal using open set word recognition in quiet and sentence recognition in noise (Zhang, Spahr, & Dorman, 2010). The electrical signal was presented directly to the CI device in the following conditions: unfiltered and high pass filtered at 250, 500 and 750 Hz. The acoustic signal was delivered via a headphone as follows: unfiltered and low pass (LP) filtered at 250, 500 and 750 Hz. The gain and output of the acoustic signal for each participant was based on unaided thresholds and NAL-RP targets. Participants were tested in each condition using electric and acoustic alone and in the combined condition pairing the LP and HP conditions (i.e. unfiltered acoustic + unfiltered CI or widest, 250 LP acoustic +250 HP CI, 500 LP acoustic+, 500 HP CI etc.). Performance in the widest conditions was best for electric and acoustic stimulation alone and the combined conditions, thus reducing the frequency overlap for these bimodal users did not improve performance. Notably, the acoustic frequency range < 250 Hz accounted for the majority of benefit in the acoustic and electric combined condition. This led the authors to conclude that: 1) even participants with only limited low frequency residual hearing at the HA may benefit from bimodal stimulation 2) reducing high frequency gain of the HA may reduce acoustic feedback, prolong battery life and prevent off frequency listening. A more recent study addressed the topic of frequency overlap across the two devices with a couple of key differences (Neuman & Svirsky, 2013). The first difference was that each participant’s personal HA was used instead of an earphone. The second difference was that the CI frequency allocation remained the same (widest) and only the HA frequency bandwidth was varied. Fourteen adult bimodal recipients were tested with words in quiet and sentences in noise with the 4 different HA frequency responses. The wideband HA frequency response was determined by matching the gain and output to NAL-RP targets as closely as possible. The bandwidth of the HA was then systemically restricted at 500, 1000 and 2000 Hz. Bimodal benefit was defined as better scores in the bimodal condition/s compared to the CI only. The best performance was obtained when the gain and output were amplified across the widest frequency range of usable residual hearing. Furthermore, restricting the gain below 1000 Hz did not provide greater benefit.

There has also been increasing interest in using frequency lowering technology available in HAs for bimodal fittings. Different manufacturers employ various algorithms and use different names for HA technology that is designed to shift high frequency information to a lower frequency region (Glista et al., 2009). Non-linear frequency compression (NLFC) is one type of algorithm that is implemented in HAs by only compressing higher frequencies in a predetermined range and leaving lower frequencies unchanged. This allows for improved audibility of consonants without possible distortion of low frequency vowel formants. These parameters, referred to as the cut-off frequency and compression ratio, are adjusted by the clinician (McDermott & Henshall, 2010). In general, the default settings recommend that the minimum amount of compression be employed as increasing the range of frequencies that are compressed can cause detriments to sound quality and discrimination of vowel sounds. Individuals with severe to profound hearing loss in the high frequency range are typical candidates for frequency lowering HAs since many are unable to achieve adequate high frequency audibility due to limited gain and acoustic feedback.

High frequency audibility assumes a critical role in linguistic development for children acquiring spoken English skills. Specifically, many consonant sounds consist of high frequency energy that contributes to overall speech intelligibility (Miller & Nicely, 1955) and the English phonemes /s/ and /z/ serve as important markers for plurality and possession (Moeller, Hoover, Putman, Arbataitis, Bohnenkamp, Peterson, Lewis, et al., 2007; Moeller, Hoover, Putman, Arbataitis, Bohnenkamp, Peterson, Wood, et al., 2007; P. G. Stelmachowicz, Lewis, Choi, & Hoover, 2007). This is supported by several studies demonstrating that children require a wider frequency bandwidth for optimal perception of speech compared to adults (Pittman, Lewis, Hoover, & Stelmachowicz, 2005; Pittman & Stelmachowicz, 2000; Patricia G. Stelmachowicz, Pittman, Hoover, & Lewis, 2002). Modest positive results, especially for detection of high frequency phonemes, have been documented for children with moderate to severe hearing loss using frequency lowering HAs (McCreery, Venediktov, Coleman, & Leech, 2012). This has led many clinicians and researchers to examine if NLFC should be considered for bimodal recipients.

Alternatively, it may be reasonable to be concerned that this type of processing could interfere with the CI processing given that for most bimodal recipients the transmission of high frequency information is transmitted via the CI. Differences in the place of high frequency stimulation of the cochlea across the two devices as well as overall processing differences may be expected to interfere with binaural processing. To date the literature for adult and pediatric bimodal recipients has produced mixed results. Two studies with adult bimodal recipients failed to demonstrate benefits of NLFC over the conventional HA setting (NLFC not activated). One study with eight adult bimodal recipients did not find any benefit, or detriment with NLFC activated vs. not activated for consonant perception in quiet and sentences in noise, however participants readily accepted NLFC (McDermott and Henshall, (2010). A recent study on 10 adult bimodal recipients found no benefits for NLFC for spondee recognition in noise or localization and many of the participants reported that NLFC produced a “harsh” or “distorted” sound quality (Perreau, Bentler, & Tyler, 2013). A study of 11 pediatric bimodal participants found no benefit with HAs with NLFC vs. without NLFC for word and consonant recognition in quiet and sentence recognition in noise, however many of these pediatric participants preferred using NLFC (Park, Teagle, Buss, Roush, & Buchman, 2012). The compression cut-off frequency and compression ratio were set for participants in these studies based on individual hearing thresholds. The verification procedures varied across studies with some verifying audibility using live voice presentation of the phonemes /s/ and / sh / and measuring the simulated real ear output compared to the unaided thresholds from 2000-4000 Hz. Others presented recorded 4000 and 6300 Hz speech bands or high frequency inputs generated from a probe microphone system.

The review of the literature on the effects of various HA settings on bimodal benefit have mainly included leaving the CI program unchanged (i.e. widest frequency allocation) and varying the HA frequency response to some degree. The results from Zhang et al (2010) support allowing the CI map to cover the standard frequency range (i.e. 250-4000 Hz) and to consider various options for the HA response. This seems to be reasonable given that most, though not all, bimodal recipients consider the CI their primary device. The fact that these studies have produced such mixed results is not necessarily surprising given the variability across research methods, HA fitting procedures, outcome measures, hearing threshold profiles and clinical populations (i.e. adults vs. pediatric). A common component of many of these studies is that there is a considerable degree of individual variability as to the best “condition” (McDermott & Henshall, 2010; Park et al., 2012). Clinical audiologists know that their patients present with a variety of hearing backgrounds, individual needs and abilities, thus there is no “one size fits all” for fitting devices. Likewise, fitting procedures, targets and recommendations for adults may not necessarily apply to children. In order to best serve their pediatric bimodal population, audiologists should attempt some type of procedure for balancing audibility and loudness across the two devices. There are no standardized procedures or guidelines; however several of the studies mentioned above outline some protocols for doing so. Most start with using a prescriptive fitting target for the HA with gain and output modified when listening with the CI and HA combined. The ability to conduct a detailed protocol will necessarily be limited by the age and abilities of the child; however setting both devices for good audibility is a good start. This would involve aided thresholds near 20 dB HL from 250-6000 Hz for the CI and matching prescriptive targets for the HA at input levels (i.e. DSL targets) from soft to loud.

Summary

Audiologists may consider modifying the frequency response of the HA for individuals demonstrating minimal bimodal benefit with conventional settings. This may include restricting the gain to low or mid frequency regions depending on the residual hearing. The audiologist may consider activating NLFC as well. Careful monitoring and testing would be important. Verification of audibility should be conducted using all or some combination of live voice detection of phonemes or audibility of recorded speech bands (4000 and 6300 Hz) with a real ear measurement system. A variety of speech measures that replicate real world listening conditions is needed and may include measures beyond word and sentence recognition in quiet and noise. Among those to be considered would be localization tasks, music/melody perception, talker discrimination and parent/self report questionnaires.

Conclusion

Given that receiving a second CI will require a surgical intervention, clinicians and parents must carefully weigh the decision to proceed from bimodal to bilateral CIs and careful monitoring and testing should be conducted. It is important to note that reviews of the literature on bimodal vs. bilateral CIs have not produced definitive results as to the device configuration that will provide the greatest benefit for an individual (Ching et al., 2007; Schafer et al., 2011). It will also be important to consider bilateral CIs for those children who demonstrate little or no benefit from bimodal fittings.

References

Bess, F. H., Dodd-Murphy, J., & Parker, R. A. (1998). Children with minimal sensorineural hearing loss: prevalence, educational performance, and functional status. Ear and Hearing, 19(5), 339-354.

Blamey, P. J., Dooley, G. J., James, C. J., & Parisi, E. S. (2000). Monaural and binaural loudness measures in cochlear implant users with contralateral residual hearing. Ear and Hearing, 21(1), 6-17.

Brown, C. A., & Bacon, S. P. (2009). Low-frequency speech cues and simulated electric-acoustic hearing. Journal of the Acoustical Society of America, 125(3), 1658-1665. doi: 10.1121/1.3068441

Byrne, D., Parkinson, A., &, & Newall, P. (1991). Modified hearing aid selection procedures for severe/ profound hearing losses. In G. A. Studebaker, F. H. Bess, & L. Beck (Eds.), Vanderbilt hearing aid report II (pp. (pp. 295–300). Parkton, MD: York Press.

Cadieux, J. H., Firszt, J. B., & Reeder, R. M. (2013). Cochlear implantation in nontraditional candidates: preliminary results in adolescents with asymmetric hearing loss. Otology and Neurotology, 34(3), 408-415. doi: 10.1097/MAO.0b013e31827850b8

Chang, J. E., Bai, J. Y., & Zeng, F. G. (2006). Unintelligible low-frequency sound enhances simulated cochlear-implant speech recognition in noise. IEEE Transactions in Biomedical Engineering, 53(12 Pt 2), 2598-2601. doi: 10.1109/TBME.2006.883793

Ching, van Wanrooy, E., & Dillon, H. (2007). Binaural-bimodal fitting or bilateral implantation for managing severe to profound deafness: a review. Trends in Amplification, 11(3), 161-192. doi: 11/3/161 [pii] 10.1177/1084713807304357

Ching, T., Hill, M., Brew, J., Incerti, P., Priolo, S., Rushbrook, E., & Forsythe, L. (2005). The effect of auditory experience on speech perception, localization, and functional performance of children who use a cochlear implant and a hearing aid in opposite ears. International Journal of Audiology, 44(12), 677-690. doi: Doi 10.1080/00222930500271630

Ching, T., Psarros, C., Hill, M., Dillon, H., & Incerti, P. (2001). Should children who use cochlear implants wear hearing aids in the opposite ear? Ear and Hearing, 22(5), 365-380.

Cornelisse, L. E., Seewald, R. C., & Jameson, D. G. (1994). Fitting wide dynamic range compression hearing aids: the DSL approach. Hearing Journal, 47, 23-29.

Dorman, M. F., Gifford, R. H., Spahr, A. J., & McKarns, S. A. (2008). The benefits of combining acoustic and electric stimulation for the recognition of speech, voice and melodies. Audiology and Neurotology, 13(2), 105-112. doi: 10.1159/000111782

Firszt, J. B., Holden, L. K., Reeder, R. M., Cowdrey, L., & King, S. (2012). Cochlear implantation in adults with asymmetric hearing loss. Ear and Hearing, 33(4), 521-533. doi: 10.1097/AUD.0b013e31824b9dfc

Flexer, C. A. (1999). The importance of hearing and the impact of hearing problems. Facilitating Hearing and Listening in Young Children (Second Edition ed., pp. 1-22). San Diego: Singular Publishing Group.

Francart, T., & McDermott, H. J. (2013). Psychophysics, fitting, and signal processing for combined hearing aid and cochlear implant stimulation. Ear and Hearing, 34(6), 685-700. doi: 10.1097/AUD.0b013e-31829d14cb

Gantz, B. J., & Turner, C. (2004). Combining acoustic and electrical speech processing: Iowa/Nucleus hybrid implant. Acta Otolaryngolica, 124(4), 344-347.

Gifford, R. H., Dorman, M. F., Shallop, J. K., & Sydlowski, S. A. (2010). Evidence for the expansion of adult cochlear implant candidacy. Ear and Hearing, 31(2), 186-194. doi: 10.1097/AUD.0b013e3181c6b831

Glista, D., Scollie, S., Bagatto, M., Seewald, R., Parsa, V., & Johnson, A. (2009). Evaluation of nonlinear frequency compression: clinical outcomes. International Journal of Audiology, 48(9), 632-644. doi: 10.1080/14992020902971349

James, C. J., Fraysse, B., Deguine, O., Lenarz, T., Mawman, D., Ramos, A., . . . Sterkers, O. (2006). Combined electroacoustic stimulation in conventional candidates for cochlear implantation. Audiology and Neurotology, 1(11 Suppl), 57-62. doi: 10.1159/000095615

Keilmann, A. M., Bohnert, A. M., Gosepath, J., & Mann, W. J. (2009). Cochlear implant and hearing aid: a new approach to optimizing the fitting in this bimodal situation. European Archives of Otorhinolaryngology, 266(12), 1879-1884. doi: 10.1007/s00405-009-0993-9

Kiefer, J., Pok, M., Adunka, O., Sturzebecher, E., Baumgartner, W., Schmidt, M., . . . Gstoettner, W. (2005). Combined electric and acoustic stimulation of the auditory system: results of a clinical study. Audiology and Neurotology, 10(3), 134-144. doi: 84023 [pii] 10.1159/000084023

Kong, Y. Y., Stickney, G. S., & Zeng, F. G. (2005). Speech and melody recognition in binaurally combined acoustic and electric hearing. Journal of the Acoustical Society of America, 117(3 Pt 1), 1351-1361.

McCreery, R. W., Venediktov, R. A., Coleman, J. J., & Leech, H. M. (2012). An Evidence-Based Systematic Review of Frequency Lowering in Hearing Aids for School-Age Children With Hearing Loss. American Journal of Audiology, 21(2), 313-328. doi: 10.1044/1059-0889(2012/12-0015)

McDermott, H., & Henshall, K. (2010). The use of frequency compression by cochlear implant recipients with postoperative acoustic hearing. Journal of the American Academy of Audiology, 21(6), 380-389. doi: 10.3766/jaaa.21.6.3

Miller, G. A., & Nicely, P. E. (1955). An Analysis of Perceptual Confusions Among Some English Consonants. Journal of the Acoustical Society of America, 27(2), 338-352.

Moeller, M. P., Hoover, B., Putman, C., Arbataitis, K., Bohnenkamp, G., Peterson, B., . . . Stelmachowicz, P. (2007). Vocalizations of infants with hearing loss compared with infants with normal hearing: Part II--transition to words. Ear and Hearing, 28(5), 628-642. doi: 10.1097/AUD.0b013e31812564c9

Moeller, M. P., Hoover, B., Putman, C., Arbataitis, K., Bohnenkamp, G., Peterson, B., . . . Stelmachowicz, P. (2007). Vocalizations of infants with hearing loss compared with infants with normal hearing: Part I--phonetic development. Ear and Hearing, 28(5), 605-627. doi: 10.1097/AUD.0b013e31812564ab00003446-200709000-00002 [pii]

Mok, M., Galvin, K. L., Dowell, R. C., & McKay, C. M. (2010). Speech perception benefit for children with a cochlear implant and a hearing aid in opposite ears and children with bilateral cochlear implants. Audiology and Neurotology, 15(1), 44-56. doi: 000219487 [pii]10.1159/000219487

Mok, M., Grayden, D., Dowell, R. C., & Lawrence, D. (2006). Speech Perception for Adults Who Use Hearing Aids in Conjunction With Cochlear Implants in Opposite Ears. Journal of Speech, Language, and Hearing Research, 49(2), 338-351.

Mok, M., Grayden, D., Dowell, R. C., & Lawrence, D. (2006). Speech perception for adults who use hearing aids in conjunction with cochlear implants in opposite ears. Journal of Speech, Language and Hearing Research, 49(2), 338-351. doi: 10.1044/1092-4388(2006/027)

Neuman, A. C., & Svirsky, M. A. (2013). Effect of hearing aid bandwidth on speech recognition performance of listeners using a cochlear implant and contralateral hearing aid (bimodal hearing). Ear and Hearing, 34(5), 553-561. doi: 10.1097/AUD. 0b013e31828e86e8

Nittrouer, S., Caldwell, A., Lowenstein, J. H., Tarr, E., & Holloman, C. (2012). Emergent literacy in kindergartners with cochlear implants. Ear and Hearing, 33(6), 683-697. doi: 10.1097/AUD.0b013e318258c98e

Nittrouer, S., & Chapman, C. (2009). The effects of bilateral electric and bimodal electricacoustic stimulation on language development. Trends in Amplification, 13(3), 190-205. doi: 10.1177/1084713809346160

Park, L. R., Teagle, H. F., Buss, E., Roush, P. A., & Buchman, C. A. (2012). Effects of frequency compression hearing aids for unilaterally implanted children with acoustically amplified residual hearing in the nonimplanted ear. Ear and Hearing, 33(4), e1-e12. doi:

10.1097/AUD.0b013e31824a3b97

Perreau, A. E., Bentler, R. A., & Tyler, R. S. (2013). The contribution of a frequency-compression hearing aid to contralateral cochlear implant performance. Journal of the American Academy of Audiology, 24(2), 105-120. doi: 10.3766/jaaa.24.2.4

Pittman, A. L., Lewis, D. E., Hoover, B. M., & Stelmachowicz, P. G. (2005). Rapid word-learning in normal-hearing and hearing-impaired children: effects of age, receptive vocabulary, and high-frequency amplification. Ear and Hearing, 26(6), 619-629. doi: 00003446-200512000-00008 [pii]

Pittman, A. L., & Stelmachowicz, P. G. (2000). Perception of voiceless fricatives by normal-hearing and hearing-impaired children and adults. Journal of Speech, Language and Hearing Research, 43(6), 1389-1401.

Potts, L. G., Skinner, M. W., Litovsky, R. A., Strube, M.J., & Kuk, F. (2009). Recognition and localization of speech by adult cochlear implant recipients wearing a digital hearing aid in the nonimplanted ear (bimodal hearing). Journal of the American Academy of Audiology, 20(6), 353-373.

Qin, M. K., & Oxenham, A. J. (2006). Effects of introducing unprocessed low-frequency information on the reception of envelope-vocoder processed speech. Journal of the Acoustical Society of America, 119(4), 2417-2426.

Ross, M. (1990). Implications of delay in detection and management of deafness. Volta Review, 92, 69-79.

Sammeth, C. A., Bundy, S. M., & Miller, D. A. (2011). Bimodal Hearing or Bilateral Cochlear Implants: A Review of the Research Literature. Seminars in Hearing, 32(01), 003-031. doi: 10.1055/s-0031-1271945

Schafer, E. C., Amlani, A. M., Paiva, D., Nozari, L., & Verret, S. (2011). A meta-analysis to compare speech recognition in noise with bilateral cochlear implants and bimodal stimulation. International Journal of Audiology, 50(12), 871-880. doi: 10.3109/14992027.2011.622300

Sheffied, B. M. Z., F. G. (2011). The relative phonetic contributions of a cochlear implant and residual acoustic hearing to bimodal speech perception. Journal of the Acoustical Society of America, 131(1), 518-530.

Simpson, A., McDermott, H. J., Dowell, R. C., Sucher, C., & Briggs, R. J. S. (2009). Comparison of two frequency-to-electrode maps for acoustic-electric stimulation. International Journal of Audiology, 48(2), 63-73. doi: doi:10.1080/14992020802452184

Stelmachowicz, P. G., Lewis, D. E., Choi, S., & Hoover, B. (2007). Effect of stimulus bandwidth on auditory skills in normal-hearing and hearing-impaired children. Ear and Hearing, 28(4), 483-494. doi: 10.1097/ AUD.0b013e31806dc26500003446-200708000-00006 [pii]

Stelmachowicz, P. G., Pittman, A. L., Hoover, B. M., & Lewis, D. E. (2002). Aided Perception of /s/ and /z/ by Hearing-Impaired Children. [Article]. Ear & Hearing 23(4), 316-324.

Turner, C. W., Gantz, B. J., Vidal, C., Behrens, A., & Henry, B. A. (2004). Speech recognition in noise for cochlear implant listeners: benefits of residual acoustic hearing. Journal of the Acoustical Society of America, 115(4), 1729-1735.

Tyler, R. S., Parkinson, A. J., Wilson, B. S., Witt, S., Preece, J. P., & Noble, W. (2002). Patients utilizing a hearing aid and a cochlear implant: speech perception and localization. Ear and Hearing, 23(2), 98-105.

Vermeire, K., Anderson, I., Flynn, M., & Van de Heyning, P. (2008). The influence of different speech processor and hearing aid settings on speech perception outcomes in electric acoustic stimulation patients. Ear and Hearing, 29(1), 76-86. doi: 10.1097/ AUD.0b013e31815d6326

Vongphoe, M., & Zeng, F. G. (2005). Speaker recognition with temporal cues in acoustic and electric hearing. Journal of the Acoustical Society of America, 118(2), 1055-1061.

Zhang, T., Spahr, A. J., & Dorman, M. F. (2010). Frequency Overlap Between Electric and Acoustic Stimulation and Speech-Perception Benefit in Patients with Combined Electric and Acoustic Stimulation. Ear and Hearing, 31(2), 195-201. doi: Doi 10.1097/ Aud.0b013e3181c4758d

C H A P T E R  S I X T E E N

Understanding the Needs of Children Who are

Deaf/Hard of Hearing Plus

Susan Wiley, M.D.

Abstract

Children who are deaf or hard of hearing (deaf/HH) have a high rate of additional disabilities. Understanding developmental progress and recognizing when children are showing different rates of progress is helpful to intervene more effectively for a child’s broader needs. Focusing on functional skill development, strong partnership with parents and clinicians from broad professional backgrounds can allow a stronger approach to intervention for children with complex needs. Being creative and innovative can assist in the identification of strategies to support a child’s progress and successes.

Additional disabilities in children who are deaf or hard of hearing (deaf/HH) are fairly common, with rates reported as high as 40%. The term Deaf/HH Plus has been used to guide a positive perspective on this group of children. Specific additional disabilities in children who are deaf/HH occur at a higher rate than the general population. Table 1 compares rates of disabilities in children who are deaf/HH to the rates in the general population. This population of children has unique challenges. The complicating factors of the impact of hearing loss and an additional disability can make it challenging to plan an approach to effective intervention. Our goal should be to focus on children achieving their maximum potential. The rewards are great when children make progress, even if not at the rate of typically developing children.

One possible reason for this higher rate of disabilities among children who are deaf/HH is due to the presence of risk factors for hearing loss which are also known to be associated with developmental delays. Additionally, some syndromes associated with hearing loss can impact broader development.

Table 1: Rates of specific disabilities in children who are deaf/HH and the general population (Adapted from Boyle et al. 2011; Gallaudet Research Institute, 2011).

It is important to recognize that sometimes children can have risk factors for developmental delays which are unrelated to hearing loss, such as a family history of developmental problems. Risk factors for developmental delay can co-occur in children with hearing loss. Thus, the cause of their hearing loss doesn’t “protect” them from other factors which can impact development.

Typical Developmental Progression

It is helpful to understand typical child developmental progression and recognize when children who are deaf/HH are not following this developmental trajectory. Although, hearing is an important aspect to consider in understanding how children learn language, developmental progression is largely about early brain development. In the first two years of life, there is exponential head growth. This growth is due to rapid changes in brain development and a rapid increase in neuronal connections that are made in early childhood, coupled with myelination. Myelination is the development of white matter around the nerves to help the signaling and messages to travel through the neural connections. Although many have considered the first three years of life as a critical window for child development, learning continues to occur after this period. In fact, myelination of the brain occurs into early adulthood (mid-20’s).

Much of child development is based on a specific progression of brain development, and thus is fairly predictable in typically developing children. Environmental factors can impact development as well (Board on Children, Youth and Families, 2002). For example, early experiences allow children exposure to activities to support learning. Early Head Start programs have shown beneficial developmental gains for children when starting school with improved Kindergarten readiness (Roggman, Boyce & Cook, 2009). The interplay of genetics and experiences impacts brain development and how a child learns.

Motor Development

There is a broad foundation of understanding of the attainment of specific developmental milestones. These general premises also apply to children who are deaf/HH with just a few different considerations. For example, motor development follows a specific progression. In general, children who are deaf/HH should follow a similar developmental trajectory. There are a limited number of reasons why this would not occur, including inner ear malformations, vestibular problems, or vision impairment. If a child who is deaf/HH does not have a rational reason for motor delay, further work-up and evaluation may be warranted for brain-based or muscular problems.

Motor development is an orderly and predictable sequence which is initially built on a foundation of multi-sensory input with touch and vision followed by proprioceptive and vestibular input. With motor movements repeated over and over, motor patterns are learned and next skills can be acquired. In general, motor skill development proceeds from head to toe and proximal to distal. Although, the continuum of motor development is not always smooth, there should be symmetry in motor movements and a general progression in skill development over time. When development of motor skills are atypical (i.e. not just delayed from the general skill progression), this can indicate more significant motor problems such as cerebral palsy.

Gross motor development is not a good proxy for cognitive development, as children with mild intellectual disability often have age appropriate early gross motor milestones and children with cerebral palsy may have significant motor impairment with intact problem-solving.

Cognitive Development

Cognitive capability is often more predictive of language capabilities as compared to the presence of a specific disability label (Meinzen-Derr, Wiley, Grether, & Choo, 2011). The exception to this premise is when a disability label has substantial impact on communication development such as in children with autism spectrum disorders. There are a number of theoretical frameworks for cognitive development in children. Piaget described an early foundational framework to provide an understanding of how children learn. In infancy and toddler years, children learn through sensori-motor exploration. Children then move into the pre-operational stage, relying on language as a way to learn about the world. Children understand the world through their own experiences. As children begin to approach early elementary ages, the concrete operational stage provides more logic and reasoning skills. This stage is followed by more abstract reasoning, including inductive and deductive reasoning, noted in the formal operations stage. (Augustyn & Zuckerman, 2009).

In general, using non-verbal measures of cognitive development are most appropriate for children who are deaf/HH when trying to understand cognitive capacity (Braden, 1992). For children who are deaf/HH, a strong language foundation is important for language-based problem solving. Thus, as higher abstract reasoning skills are required, the interplay of language and cognition on how children learn can allow us to develop an understanding of a child’s strengths and use this to support learning in areas which are more challenging.

Language Development

Language developmental trajectories for children who are deaf/HH present with more challenges in understanding when a child may be experiencing a language disorder which is not merely due to the degree of a child’s hearing loss. With the successful implementation of universal newborn hearing screening and improved early identification of hearing loss, children are obtaining language skills in the average range (Kennedy, McCann, Campbell, Law, Mullee, et al. 2006; Vehaert, Williams, Van Kerschaver & Desloovere, 2008). With this realization of improved language outcomes, we should be compelled to recognize when children are not making appropriate progress.

It is appropriate to consider key questions when determining next steps if a child is not making appropriate language progress such as: What is the impact of hearing on language development? Do our interventions allow access to language development? Is the communication environment able to support the child’s language needs? These questions provide guidance related to amplification, effectiveness of communication approach, and sufficiency of the language environment. In addition to these questions, one should consider whether there are unexplained or atypical patterns of language development. When a child has good comprehension but poor speech, consideration of an expressive language or speech sound disorder may be appropriate. Some children also have considerable language processing challenges. Monitoring development of non-verbal communication, gestures, and pragmatic language is also important and can be a red flag for broader social-communication problems. It is reasonable to expect that a child’s language level should approach their non-verbal cognitive capacity. However, if we are unaware of a child’s potential, our interventions could under-estimate appropriate goals for progress.

Appropriate Goals and Functional Skill

Development

Unfortunately, children who are deaf/HH plus are often compared to typically developing children who are deaf/HH. This comparison may not provide meaningful information to guide interventions and expectations. It may be more helpful to consider what hearing children with similar developmental abilities can achieve to assist in goal-setting and monitoring of progress. Most importantly, we should guide intervention for individual growth and not over-estimate or under-estimate a child’s capacity to learn.

The role of functional skill development and quality of life may be particularly relevant for this group of children. Functional auditory skills have been highlighted in children who are deaf/HH, but broader functional skill development has been largely ignored. Functional skills focus on broad-based whole child needs and are defined as a child’s ability to perform essential daily tasks in the areas of self-care (eating, dressing, bathing), mobility (changing positions, movement in space at home and community), and social cognition or social function (communicating basic needs, problem solving, social interaction with peers) (Msall, 1996).

This perspective can broaden our understanding of a child’s strengths and needs and help determine next areas for focusing intervention. Partnering with families to prioritize a child’s needs is important in children with complexities. The number of different interventions and therapies which may be suggested by professionals can be unrealistic and become overwhelming to families. This may detract from the family’s most pressing needs.

Partnerships and Team Building

Children who are deaf/HH plus benefit greatly from strong team collaboration. There can be barriers to effective team work, particularly if professionals work within different systems of care (educational settings, private therapy practices, hospital-based services). Strong collaboration can bring the team members in alignment and improve knowledge across disciplines.

Based on a focus group on the needs of children who are deaf/HH with autism spectrum disorders, participating professionals indicated a number of strategies which they found helpful in building a collaborative team across settings (Wiley, Meinzen-Derr, & Gustafsen, 2013). Although, they recognized that having time to spend in team meetings or in communication with other professionals is not a “billable service,” it is important to determine ways to effectively communicate among professionals and with families and include family participation in this communication system. Technology may serve as one mechanism to enhance communication, such as through a communication notebook, blog, or internet group. Families have also indicated their desire for strong and consistent communication from those working with their child (Wiley, Gustafson & Rozniak, 2013). Professionals also indicated they look for specific characteristics in team members, such as willingness to share information, flexibility, respect and sensitivity, awareness of limits, ability to think outside the box and be open-minded, and showing a commitment to follow-through.

Based on these results as well as the philosophy helpful to strive towards common goals, use active listening strategies, communicate effectively, and be open to trying new ideas and strategies. When thinking outside the box, if we recognize the limitations in knowledge and expertise, and are open to new ideas, we can enhance the care and interventions for these children with complex needs.

Conclusion

With the high rate of additional disabilities in children who are deaf/HH, it is important to recognize the developmental patterns that children exhibit over time. As development is ever-changing due to on-going brain development, monitoring progress and discussing concerns if development seems to be progressing at a different rate or atypical pattern than most children can help expand the services and strategies important for children to achieve their maximal capabilities. Partnering with families to identify supports and adaptations is particularly important for this complex group of children.

The quote from Candace Lindow-Davies, from the Minnesota Hands and Voices chapter, is an appropriate concluding reflection:

Deaf/hh Plus is meant to be a positive term, not in any way negative or insensitive to the child who has medical issues along with hearing loss. In fact, I see it as an “A+” or “B+,” meaning the child carries additional positive qualities. But it is a gift that needs to be carefully unwrapped. And it may not appear to be a gift when you first receive it. Time helps you appreciate, understand and unfold the possibilities. And the “Plus” most often means the child and family has added responsibilities and requires additional expertise. (http://www.cohandsandvoices.org/plus/index.html accessed 12/28/13)

References

Augustyn, M, F. & Zuckerman, B. (2009). Infancy and Toddler Years. In Developmental-Behavioral Pediatrics (4th Ed). W.B. Carey, A.C. Crocker, E.R. Elias, H. Feldman, & W.C. Crocker (Eds.). Saunders Elsevier: Philadelphia, PA.

Board on Children, Youth and Families, National Research Council and Institute of Medicine. (2002). From Neurons to Neighborhoods: The Science of Early Childhood Development. National Academy Press, Washington DC.

Boyle, C.A., Boulet, S., Schieve, L.A., Cohen, R.A., Blumbert, S.J., Yeargin-Allsopp, M., Visser, S., Kogan, M.D. (2011). Trends in the prevalence of developmental disabilities in US children, 1997-2008. Pediatrics, 127, 1034-1042.

Braden, JP. (1992). Intellectual assessment of deaf and hard of hearing people: a quantitative and qualitative research synthesis. School Psychology Review, 21, 83-95.

Centers for Disease Control and Prevention. Autism Spectrum Disorders, Data and Statistics. http://www.cdc.gov/ncbddd/autism/data.html/ Accessed December 27th, 2013.

Gallaudet Research Institute. (2011). Regional and National Summary Report of Data from the 2009-2010 Annual Survey of Deaf and Hard of Hearing Children and Youth. http://research.gallaudet.edu/Demographics/2010_National_Summary.pdf Accessed 12/27/13

Kancherla, V., Van Naarden, B., Braun, K., Yeargin-Allsopp, M. (2013). Childhood vision impairment, hearing loss and co-occurring autism spectrum disorder. Disability and Health Journal, 6, 333-342.

Kennedy, C.R., McCann, D.C., Campbell, M.J., Law, C.M., Mullee, M., Petrou, S., Watkin, P., Worsfold, S., Yuen, H.M., Stevenson, J. (2006). Language ability after early detection of permanent childhood hearing impairment. New England Journal of Medicine, 18;354 (20), 2131-2141.

Meinzen-Derr, J., Wiley, S., Grether, S., & Choo, D. (2011). Children with cochlear implants and developmental disabilities: a language skills study with developmentally matched hearing peers. Research in Developmental Disabilities, 32, 757-767.

Msall, M.E. (1996). Functional assessment in neurodevelopmental disability. In P.J. Accardo (Ed.), Developmental disabilities in infancy and children, (2nd Ed). Baltimore: Paul Brookes Publishing.

Roggman, L., Boyce, L. K., & Cook, G. (2009). Keeping kids on track: Impacts of a parenting-focused Early Head Start program on attachment security and cognitive development. Early Education & Development, 20(6), 920-941.

Vehaert, N, Willems, M, Van Kerschaver, E, Desloovere, C. (2008). Impact of early hearing screening and treatment on language development and education level: evaluation of 6 years of universal newborn hearing screening (ALGO) in Flanders, Belgium. International Journal of Pediatric Otorhinolaryngology, 72, 599-608.

Wiley, S., Meinzen-Derr, J., & Gustafsen, S. (2013). Autism in children who are deaf/hard of hearing. Presented at Early Hearing Detection and Intervention Meeting.

Wiley, S., Gustafson, S., & Rozniak, J. (2013). Needs of parents of children who are deaf/hard of hearing with autism spectrum disorder. Journal of Deaf Studies and Deaf Education (in press). online November 1, 2013; doi:10.1093/deafed/ent044.

C H A P T E R  S E V E N T E E N

An Update on Auditory Neuropathy Spectrum Disorder in Children

Gary Rance, Ph.D.

Abstract

Auditory neuropathy spectrum disorder (ANSD) is a form of hearing impairment in which cochlear (outer hair cell) function appears normal but afferent neural activity in the auditory pathway is disordered. It is now over 20 years since the first paediatric ANSD cases appeared in the literature and over 15 years since the disorder was identified in infant populations. In the ensuing period our understanding of ANSD’s causes, perceptual consequences and associated management challenges has developed considerably. This article provides an overview of the current literature and presents longitudinal outcome data for a group of affected children tracked from infancy through to early adulthood.

The term “auditory neuropathy” was coined in the mid-1990’s to describe a form of hearing impairment in which cochlear (outer hair cell) function appeared normal, but afferent neural activity in the VIIIth nerve and brainstem was disordered (Starr, Picton, Sininger, Hood, Berlin, 1996). However, the authors of this paper were not the first to show a mismatch between audiologic and electrophysiologic results. Kraus, Ozdamar, Stein, & Reed (1984), for example, had previously described a group of children for whom the auditory brainstem response (ABR) was mysteriously absent despite relatively normal sound detection. The Starr et al. study was, however, significant in that it was amongst the first to explore the nexus between neurology and audiology, presenting possible pathologic mechanisms and providing a template for evaluation of affected patients.

The clinical findings that distinguish “auditory neuropathy” from sensory-type hearing loss are the demonstration of pre-neural, cochlear activity, in conjunction with an inability to record evoked neural responses from the auditory pathway. Cochlear outer hair cell function in such cases is reflected by the presence of otoacoustic emissions (the acoustic by-product of the cochlear mechanical processes [Kemp, 1978]) and cochlear microphonics (the receptor potentials produced mainly by the polarization and depolarization of the cochlear outer hair cells [Dallos & Cheatham, 1976]). The auditory pathway disorder is suggested by the absence (or severe distortion) of electrical potentials from the auditory nerve and auditory brainstem (ABR). An example of this electrophsyiologic result pattern is shown in Figure 1.

Figure 1. Averaged EEG tracings for a 2 month old child with unilateral ANSD. The top tracing shows a normal ABR waveform for the left ear. The middle and lower tracings show cochlear microphonic responses but absent ABRs to unipolar stimuli at 80 dBnHL for the right ear. Asterisks denote the positive peaks in the CM waveform.

In the period since 1996, a number of alternative terminologies have been proposed to describe what Starr et al. referred to as “auditory neuropathy”. The most commonly used include auditory neuropathy/dys-synchrony (Berlin, Hood & Rose, 2001), auditory synaptopathy (Moser, Strenke, Meyer et al. 2006) and presynaptic and postsynaptic nerve disorder (Starr, Sininger & Pratt, 2000). The development of these descriptors reflects the fact that multiple pathological mechanisms may produce a common pattern of physiologic results. For example, the phenotype may result from specific loss of cochlear inner hair cells (Amatuzzi, Liberman & Northrop, 2001), disordered release of neurotransmitter by inner hair cell ribbon synapses (Wynne, Zeng, Bhatt, et al. 2013), differentiation accompanying loss of auditory nerve fibres (Starr, Michalewski, Zeng et al., 2003), neural dys-synchrony or conduction block as a result of demyelination of nerve fibres (Rance, Ryan, Bayliss et al. 2012a) and auditory nerve hypoplasia (Buchman, Roush, Teagle et al. 2006). As a result, the term auditory neuropathy spectrum disorder (ANSD) was developed to acknowledge this heterogeneity (Guidelines Development Conference, 2008).

Etiology of ANSD

While ANSD can occur in the absence of obvious health problems, the majority of reported cases (>70%) have presented with specific medical risk factors (for a review see Rance & Starr, 2011). Over the past decades numerous different aetiologies have been linked with the disorder. In children, ANSD is most commonly associated with transient neonatal insults such as hyperbilirubinaemia (Rance, Beer, Cone-Wesson et al., 1999; Shapiro, 2003) and oxygen deprivation (Rance et al. 1999; Sininger & Oba, 2001). In addition, greater awareness of the potential for auditory deficit in genetic, neurodegenerative conditions such as Charcot-Marie-Tooth disease and the mitochondrial disorders Friedreich ataxia and Leber’s Hereditory Optic Neuropathy, is also leading to an increase in early childhood diagnoses in these populations. Interestingly, it is becoming clear that the susceptibility of the auditory system to neural changes means that hearing deficits in individuals with these generalized neuropathic diseases often precede the onset of motor and other sensory symptoms (Starr et al. 1996; Rance et al. 2012a).

Other, less common, causes of paediatric ANSD include infectious processes (such as mumps and meningitis), inflammation (eg. siderosis), neoplasms (eg. acoustic neuroma), autoimmune disorders (such as Guillain Barre syndrome), nutritional disorders and genetic mutations affecting the optic/vestibular nerves and ribbon synapse function (for reviews see Rance, 2005; Starr et al., 2003; Starr & Rance, In Press).

Audiometric Presentation

Sound detection thresholds in children with ANSD vary across the audiometric range. For youngsters with congenital/perinatal aetiologies, average hearing levels are reasonably evenly distributed, with approximately 10% of cases enjoying sound detection within the normal range and a similar proportion presenting with profound hearing loss (Rance & Starr, 2011). Hearing levels in this congenital/perinatal population appear to be independent of whether or not the ABR is present (in distorted form) or absent. In children with ANSD due to neurodegenerative conditions, sound detection thresholds tend to be less affected with around 75% presenting with hearing levels in the normal range, and the remaining typically showing mild/moderate loss (Rance et al. 2012a; 2012c).

Fluctuating hearing levels have been consistently reported since the earliest reports involving children with ANSD (Rance et al. 1999; Sininger & Oba, 2001). While many cases describing day-to-day fluctuations have appeared in the literature, our experience suggests that significant hearing threshold variability is reasonably rare. Only around 5% of the children in the Australian cohort have shown consistent fluctuations in either audiometric levels or functional hearing ability over time.

In some instances, hearing level variability can be attributed to specific clinical changes. Starr, Sininger, Winter et al. (1998) for example, described a family group with mutations in the otoferlin gene which caused disruption of ribbon synaptic release with changes in core body temperature. These individuals showed dramatic ABR changes and temporary shifts in detection threshold when febrile. In most ANSD cases however, the mechanisms underlying hearing level fluctuation are unknown.

Auditory Processing

Disruption of the neural representation of sound in the VIIIth nerve and central pathways of ANSD listeners results in auditory processing deficits. Psychophysical studies investigating the ways in which this abnormality manifests have found a pattern of effects consistent with the physiologic profile of the disorder. For example, frequency resolution (the ability to separate frequency components in a complex sound) and intensity discrimination (the capacity to detect level differences) are largely dependent on cochlear-level processing and are typically unimpaired in children with ANSD (Rance, McKay & Grayden, 2004; 2012b; Kraus, Bradlow, Cheatham et al. 2000). In contrast, distortion of neural firing patterns in ANSD results in impaired temporal resolution (the ability to perceive brief signal changes over time) and disruption of the temporal aspects of pitch discrimination (Rance et al. 2004; Rance et al. 2012c; Zeng, Kong, Michaelewski, Starr, 2005).

In addition to suffering these monaural processing limitations, listeners with ANSD also show reduced ability to integrate binaural cues. That is, the temporally distorted signals conducted through the left and right auditory nerves cannot be effectively combined at the level of the superior olivary complex (lower brainstem) (Reidel & Kollmeier, 2002). One important consequence of this deficit is impaired localization ability. While localization based on inter-aural level differences (as required for high frequency sounds) is typically normal in ANSD listeners, sound direction judgements based on inter-aural timing differences (as for low-frequency stimuli) may be greatly affected (Starr et al. 1991; Zeng et al. 2005).

Functional Hearing (Speech Perception)

Speech understanding difficulties are the major functional consequence of ANSD. Most adults with the disorder have shown perceptual deficits greater than predicted from their behavioural audiogram (Rance, Fava, Baldock et al., 2008; Starr et al., 1996; Starr et al., 2000). Results in children are more variable. At best, young ANSD listeners show speech perception abilities equivalent to those of their peers with sensory hearing loss. At worst, they may demonstrate no functional ability at all despite, in many cases, enjoying complete access to the normal speech signal. Figure 2 shows this broad range of abilities and reflects the lack of relationship between open-set speech perception score and signal audibility in listeners with ANSD. As can be seen from this data, a high proportion of individuals (approximately 40%) show perceptual ability considerably poorer than the expected minimum for sensory hearing loss. It is worth noting, however, (given the generally pessimistic expectations that have developed for this population over the past few decades) that for listening in quiet at least, many children with ANSD do show significant functional hearing abilities.

Figure 2. Open-set speech perception scores (in quiet) plotted against average hearing level for listeners with ANSD. Data represents a meta-analysis of published findings as of December 2013. The filled data points are results from word-level assessment and the open points show sentence test findings. The grey area represents the 95% performance range for ears with sensory hearing loss (Yellin et al., 1989).

The mismatch between audibility and speech understanding in listeners with ANSD suggests that distortion of supra-threshold cues is the limiting factor in perceptual performance (Rance et al., 1999; 2002; 2012a; Starr et al., 1996; 2000). Speech perception ability for this population, in fact, appears more closely related to the level of neural disruption in the central auditory pathways and the resulting degree of temporal processing deficit (Kraus et al., 2000; Zeng et al., 2005).

Accurate neural representation of timing cues is a pre-requisite for speech understanding. In order to discriminate phonemes in running speech or even in single words, the listener must be able to identify the characteristic spectral shapes of individual phonemes, and importantly, be able to rapidly update this perception to track the flow of speech sounds. Recent work from our laboratory (Rance et al. 2008; 2010) has used transmission analysis techniques to identify speech perception error patterns in ANSD listeners and found that discrimination of temporal-based speech cues is a particular problem. Where individuals with sensory loss struggle to discriminate phonemes differing in frequency content (eg., /s/ and /f/), ANSD listeners consistently mistake speech sounds differing in their temporal characteristics such as the consonants /p/ and /b/ or /t/ and /d/ where voice-onset-time (VOT) is the major acoustic marker and vowels such as /i/ and /I/ where duration is the primary cue.

Speech Perception in Background Noise

All forms of permanent hearing loss impair figure/ ground perception (Rance, Barker, Mok et al 2007). Speech perception in noise problems for ANSD listeners with impaired sound detection thresholds are likely to be severe, but the underlying mechanisms may be difficult to tease out in such cases. More obvious are the deficits caused by ANSD in cases with normal or near normal hearing levels. As demonstrated in Figure 3, which shows speech perception findings for a group of ANSD children with relatively normal sound detection shows that even those individuals with reasonable perception in quiet can struggle to discriminate speech in noise at levels consistent with real-life listening conditions (0-5 dBSNR).

Figure 3. Open set speech perception scores for ANSD children with 4-frequency average hearing thresholds <30 dBHL. Shown are scores for CNC-words presented in quiet and at +10 dB, +5 dB and 0 dB signaltonoise ratios. The shaded area represents the 95% performance range for age-matched controls.

Figure 4. Hearing disability survey results for 26 school-aged children with ANSD and average hearing levels <30 dBHL (unfilled bars) and matched control subjects (filled bars). Individuals with ANSD reported significantly higher degrees of everyday listening and communication difficulty than healthy counterparts. “Perceived difficulty”, is the proportion of situations in which the subject struggled to hear/ communicate.

The consequent effects on everyday listening and general communication are reflected in Figure 4 which shows self-reported hearing disability ratings from the Abbreviated Profile of Hearing Aid Benefit (APHAB) questionnaire.

The mechanisms underlying figure/ground deficits in individuals with ANSD are not completely understood, but psychophysical studies have shown similarly exaggerated noise effects in both simultaneous (where the signal is presented within the noise) and non-simultaneous (where the noise occurs immediately before or after the signal) masking experiments (Kraus et al., 2000; Vinay & Moore, 2007; Zeng et al., 2005). As such, it appears that affected listeners are less able to separate sounds occurring both concurrently and successively. In an everyday listening context, where the level of background noise fluctuates, this temporal processing deficit might impair the listener’s ability to use brief gaps in the noise to access the speech signal and optimize understanding.

Another way in which listening in noise may be affected by ANSD involves spatial listening. In everyday circumstances where auditory signals emanate from multiple directions, sound localization cues may be used to separate a target signal (such as speech) from the competing noise (Micheyl, Carlyon, Gotshal et al., 2007). ANSD disrupts the ability to selectively attend to a particular voice based on it’s location and as a result, affected listeners typically require much lower noise levels than their normal peers to understand speech and communicate effectively (Rance et al, 2012b). This effect can be seen in Figure 5 which shows Spatial Advantage levels (dB) obtained using the Listening in Spatialized Noise Test (LiSN-S). Spatial advantage in this context is the difference in speech reception threshold (SRT) obtained when speech and noise stimuli are presented from different directions (90 apart) compared to when the speech and noise emanate from the same direction. As such, the advantage is a reflection of the listener’s ability to use inter-aural difference cues to localize the sound sources, and hence, improve perception. Not surprisingly, most of the ANSD children represented showed impaired spatial ability. Normal children, are typically afforded a 10-14 dB release from masking when signal and noise are spatially separated. Amongst children with ANSD, in contrast, spatial advantage varied considerably (depending on the degree of temporal processing deficit), but on average, youngsters with the disorder obtained only ≈6 dB improvement from separation of signal and noise sources. In real-world listening, this deficit may pose a significant threat to communication competence.

Figure 5. Spatial advantage scores (LiSN-S) plotted against AM detection threshold (temporal resolution ability) for children with ANSD and average hearing levels <30 dBHL. The shaded area represents the 95% performance range for matched controls.

Management of Children with ANSD Using Hearing Aids and Cochlear Implants

In the period since ANSD was first identified in children, opinion has fluctuated as to the efficacy of acoustic amplification and cochlear implantation as management options. As more data has become available there has been general (if not universal) acceptance that some children will derive most benefit from hearing aids and some will be best served by cochlear implantation. For a thorough review see Roush, Frymark, Venedtiktov, & Wang (2011).

Hearing Aid Amplification

As the basic function of conventional hearing aids is to amplify acoustic signals, they can make environmental sounds and speech louder (allowing improved access to ANSD listeners with impaired sound detection), but they cannot dramatically improve the clarity of a temporally distorted signal. Amplification outcomes have been mixed with some children (typically those with lesser degrees of temporal disruption) responding well and showing aided speech perception abilities consistent with their sensorineural counterparts (Rance et al., 2002; Roush et al, 2011). In many youngsters (and almost all reported adults), however, conventional amplification has been of little or no benefit (Berlin, Hood, Morlet et al., 2010; Rance, 2005; Starr et al., 1996). As a result, Digital Signal Processing (DSP) hearing aids with strategies designed to accentuate temporal cues in the acoustic signal have been considered (Narne & Vanaja, 2008; Zeng, Oba & Starr, 2001) and may, in the future, improve outcomes in some cases.

Cochlear Implantation

The literature regarding CI outcomes in ANSD children has followed an interesting course of the past 15 years. Early reports (Miyamoto, Iler-Kirk, Renshaw, Hussain et al., 1999; Rance et al. 1999) described poor CI outcomes in a (small) number of cases and advised against implantation arguing that perception would likely be impaired as the signal provided by the device must still pass through a disordered neural system. Then followed a period (in the 2000’s) in which CI results were almost universally positive with a series of publications showing speech perception benefits in ANSD cases consistent with those of young implantees with sensory loss (Madden, Rutter, Hilbert, Greinwald, Choo, 2002; Mason, DeMichele, Stevens, Ruth, Hashisaki, 2003; Shallop, 2002; Teagle, Roush, Woodward et al., 2010; Trautwein, Shallop, Fabry, Friedman, 2001; Zeng & Liu, 2006). More recently, however, expectations have been tempered slightly with a number of studies reporting poorer than anticipated speech perception results (Neary & Lightfoot, 2012; Roush et al. 2011), again raising the possibility that some forms of ANSD can affect the neural integrity of the CI-elicited signal and highlighting the need for diagnostic procedures that can better differentiate between sites of lesion. While cochlear implantation remains the intervention option of choice for most children with ANSD, clinicians and particularly families need to be aware of the possibility of unexpected outcomes in this population.

The ways in which perception is improved by the CI in individuals with ANSD are currently under investigation. Significantly, most subjects with cochlear implants show normal ABRs to electrical stimulation suggesting either an increase in the number of neural elements contributing to the evoked response (perhaps as a result of by-passing peripheral abnormality when stimulating the spiral ganglion directly) or an improvement in the synchrony of neural firing (perhaps reflecting the fact that the electrical stimuli produced by CIs is in the form of discrete pulse trains which more efficiently generate synchronous activity).

Long-Term Outcomes

While the relative benefits of amplification and cochlear implantation on speech perception ability have been reasonably well documented, the effects of these interventions on oral language development, has been underexplored (Roush et al. 2011). In 2009 we published cross-sectional language data for a (small) group of school-aged children which suggested no difference in pronunciation abilities (Diagnostic Evaluation of Articulation and Phonology [DEAP]) and receptive vocabulary (Peabody Picture Vocabulary Test [PPVT]) (Rance & Barker 2009) between aided and CI groups. More recently, Ching, Day, Dillon et al. (2013) has shown similar results in a larger cohort of children tested at 3 yrs of age. In our clinic (University of Melbourne) we manage a cohort of children diagnosed with ANSD in the early

1990’s and have longitudinal data across a number of domains (auditory processing, speech perception, hearing disability, educational progress etc) from infancy to (in some cases) early adulthood. Figure 6 shows longterm receptive language outcomes for ANSD children managed with cochlear implants (panel A) and hearing aids fit according to the NAL procedure (Byrne & Dillon, 1986) (panel B). Mean rates of language growth for the two intervention categories were equivalent (P>0.05) and children in both groups showed a developmental course only mildly delayed relative to that of normally hearing youngsters. As such, the findings suggest that good longterm oral language development is a realistic expectation for many children with ANSD – provided they are offered the management option most appropriate to their abilities. The aided participants in Figure 6 represent a biased sample. Many of the ANSD children in our clinical cohort who were originally fit with hearing aids, were subsequently referred for CI when it became clear that they were not showing adequate progress with amplification. As such, the children who remained hearing aid users reflect the subset that was able to use their audition to develop good oral language. A significant research challenge for the future is to develop clinically applicable procedures that can measure a child’s auditory capacity at a young age so that management decisions can be made in a timely fashion.

Figures 6A & 6B. Receptive language development (PPVT) for children with ANSD. Data points represent the child’s equivalent language age plotted against chronological age at each assessment point. Panel A shows findings for 5 children managed with either monaural or binaural cochlear implants. Panel B shows findings for 6 children managed with conventional hearing aids. The diagonal line represents the expected rate of language growth for normally hearing/developing children.

Summary

Our understanding of ANSD, it’s causes, and particular perceptual consequences has improved considerably over the past two decades. The variability of presentation continues, however, to raise clinical questions and it is clear that a “one size fits all” approach is not appropriate for this population. Development of a knowledge-base that can underpin management decision-making remains a significant goal for the future.

References

Amatuzzi M, Liberman M.C. & Northrop C. (2001). Selective inner hair cell loss in prematurity: a temporal bone study of infants from a neonatal intensive care unit. Journal of the Association for Research in Otolaryngology, 12(5), 595-604.

Berlin, C.I., Hood, L.J., Morlet, T. et al. (2010). Multi-site diagnosis and management of 260 patients with auditory neuropathy/dys-synchrony (auditory neuropathy spectrum disorder). International Journal of Audiology, 49, 30-43.

Berlin, C. I., Hood, L. J. & Rose, K. (2001). On renaming auditory neuropathy as auditory dys-synchrony. Audiology Today, 13, 15–17.

Buchman, C.A., Roush, P.A., Teagle, H.F.B., Brown, C., Zdanski, C.J., Grose J.H. (2006). Auditory neuropathy characteristics in children with cochlear nerve deficiency. Ear and Hearing, 27, 399-408.

Byrne, D. & Dillon, H. (1986). The National Acoustics Laboratories (N.A.L.) new procedure for selecting the gain and frequency response of a hearing aid. Ear and Hearing, 7, 257-265.

Ching, T., Day, J., Dillon, H. et al. (2013). Impact of the presence of auditory neuropathy spectrum disorder (ANSD) on outcomes of children at 3 years of age. International Journal Audiology, 52, 55-64.

Dallos, P. & Cheatham, M. A. (1976). Production of cochlear potentials by inner and outer hair cells. Journal of the Acoustical Society of America, 60, 510–512. Guidelines Development Conference on the Identification and Management of Infants with Auditory Neuropathy. (2008). www.thechildrenshospital.org/conditions/speech/danielscenter/ANSD-Guidelines. aspx.

Kemp, D. T. (1978). Stimulated acoustic emission from the human auditory system. Journal of the Acoustical Society of America, 64, 1386–1391.

Kraus N., Ozdamar O., Stein L. & Reed N. (1984). Absent auditory brain stem response: peripheral hearing loss or brain stem dysfunction. Laryngoscope,94(3), 400-406.

Kraus, N., Bradlow, A.R., Cheatham, J., Cunningham, C.D., King, D.B., Koch, T.G., Nicol, T.J., McGee, L.K., Stein, L.K., Wright, B.A. (2000). Consequences of neural asynchrony: A case of auditory neuropathy. Journal of the Association for Research in Otolaryngology, 1(1), 33-45.

Madden, C., Rutter, M., Hilbert, L., Greinwald, J., Choo, D. (2002). Clinical and audiological features in auditory neuropathy. Archives of Otolaryngology-Head and Neck Surgery, 128, 1026–1030.

Mason, J. C., De Michele, A., Stevens, C., Ruth, R., Hashisaki, G. (2003). Cochlear implantation in patients with auditory neuropathy of varied etiologies. Laryngoscope, 113(1), 45–49.

Micheyl C., Carlyon R.P., Gutshalk A. et al. (2007). The role of auditory cortex in the formation of auditory streams. Hearing Research, 229, 116-131.

Miyamoto, R. T., Iler Kirk, K., Renshaw, J., Hussain, D. (1999). Cochlear implantation in auditory neuropathy. Laryngoscope, 109, 181–185.

Moser T., Strenke N., Meyer A. et al. (2006). Diagnosis and therapy of auditory synaptopathy/neuropathy. Hals-Nasen-Ohrenheikunde, 54(11), 833-839.

Narne, V. K. & Vanaja, C. S. (2008). Effect of envelope enhancement on speech perception in individuals with auditory neuropathy. Ear and Hearing, 29, 45–53.

Neary W. & Lightfoot G. (2012). Auditory neuropathy spectrum disorder: Examples of poor progress following cochlear implantation. Audiological Medicine, 10, 143–150.

Rance, G. (2005). Auditory neuropathy spectrum disorder and it’s perceptual consequences. Trends in Amplification, 9(1), 1–43.

Rance G. & Barker E. (2009). Speech and language outcomes in children with auditory neuropathy/ dys-synchrony managed with either cochlear implants or hearing aids. International Journal of Audiology, 48, 313-320.

Rance, G., Barker, E., Mok, M., Dowell, R., Rincon, A., Garratt, R. (2007). Speech perception in noise for children with auditory neuropathy/dys-synchrony type hearing loss. Ear and Hearing, 28(3), 351–360.

Rance, G., Beer, D.E., Cone-Wesson, B., Shepherd R.K., Dowell, R.C., King, A.K., Rickards, F.W., Clark, G.M. (1999). Clinical findings for a group of infants and young children with auditory neuropathy. Ear and Hearing, 20, 238-252.

Rance, G., Cone-Wesson, B., Wunderlich, J., Dowell, R.C. (2002). Speech perception and cortical event related potentials in children with auditory neuropathy. Ear and Hearing, 23, 239-253.

Rance, G., Corben, L., Barker, E., Carew, P., Chisari, D., Rogers, M., Dowell, R., Jamaluddin, S., Bryson. R., Delatycki, M. (2010). Auditory perception in individuals with Friedreich Ataxia. Audiology & Neurotology, 15, 229-240.

Rance, G., Fava, R., Baldock, H., Chong, A., Barker, E., Corben, L., Delatycki, M. (2008). Speech perception ability in individuals with Friedeich Ataxia. Brain, 131, 2002-2012.

Rance, G., McKay, C. & Grayden, D. (2004). Perceptual characterisation of children with auditory neuropathy. Ear and Hearing, 25, 34-46.

Rance G., Ryan M.M., Bayliss K., Gill K., O’Sullivan C. & Whitechurch M. (2012a). Auditory function in children with Charcot-Marie-Tooth Disease. Brain, 135, 1412-1422.

Rance G., Ryan M.M., Carew P., Corben L.A., Yiu E., Tan J. and Delatycki M.B. (2012b). Binaural speech processing in individuals with auditory neuropathy. Neuroscience, 226: 227-235.

Rance G., Corben L.A. & Delatycki M.D. (2012c). Auditory processing deficits in children with Friedreich ataxia. Journal of Childhood Neurology, 27(9), 1197-1203.

Rance, G. & Starr, A. (2011). Auditory neuropathy/ dys-synchrony. In Comprehensive Handbook of Pediatric Audiology. R.C. Seewald & M.A. Tharpe (Eds.), Chapter 13, (pp. 225-242). Plural Publishing, San Diego.

Riedel H. & Kollmeier B. (2002). Auditory brain stem responses evoked by lateralized clicks: is lateralization extracted from the human brain stem? Hearing Research, 163, 12-26.

Roush, P., Frymark, T., Venedtiktov, R. & Wang, B. (2011). Audiologic management of auditory neuropathy spectrum disorder in children: A systematic review of the literature. American Journal of Audiology, 20, 159–170.

Shallop, J. K. 2002. Auditory neuropathy spectrum disorder in adults and children. Seminars in Hearing,

23(3): 215–223.

Shapiro S.M. 2003. Bilirubin toxicity in the developing nervous system. Pediatr Neurol 29(5):410-21

Sininger, Y.S. and Oba, S. 2001. Patients with auditory neuropathy: Who are they and what can they hear? In Y.S. Sininger & A. Starr (Eds.), Auditory Neuropathy (pp. 15-36). San Diego: Singular Publishing.

Starr, A., McPherson, D., Patterson, J., Don, M., Luxford, W., Shannon, R., Sininger, Y., Tonakawa, L. and Waring, M. 1991. Absence of both auditory evoked potentials and auditory percepts dependent on timing cues. Brain, 114: 1157-1180.

Starr, A., Michalewski, H. J., Zeng, F. G., Fujikawa-Brooks, S., Linthicum, F., Kim, C. S., et al. 2003. Pathology and physiology of auditory neuropathy with a novel mutation in the MPZ gene. Brain, 126:1604–1619.

Starr, A., Picton, T.W., Sininger, Y.S., Hood, L.J. and Berlin, C.I. 1996. Auditory Neuropathy. Brain, 119 (3): 741-753.

Starr A. and Rance G. (In Press). Auditory Neuropathy. In Human Auditory System. GG Celesia, G Hickok (Eds). Elsevier Publishing.

Starr, A., Sininger, Y.S. and Pratt, H. 2000. The varieties of auditory neuropathy. J Basic & Clin Physiol Pharmacol, 11(3): 215-230.

Starr, A., Sininger, Y. S., Winter, M., Derebery, M. J., Oba, S. and Michalewski, H. J. 1998. Transient deafness due to temperature–sensitive auditory neuropathy. Ear and Hearing, 19: 169–179.

Teagle, H., Roush, P., Woodward, J. S. et al. 2010. Cochlear implantation in children with auditory neuropathy spectrum disorder. American Journal of Audiology, 20: 159–170.

Trautwein, P., Shallop, J., Fabry, L. and Friedman, R. 2001. Cochlear implantation of patients with auditory neuropathy. In Y. S. Sininger, & A. Starr (Eds.), Auditory neuropathy (pp. 203–232). San Diego, CA: Singular Publishing.

Vinay and Moore, B.C.J. 2007. Ten(HL)-test results and psychophysical tuning curves for subjects with auditory neuropathy. International Journal of Audiology, 46(1): 39-46.

Wynne D.P., Zeng F.G., Bhatt S., Michalewski H.J., Dimitrijevic A. and Starr A. 2013. Loudness adaptation accompanying ribbon synapse and auditory nerve disorders. Brain, 136( 5): 1626-38.

Yellin, M.W., Jerger, J. and Fifer, R.C. 1989. Norms for disproportionate loss in speech intelligibility. Ear Hear 10(4): 231-234.

Zeng, F.-G., Kong, Y.,-Y., Michaelewski, H.J. and Starr, A. 2005. Perceptual consequences of disrupted auditory nerve activity. J Neurophysiol, 93: 3050-3063.

Zeng, F.-G. and Liu, S. 2006. Speech perception in individuals with auditory neuropathy. J Speech Lang Hear Res, 49: 36.

Zeng, F.-G., Oba, S. and Starr, A. 2001. Supra threshold processing deficits due to desynchronous neural activities in auditory neuropathy. In Physiological and Psychophysical bases of Auditory Function, pp.

365-372. D.J. Breebaart, A.J.M. Houstma, A. Kohlrausch, V.F. Prijs & R. Schoonhoven (Eds.), Shaker Publishing BV, Maastricht, Netherlands.

C H A P T E R  E I G H T E E N

Decision Support Guide for Hearing Aid Use

in Infants and Children with Minimal/Mild

Bilateral Hearing Loss

Marlene P. Bagatto, Au.D, Ph.D.

Anne Marie Tharpe, Ph.D.

Abstract

Evidence suggests that the majority of children with minimal/mild, permanent, bilateral hearing loss (MBHL) are at greater risk for academic, speech-language and social-emotional difficulties than their normal hearing peers. It is reasonable to assume that appropriate and timely hearing technology could mitigate the negative impact of such losses. However, there currently is no way to predict which children will experience difficulties and which will follow a typical course of development. This makes early intervention recommendations unclear, leading to several pediatric amplification guidelines recommending hearing aids to these children on a case-by-case basis. The absence of more specific management guidelines presents a challenge to pediatric audiologists who work with families of infants and children with MBHL as they lack the evidence to support clear amplification recommendations. Although comprehensive management of infants and children with MBHL is multifaceted, this paper will focus on the consideration of hearing aids. Specifically, a process is described that is intended to facilitate appropriate case-by-case reasoning when considering amplification for infants and children identified with MBHL.

For the past several decades, evidence has accrued suggesting that a large percentage of children with minimal and mild degrees of bilateral permanent hearing loss (MBHL) have psychoeducational and behavioral difficulties (Bess, Dodd-Murphy & Parker, 1998; Bess & Tharpe, 1984; Most, 2004; Wake, Hughes, Poulakis, Collins & Rickards, 2004). It is reasonable to assume that appropriate and timely hearing technology could assuage the negative impact of such losses. Toward that end, several hearing technology options have been recommended for these children (Tharpe, Ricketts & Sladen, 2003; Tharpe, Eiten & Gabbard, 2008) but evidence-based guidance regarding these fitting practices has been lacking. Extant consensus-based and evidence-based protocols and guidelines have consistently recommended the selection of amplification for children with MBHL on a case-by-case basis (e.g., Bagatto, Scollie, Hyde & Seewald, 2010) with consideration for whether the degree of loss could interfere with normal development (e.g., American Academy of Audiology [AAA], 2013). However, additional guidance has not been forthcoming. This lack of guidance has resulted in uncertainty about hearing aid recommendations with this group of children (Fitzpatrick, Whittingham & Durieux-Smith, 2013).

A decision support guide is provided herein that is designed to help clinicians compile information that will assist them in deciding whether an infant or child five years of age and younger with MBHL is a good candidate for hearing aids. The rationale for this work is to reduce clinician uncertainty when making hearing aid recommendations for these children. Furthermore, the proposed guide is based on several assumptions. First, it is assumed that audiologic certainty has been obtained. That is, there has been reliable determination of degree, configuration and type of hearing loss for at least two frequencies in each ear (AAA, 2013). Another assumption is that all infants and children with MBHL who are provided with personal hearing aids are also considered candidates for frequency-modulated (FM) technology. Such technology is known to improve listening in environments where distance, noise and reverberation are an issue (Lewis & Eiten, 2011). Guidelines for remote microphone assistance technologies for children and youth are provided in a recent document from the American Academy of Audiology (2008) so will not be discussed herein. Third, the family must be well-informed of the potential benefits and limitations of hearing aids for their infant or child with MBHL. A family-centred approach to decision making is central to the intervention process. Finally, the decision support guide provided in this document is not intended to be comprehensive, but rather provide guidance to audiologists when considering hearing aids for infants and children with MBHL. Selection of hearing aids is but one part of comprehensive and fluid management of childhood hearing loss, which should also include periodic, comprehensive monitoring of hearing, speech, language and family-focused counseling (Joint Committee on Infant Hearing [JCIH], 2007).

Several elements have been included for consideration in the proposed guide to support clinical decision making (Figure 1).

These factors include:

1) configuration and degree of hearing loss;

2) ear canal and earmold acoustics;

3) hearing aid gain/output and noise floor;

4) child factors; and

5) family factors.

Details about each of these factors are described in the following sections.

Figure 1: Factors to consider when determining the appropriateness of a hearing aid for an infant or child with MBHL.

Configuration and Degree of Hearing

Loss

Minimal/mild bilateral hearing loss in children is defined as (Bess et al., 1998):

a) Permanent Mild Bilateral: pure tone average (500, 1000, 2000 Hz) between 20 and 40 dB HL

b) Permanent High Frequency: pure tone thresholds > 25 dB HL at two or more frequencies above 2000 Hz

These definitions are supported by the National Workshop on Mild and Unilateral Hearing Loss (2005) and are used to categorize different configurations of MBHL: flat and high frequency. The degree of hearing loss in the high frequencies can range from mild to profound for the purposes of this guide. With both configurations, the hearing losses should be defined in each ear by at least one low and one high frequency threshold, as is required by several pediatric hearing aid fitting protocols (e.g., AAA, 2013; Bagatto et al., 2010).

Ear Canal and Earmold Acoustics

The external ears of infants and young children are significantly smaller than those of adults (Bagatto, Scollie, Seewald, Moodie & Hoover, 2002; Feigin, Kopun, Stelmachowicz, & Gorga, 1989; Kruger, 1987) and the size changes as the child grows. This growth has substantial implications when defining accurate hearing levels as well as when measuring hearing aid output in devices that are calibrated with reference to an average adult ear canal. It is therefore essential to measure the real-ear-to-coupler difference (RECD) in infants with MBHL and use this measurement to convert the audiogram (referenced in dB HL) to sound pressure level (SPL; Seewald & Scollie, 1999). This will provide a more accurate description of the infant’s hearing levels that can be directly compared to hearing aid output on an SPL scale. As the infant grows, the ear canal changes thus changing the SPL delivered to the ear. Therefore, the RECD must be measured on a regular basis over time for a given infant so that changes to the ear canal acoustics can be applied when comparing sequential audiograms and defining the amount of output provided by a hearing aid.

Small infant ears can also impact the earmold acoustics of a potential hearing aid fitting for a child with MBHL. In many instances, the ear canals of infants and young children are too small to accommodate a vent in the earmold. An earmold vent provides an outlet for sound up to about 1000 Hz, depending on vent diameter (Dillon, 2012). The ability to provide venting has implications for some degrees and configurations of MBHL where amplification may not be required (see Figure 2).

Figure 2: An example of unaided speech (shaded region) audibility for a child with a mild high frequency hearing loss (open circles). The x-axis is frequency (Hz) and the y-axis is sound pressure level (SPL) at the eardrum. Note that no amplification is required in the low frequency region, but is needed in the high frequency region. A vented earmold will help reduce the impact of upward spread of masking.

An occluding earmold will not allow sound to escape in the low-frequency region thus providing amplification in an area where little or no hearing aid gain is needed. This may interfere with the hearing aid benefit necessary in the high frequency region because of upward spread of masking. When considering a hearing aid recommendation for infants and children with MBHL, it is important to weigh the implications of potentially masked high frequency speech cues resulting from an unvented earmold compared to the potential high frequency benefit provided with the same fitting. The small ear canals of infants impact the assessment of hearing sensitivity in this population as well as the ability to provide a vented earmold in the hearing aid fitting. As such, ear canal size and earmold acoustics are important factors when considering whether to pursue a hearing aid fitting with an infant or child with MBHL.

Hearing Aid Gain/Output and Noise

Floor

Confirmation that a broad frequency range of speech is audible at various input levels and ensuring loud inputs to the hearing aids are comfortable for the infant are explicit goals of a pediatric hearing aid fitting, regardless of degree of hearing loss. Easy and safe access to speech supports a child’s development of language. This is achieved by employing coupler-based verification techniques and RECD measures to assess the output of the hearing aid to be provided. In the case of MBHL, minimal hearing aid gain may be required and could interact with the low-level hearing aid noise floor (Figure 3). Consequently, the noise could be heard by the child and may mask speech sounds amplified by the hearing aid. With venting, an improvement in performance may result. However, careful consideration of hearing aid benefit compared to the unaided condition is necessary when considering a hearing aid for an infant or child with MBHL.

Consideration of the Speech Intelligibility Index (SII; ANSI S3.5-1997) values during verification of hearing aids means that support is given on whether providing a hearing aid will result in benefit compared to the unaided condition.

Figure 3: An example of a low-gain hearing aid fitting. The x-axis is frequency (Hz) and the y-axis is sound pressure level (SPL) at the eardrum. The SII values for average aided speech is 94% and the SII values for soft aided speech are 89%.

The SII values shown in Figure 3 for both the unaided and aided conditions are high (89% and 94% respectively). At these levels, ease of listening is more prominently impacted than performance (Scollie, 2008). Speech audibility may be improved for some children with MBHL without hearing aids by increasing the vocal effort of the talker, decreasing speaker-listener distance, and reducing background noise. Conducting appropriate outcome measurements that evaluate access to speech in various conditions (e.g., Ling 6(HL) Detection Task; Scollie, Glista, Tenhaaf, Dunn, Malandrino, Keene & Folkeard, 2012) might provide important information when considering providing hearing aids to an infant or child with MBHL.

Child Factors

The individual characteristics of a child with MBHL and his or her listening environment are an integral part of hearing aid management decisions. Evidence suggests that 25 to 40% of children with hearing loss have additional handicapping conditions that might further impact their capacity to develop normally (Tharpe, FinoSzumski & Bess, 2001). The presence of comorbidity can result in poorer functional auditory outcomes when compared to typically-developing children who have been fitted with hearing aids (Bagatto, Moodie, Malandrino, Richert, Clench & Scollie, 2011).

Figure 4: An example of LittlEARS scores (y-axis) by age (x-axis) for children with unaided MBHL. The solid line represents the average LittlEARS scores for normal hearing children and the dashed lines are the upper and lower 95% confidence intervals. The diamonds represent individual child’s LittlEARS scores. The diamonds that are circled are children with comorbidities.

For example, as seen in Figure 4, the auditory development of children with MBHL who have not been provided with hearing aids was assessed using the LittlEARS Auditory Questionnaire (Tsiakpini, Weichbold, Kuehn-Inacker, Coninx, D’Haese & Almadin, 2004). Those children who did not meet auditory development milestones (represented by the encircled scores) were noted to have disabilities in addition to hearing loss that impacted their auditory development. It is therefore important to conduct outcome measures in the aided as well as unaided conditions to inform the decision to recommend hearing aids for infants and children with MBHL. Alternative functional auditory assessments are available for clinical use and have been described for use with infants and young children (e.g., Bagatto, Moodie, Seewald, Bartlett & Scollie, 2011; Tharpe & Flynn, 2005).

Another factor to consider is the ambulatory status of the child, as opposed to just the age of a child, when contemplating hearing aids for an infant or child with MBHL. Whether a child is crawling, walking, or otherwise able to distance him/herself from the talker of interest is a relevant consideration because distance will directly impact the SII as well as signal-to-noise ratio. A tool that takes speaker-listener-distance into consideration is the Situational Hearing Aid Response Profile (SHARP; Brennan, Lewis, McCreery, Creutz & Stelmachowicz, 2013). The SHARP is a software application used to characterize the audibility of speech signals across a wide range of realistic listening situations with varying acoustic environments. Applying this tool to a hearing aid selection procedure can provide useful information to guide case-by-case reasoning when managing MBHL in children. Figure 5 provides SHARP examples of the audibility of speech for a given hearing loss in SPL at various levels and distances and provides SII values to inform the amount of speech audibility. As demonstrated, if the source of speech is close to the child (e.g., hip position), a hearing aid may not be required due to the high SII value. However, for distant sounds (e.g., average conversation at four meters) the ambulatory abilities of the child matters.

One final child factor for consideration is the child’s listening environment. This can be described as the acoustics of a room (noisy versus quiet) or a group or a non-group situation. The environment in which the child spends most of his/her waking hours should be considered when managing infants and children with MBHL. For example, some infants will be in a quiet home setting throughout the day while others may be in a daycare or school setting where signal-to-noise ratios are not ideal.

Figure 5: Examples of the audibility of speech for a given hearing loss in SPL at various levels and distances for a child with MBHL. SII values are provided to inform the index of speech audibility.

The presence of distance, noise and reverberation in the child’s listening environment impacts development and performance in several areas. Listening in the presence of background noise can affect the development of speech and language skills, social-emotional functioning and educational performance in children with and without hearing loss (Lewis & Eiten, 2012). It has been demonstrated that children with MBHL have better speech perception ability in noise when wearing an FM system compared to the unaided condition (Tharpe et al., 2003). Remote microphone hearing assistance technologies can provide a clear, audible input signal and reduce the impact of noise and reverberation. They are available in a variety of configurations (e.g., ear-level FM only, sound field) regardless of whether the child with MBHL uses hearing aids (AAA, 2008). The child’s listening environment is an important consideration when selecting hearing technology for children with MBHL.

Family Factors

Another important aspect to the management of children with MBHL is their family. Their readiness and motivation to proceed with the exploration of hearing aids are essential to this process. A family-centred approach is a guiding principle underlying the management of children with hearing loss and should be applied when considering hearing aids for infants and children with MBHL. Caregivers should be apprised of the benefits and limitations of a hearing aid fitting for their child and, where possible, these should be illustrated through the use of outcome measures (e.g., setting throughout the day while others may be in a daycare or school setting where signal-to-noise ratios are not ideal. The presence of distance, noise and reverberation in the child’s listening environment impacts development and performance in several areas. Listening in the presence of background noise can affect the development of speech and language skills, social-emotional functioning and educational performance in children with and without hearing loss (Lewis & Eiten, 2012). It has been demonstrated that children with MBHL have better speech perception ability in noise when wearing an FM system compared to the unaided condition (Tharpe et al., 2003). Remote microphone hearing assistance technologies can provide a clear, audible input signal and reduce the impact of noise and reverberation. They are available in a variety of configurations (e.g., ear-level FM only, sound field) regardless of whether the child with MBHL uses hearing aids (AAA, 2008). The child’s listening environment is an important consideration when selecting hearing technology for children with MBHL.

LittlEARS, Ling 6(HL) Detection Task). Providing hearing aids on loan to the family for a trial period provides a real-world demonstration that can be invaluable in this process. A supportive and fluid approach to case management will facilitate careful case-by-case reasoning when combined with the previous factors discussed.

Decision Support Guide

With the above factors in mind, a decision support guide in the form of a flow chart has been created to assist clinicians in determining the appropriateness of a hearing aid recommendation for individual children with MBHL (Figure 6). This guidance is based on the definitions of MBHL for both flat and high frequency configurations (Bess et al, 1998) and is intended for children from birth to five years of age. Whether a hearing aid recommendation is pursued or not, caregiver counseling and close monitoring of the child’s development and auditory performance is recommended as changing circumstances could support fitting at a later time in the child’s life.

Figure 6: Decision support guide for clinicians considering hearing aids for infants and children with MBHL.

Further information is needed about the impact of hearing aid use in infants and children with MBHL in their early years. Continuing education for clinicians on how to make decisions about the management of infants and children with MBHL is essential. It is expected that this guide will evolve as it is used by pediatric audiologists but, in the meantime, it serves as a reminder for clinicians to gather the necessary evidence to support their management decisions.

Acknowledgements

The authors gratefully acknowledge the input of Christine Brown, Frances Richert, Susan Scollie and the pediatric audiologists at the Vanderbilt Bill Wilkerson Center during the development of this guide.

Summary

A significant number of children with MBHL experience difficulties with language, academic, and psychosocial development (Bess et al, 1998; Hicks & Tharpe, 2002; Most, 2004; Wake et al., 2004). Hearing aid management decisions for these children are not well-established, which results in clinical uncertainty (Fitzpatrick et al., 2013). We have proposed a decision support guide in the form of a flow chart to support clinical decision making when dealing with individual infants and children with MBHL and their families. We have described many factors to consider when making case-by-base decisions with this population. Regardless of whether a hearing aid has been recommended for a specific child, it is important to continue to monitor that child’s auditory as well as functional development. As the child’s ear canal grows and changes, the acoustic properties change which impact hearing thresholds and the gain requirements of the hearing aids to be fitted. In addition, children in the first three years of life often experience otitis media with effusion that can impact hearing thresholds. Therefore, including immittance measures in audiological monitoring protocols is vital. Finally, audiologists should monitor the child’s functional auditory abilities, their speech-language skills and educational progress as part of routine evaluation, whether or not hearing aids are provided. Intervention strategies should be adjusted as required, in consultation with the family, as new evidence is gathered.

References

American Academy of Audiology. (2013). Pediatric Amplification Guidelines. Retrieved from http:// www.audiology.org/resources/documentlibrary/ Documents/PediatricAmplificationGuidelines.pdf

American Academy of Audiology. (2008). Clinical Practice Guidelines: Remote Microphone Hearing Assistance Technologies for Children and Youth From Birth to 21 Years. Retrieved from http://www.audiology.org/resources/documentlibrary/Documents/ HAT_Guidelines_Supplement_A.pdf

American National Standards Institute. (1997). Methods for the calculation of the Speech Intelligibility Index (ANSI S3.5-1997). New York, NY: Acoustical Society of America.

Anderson, K., Goldstein, H., Colodzin, L., & Iglehart, F. (2005). Benefit of S/N enhancing devices to speech perception of children listening in a typical classroom with hearing aids or a cochlear implant. Journal of Educational Audiology, 12, 14–28.

Bagatto, M.P., Moodie, S.T., Malandrino, A.C., Richert, F.M., Clench, D.A., & Scollie, S.D. (2011). Trends in Amplification, 15(1), 57-76.

Bagatto, M.P., Moodie, S.T., Seewald, R.C., Bartlett, D.J., & Scollie, S.D. (2011). A critical review of audiological outcome measures for infants and children. Trends in Amplification, 15(1), 23-33.

Bagatto, M., Scollie, S., Hyde, M., & Seewald, R. (2010). Protocol for the provision of amplification within the Ontario Infant Hearing Program. International Journal of Audiology, 49, S70-S79.

Bagatto, M.P., Scollie, S.D., Seewald, R.C, Moodie, K.S., & Hoover, B.M. (2002). Real-ear-to-coupler difference predictions as a function of age for two coupling procedures. Journal of the American Academy of Audiology. 13(8), 407-415.

Bess, F.H., Dodd-Murphy, J., & Parker, R.A. (1998). Children with minimal sensorineural hearing loss: Prevalence, education performance, and functional status. Ear & Hearing, 19(5), 339-354.

Bess, F.H. & Tharpe, A.M. (1984). Unilateral hearing impairment in children. Pediatrics, 74(2), 206-216.

Brennan, M., Lewis, D., McCreery, R., Creutz, T., & Stelmachowicz, P. (2013). The Situational Hearing Aid Response Profile (SHARP). Software application retrieved from audres.org/rc/sharp

Dillon, H. (2012). Hearing aid earmolds, earshells and coupling systems. In Harvey Dillon (Ed.) Hearing Aids: Second Edition. (pp. 136-144). New York, NY: Thieme Publishers.

Feigin, J.A., Kopun, J.G., Stelmachowicz, P.G., & Gorga, M.P. (1989). Probe-tube microphone measures of ear-canal sound pressure levels in infants and children. Ear & Hearing, 10(4), 254-8.

Fitzpatrick, E.M., Whittingham, J., & Durieux-Smith, A. (2013). Mild bilateral and unilateral hearing loss in childhood: A 20-year view of hearing characteristics and audiologic practices before and after newborn hearing screening. Ear & Hearing, 35(1), 10-18.

Hicks, C.B. & Tharpe, A.M. (2002). Listening effort and fatigue in school-age children with and without hearing loss. Journal of Speech, Language & Hearing Research, 45(3), 573-584.

Joint Committee on Infant Hearing. (2007). Year 2007 Position Statement: Principles and guidelines for early hearing detection and intervention programs. Pediatrics, 120(4), 898-921.

Kruger, B. (1987). An update on the external ear resonance in infants and young children. Ear & Hearing, 8(6), 333-336.

Lewis, D. & Eiten, L. (2011). FM Systems and Communication Access for Children. In R. Seewald & A.M. Tharpe (Eds.) Comprehensive Handbook of Pediatric Audiology. (pp. 553-564. San Diego, CA: Plural Publishing.

Most, T. (2004). The effects of degree and type of hearing loss on children’s performance in class. Deafness and Education International, 6(3), 154-166.

National Workshop on Mild and Unilateral Hearing Loss: Workshop Proceedings (2005). Breckenridgem, CO: Centers for Disease Control and Prevention. Retrieved from http://www.cdc.gov/ncbddd/hearingloss/documents/unilateral/Mild_Uni_2005%20Workshop_Proceedings.pdf

Scollie, S.D. (2008). Children’s speech recognition scores: The Speech Intelligibility Index and proficiency factors for age and hearing level. Ear & Hearing, 29(4), 543-556.

Scollie, S., Glista, D., Tenhaaf, J., Dunn, A., Malandrino, A., Keene, K., & Folkeard, P. (2012). Stimuli and normative data for detection of Ling-6 sounds in hearing level. American Journal of Audiology, 21(2), 232-241.

Seewald, R.C. & Scollie, S.D. (1999). Infants are not average adults: Implications for audiometric testing. Hearing Journal, 52(10), 64, 66, 69, 70, 72.

Tharpe, A.M., Ricketts, T.A., & Sladen, D.P. (2003). FM systems for children with minimal to mild hearing loss. ACCESS: Achieving Clear Communication Employing Sound Solutions. Proceedings of Chicago Conference, Chapter 20, 191-197.

Tharpe, A.M., Eiten, L.R., & Gabbard, S.A. (2008). Hearing Technology. Seminars in Hearing, 29(2), 169-177.

Tharpe, A. M., Fino-Szumski, M. S., & Bess, F. H. (2001). Survey of hearing aid fitting practices for children with multiple impairments. American Journal of Audiology, 10(1), 32-40.

Tharpe, A.M. & Schmidtke Flynn, T. (2005). Incorporating functional auditory measures into pediatric practice: An introductory guide for pediatric hearing professionals. Brochure published by Oticon A/S. Retrieved from http://www.oticon.com/~asset/cache.ashx?id=10835&type=14&format=web

Tsiakpini, L., Weichbold, V., Kuehn-Inacker, H., Coninx, F., D’Haese, P., & Almadin, S. (2004). LittlEARS Auditory Questionnaire. MED-EL. Innsbruck, Austria.

Wake, M., Hughes, E.K., Poulakis, Z., Collins, C., & Rickards, F.W. (2004). Outcomes of children with mild-profound congenital hearing loss at 7 to 8 years: A population study. Ear & Hearing, 25(1), 1-8.

C H A P T E R  N I N E T E E N

Supporting Families of Children with

Auditor y Neuropathy Spectrum Disorder

Stephanie Olson B.A.

Abstract

Universal agreement on best treatment options for children with auditory neuropathy spectrum disorder (ANSD) continues to be challenging for professionals and parents. Families may face contradictory information regarding the diagnosis, choices in communication, amplification, and intervention services for their child. This presentation will share “what works for families” , helps them begin to understand the complexity of ANSD and gain the confidence to become full partners in their child’s care as well as pitfalls to avoid while counseling families. This paper will discuss perspectives and stories from parents, looking back as their children transitioned from the early years to preschool, and then to elementary school and beyond.

Parents of children who are deaf or hard-of-hearing face many difficult and confusing issues and decisions. These include the anxiety of referral from newborn hearing screening, the unanticipated diagnosis of permanent hearing loss, the variety of options for amplification, communication methodology, and intervention services in their community. These issues are confounded when the child has a diagnosis of auditory neuropathy spectrum disorder (ANSD). These families may receive contradictory information about diagnosis, treatment, and outcome expectations. They may hear that “recovery” from this disorder is possible and they may observe fluctuations in their child’s hearing ability.

Supporting families of children with ANSD with a team of professionals is critically important for successful outcomes for the child and family. Professionals with a variety of perspectives and expertise can help the family understand the range of options available and support the decisions the family must make. At Bill Daniels Center for Children’s Hearing, located in the Children’s Hospital Colorado, the comprehensive support team for families includes: pediatric otolaryngologist, genetics counselor, audiologist, speech language pathologist with expertise in hearing loss, social worker, deaf educator and the family consultant.

The Family Consultant typically meets with families after the confirmation of hearing loss during scheduled appointments with the audiologist. This allows the family to meet and access support in the moment without having to schedule additional appointments. She provides families with resources and information about hearing loss, communication options, facilitates connections in the hospital and the family’s home community and lends a personal perspective into the day to day issues of life with hearing loss.

To understand the perspective and experiences of parents, the Family Consultant conducted interviews with twelve parents whose children with ANSD received ongoing care at Bill Daniels Center for Children’s Hearing. Families of children aged 2 years through 12 years were interviewed. The families were asked about their experience with the diagnosis and recommendations for intervention. They were also encouraged to consider the challenges they faced as their child transitioned through important milestones such as moving from early intervention to preschool, preschool to elementary school, and middle school and beyond when giving feedback.

Characteristics of the children whose parents were interviewed are summarized below.

• 13 children; one set of twins

• Seven boys/six girls

• Ages: 2.8 years through 12 years old

• Three children were adopted

• Four children with global developmental delays including one with autism

• One multi-generational family with deafness; communication mode is both ASL and spoken English. The four children in the family have hearing loss but only one has AN

• Four children reside in rural Colorado.

• Six children have cochlear implants

• Two children are fulltime consistent hearing aid users

• One child has used hearing aids intermittently

• One child uses ASL and does not access technology

Parents were given the opportunity to visit by phone, email or meet in person. All 12 families contacted agreed to participate and share their experiences parenting a child with ANSD. The following questions were presented to the parents:

• What support or information was helpful to your family after you learned about your child’s diagnosis of ANSD?

• What do you wish the professionals would have done differently?

• Looking back, is there anything that you would have done differently for your child?

• What advice would you give to families with children who have auditory neuropathy?

• Are there any memories or experiences where you could see how AN impacted your child at home or school?

The following experiences were common to most families:

• Parents desired to know what their child was hearing

• Parents stated that professionals need to be confident in their information or comfortable in referring families. One parent shared, “I felt that I have always had to seek out information myself and then find the professionals who were willing to help me.”

• Parent to parent support is critical and alleviates the desire to search the internet for that connection and for information which may not always be accurate or current. “I was sad when I read on the internet about some cases of ANSD resolving and I had second thoughts about a cochlear implant.” Sharing that information with the audiologist is important but there is comfort in realizing that other parents also have had the hope that their child’s ANSD would resolve.

• Parents felt that it was their job to constantly educate others; “I’m always explaining what auditory neuropathy is to family members, friends and those that work with my child.”

• Professionals may not be knowledgeable about all of the tools for communication.

• Consistent and effective communication was an ongoing challenge.

• “People tend to underestimate my child.”

The statement that “People tend to underestimate my child” was shared by several parents regardless if the child had delays or if the child is currently reading above grade level or had a sophisticated understanding of language. What might professionals be implying or doing that could make a parent feel as if their child is being underestimated? Do professionals value input and observations from parents? Are the decisions and choices of parents being honored? What strategies can professionals employ to increase parent understanding of ANSD while maximizing the child’s strengths and skills? “Children with ANSD can develop into healthy and dynamic citizens with happy personal lives, successful academic experiences and satisfying careers. Clinicians should help families realize this goal by identifying and supporting the unique strengths and abilities of the child and family.”

(ANSD Guidelines, 2008).

Experiences During Transitions: Birth to

Three Years

As families looked back at the birth to three year time period, several parents were able to see the positive support that they received from their providers, especially their audiologist. Time restraint is an issue that audiologists are faced with while counseling families with ANSD. However families reported that the time spent counseling during those early days turned out to be invaluable. “The time spent in counseling was time well spent.” Another parent shared, “Audiologists should never under estimate the time spent visiting outside of the booth such as emails, and phone calls.” Other helpful comments and strategies that were expressed and considered crucial for families during the birth to three year period included:

• The need to understand the diagnosis of their child’s hearing loss

• To reiterate the diagnosis of ANSD and what their child’s audiogram means. This should take place during multiple appointments. Families reported that it took a year or two for the information about ANSD to make sense to them.

• “Maybe this will get better.” The desire for the child’s hearing loss to get better was expressed repeatedly by the families interviewed and even families with older children. One child was almost 12 years old and the family still held onto the idea that the hearing loss might improve. Another family shared that “This (hearing tests and audiograms that varied) could be part of God’s plan to heal our child.” How do audiologists encourage parents to make empowering decisions with their faith and their treatment team? If professionals attempt to draw a line between the two then treatment may become adversarial for the family. Acknowledging the values of a family may need to occur during an audiology appointment. Audiologists will learn more about families by not passing judgment, especially in situations where recommendations are not readily followed based on family values. The family may benefit from a conversation with a social worker, counselor or chaplain. Children’s Hospital Colorado has a chaplain with a personal perspective on hearing loss and is available to lend insight to the family’s desire to make faith based decisions.

• Health issues and graduating from the NICU was the most important for several families. Families with babies who had difficult neonatal complications wanted to be able to go home and wait with follow up and frequent hearing tests. Hearing is not always a priority for families with babies that struggle with health issues. Global delays also often made it difficult for some families to be consistent with hearing aid trials or get a sense of the benefits of hearing aids in the home environment.

• “It was hard to be told that my observations were wishful thinking.” Early interventionists and audiologists desire and ask for parental feedback and observations. Information from parents needs to be valued and incorporated into the visit even if it doesn’t correlate with the results of the audiogram.

• Communication options – professionals should have knowledge and understand the value of all communication options. Families appreciated honest conversations about what the best options for the best outcomes are rather than a “wait and see” approach and with ongoing testing. One family in this interview did not have a desire to incorporate sign language and felt confident that their son would do well with spoken language. The young boy has done well but must have full access to lip-reading which in retrospect serves as a visual mode for his communication needs. Another child with spoken language used cued speech while growing up and has recently added sign language for social connections with his peers. The parents of these two boys shared that as they looked back; they felt that they had to justify their communication choice to the early interventionists and providers during their child’s early years.

• Parents shared that conflicting information made it difficult to have confidence in their providers unless there was a strong team in place. Recommendations were welcomed when the child was being monitored by a team that included a variety of professionals.

• “I wish the referral for a vision screening was strongly emphasized over several of our appointments.” Parents with little one ones that needed glasses stated they didn’t realize how important vision was for children using a visual mode of communication.

• “In the early years I didn’t understand the value of collaboration until my child started school and then I was glad to have had that experience to meet my child’s school needs.” Audiologists that strive for successful teaming in the early years help parents become skilled in advocating when the child enters school.

• Clinicians with an expertise in working with children who have hearing loss were an invaluable resource for parents and children that attended toddler or preschool groups.

• “I was so scared to lose what hearing my child had.” Confidence in technology was slow to emerge during the birth to preschool years. Multiple trials with hearing aids were needed. Parents that later opted for cochlear implants stated that it was still difficult to give up what hearing their child had even when the language wasn’t progressing with therapy.

Experiences During Transitions:

Preschool Years – Three to Five Years

• Three of the mothers shared that their preschoolers were more dependent on them for clarification and comfort in social situations than typical preschoolers. While the sensitivity and attentiveness of these mothers gave their child increased access to communication it became more difficult as the child entered the school years. A mother of a seven year old child expressed her concern and desire to stay with her child during activities at a weekend camp for children with hearing loss. The staff shared that access to communication would be provided in every way at every camp activity, day and night; from fishing to horseback riding and the evening campfires. When her child saw the other campers and ran off to join them, she shared that “In hindsight, finding different ways to help my child understand what was going on would have been better than being her interpreter during those early years and in tough situations.”

• Developmental delays become more obvious as the child entered preschool. “I began to notice that the language and speech delays were more apparent as he entered preschool and when he tried to play with the other preschoolers.”

• Skills in advocacy and parental involvement became critical during the preschool years. A parent said that his advice to families would include; “People will help your child if they know you. Get to know people at your child’s school!” Confidence and knowledge about ANSD began to emerge for parents during the preschool years. This became crucial as parents began to advocate for their child’s school needs and get those needs written into the Individual Education Plan for school.

• Decisions for technology were typically made during the preschool years. “I wish we had done the cochlear implants sooner. She loves her cochlear implants (CIs) but I was scared to lose what hearing my child had.” Two of the girls from this group were implanted at the age of four and enjoyed hearing with cochlear implants. Both girls had several hearing aid trials. One did not consistently wear her hearing aids and the other child refused to wear her hearing aids. Upon activation of her CI’s one child went through a period of time when she would say good night to her cochlear implants. The other girl was so excited about hearing that when she was in her room after surgery she kept saying, “I hear birds!” “I hear my heart.” Of course those sounds were not yet present but her parents had done a nice job of talking about the possibility of hearing new sounds and she was eager to hear those sounds.

Experiences During Transitions:

Elementary School Six Year to 11 Years

• During this stage, advocacy needs to move from the parents advocating for their child to self-advocacy skills for the child and be incorporated into the child’s Individual Education Plan.

• The elementary school age child needs to become familiar and aware of when they are not hearing well and when they are hearing well. They need to learn what optimal hearing situations look like for them. This is not only challenging for this age group with ANSD but also their parents who continue to desire and know what their child is hearing. Parents should share what they themselves are hearing which helps for comparison and discussion about different sounds. One father said that he had been so focused on what his son couldn’t hear that he never shared what he himself was hearing when they were hiking or playing sports together.

• Strategies for tough days and plans need to be in place especially as the challenges of hearing in background noise take place on a daily basis for elementary age children. For the older child, there is comfort in knowing what to do when listening environments are tougher than usual.

• Creative outlets, sports or quiet time (listening breaks) may help the older child on days when extra energy is required for hearing and communicating well. One child is very artistic and will draw his way through his stress. Another journals and writes imaginary stories and yet another child takes comfort in reading quietly in his room.

• Social skills require guidance and support from family members and people who are connected with the older child. Communication breakdowns need to be recognized by the older child (not just the parents) so that the child can attempt to repair social mishaps.

• Parents shared that as their child began to transition to the middle school years they revisited questions such as; “What are the goals for my child now? What can we expect and does our child have the right tools to get information taking place academically and socially? Are the current communication methods working for our child?”

Experiences During Transitions:

Middle School (6th grade) – 11 Years to

13 Years

• School placement and support services may change from elementary school to the middle school years. The parent of a 12 year old said, “Schools are focused on what services they have to meet your child rather than what are the best services for your child.” I chose to move my child from the public school setting to a private school since smaller class sizes were more important than the services that the public school had to offer my child.”

• More schools are utilizing computers as a teaching tool. Older students with hearing loss have commented that they can’t hear fast enough when taking tests on the computer. Practice tests and conversations between the student and the teacher need to occur to examine if less than optimal grades are the results of hearing or academic performance.

• Older students may demonstrate embarrassment using an FM system. It may be time to evaluate the possibilities of note takers and wearing an FM or note takers vs. the FM system. The ease of a note taker allows the child to sit back, listen and absorb the information which may help the student focus on academic skills.

• Audiologists may be able to suggest useful strategies that assist students in obtaining missed information and seek clarification. Consistently asking the student “What did I say? Or “Did you hear me?” puts the child in a position to not tell the truth. Children this age do not want to be wrong. Asking “What did you hear” prepares the students to understand that what they hear isn’t always what was said.

• Teachers should ask the child next to the student with hearing loss for repetition to avoid consistently asking the student with hearing loss to repeat directions that were given.

• “The fluctuations in his hearing are evident in his temper when he comes home from school”. Information begins coming at a faster pace during these school years. Keeping up can be more difficult and lead to frustration especially at home when extra patience is required to get along with siblings. “I can hardly wait to be old enough to live by myself” commented a 12 year old boy when he complained that it was too hard to be with his brothers.

• “Everybody is always talking about me and my hearing.” Empower this age group to take ownership of their hearing loss by assisting them in understanding their hearing loss should be considered a goal. Creating biographical power points and getting the student involved in their own Independent Education Plan (IEP) may help students become aware of their hearing and enhance self-advocacy skills. “She (the audiologist) is always writing notes about me during the visit”. Audiologists should inform the older student what they are writing when taking notes during appointments. Students this age should be at the center of the appointment as the audiologist shares results of the tests and the child’s audiogram.

• Independence/freedom/privacy is most important for the pre-teen and teenager. Audiologists may serve as a valuable resource by sharing ideas for parents of preteens that desire privacy or independence. Parents of children with hearing loss tend to enter the child’s room because they know that their child may not hear them knocking. Create a plan, crack the door and wave a hand through the cracked door or flick the light rather than knocking and walking right into a teenager’s room. Audiologists can model this in the clinical setting. When the teen is the patient, rather than gently knocking on the door when coming into a room during the appointment, knock loudly, or wave a hand through a door that is cracked open. Parents will attempt these strategies at home. Audiologists may be a source for suggesting ways to move the family and child towards independence by encouraging the preteen to use technology or assistive devices. One of the fathers shared how the family was able to let the son bike a distance from home with a friend as long as the boys used the FM system. Parents may share the frustration of waking teens up in the morning and not realize there are alarm clocks that are available for people with hearing loss. Two of the families shared that the value of the extra time their audiologist spent counseling them during the early years was beneficial once again during their child’s adolescence. Referrals for resources, assistive devices and connections with deaf/hard of hearing mentors or role models were needed as their youngster entered adolescence.

Summary

The following statements are taken from a report from a panel of distinguished scientists and clinicians at the Lake Como, Italy, 2008 Guidelines Development Conference on Auditory Neuropathy Spectrum Disorder (ANSD Guidelines, 2008):

“Counseling families of infants with this ANSD is one of the greatest challenges associated with this disorder. Because the developmental effects of ANSD cannot be predicted from test results obtained in the earliest months or even years of life, families struggle with the uncertainty of what the diagnosis means relative to their infant’s growth and development. Many infants with ANSD have had difficult perinatal courses with complications including prematurity, birth asphyxia, infections or other conditions requiring neonatal intensive care. The significance of the ANSD diagnosis may be difficult for families to appreciate as they struggle to understand their infant’s complex medical and developmental needs. Strong support systems, including parents of children with similar diagnoses and professionals with expertise in clinical social work and family counseling, should be available to meet the ongoing and challenging needs of families.”

Parents interviewed for this paper reinforced the importance of a strong support system including a multidisciplinary team of professionals. As professionals, regardless of our discipline, we can endeavor to give parents the confidence that their child with auditory neuropathy will do well with ongoing support, family involvement, quality services, and access to language and technology. As one mother so eloquently expressed, “Hope didn’t get me through understanding hearing loss and deafness. People did - people got me through it.”

Reference

Guidelines for Identification and Management of Infants and Young Children with Auditory Neuropathy Spectrum Disorder. (2008). Bill Daniels Center for Children’s Hearing, Children’s Hospital Colorado. Aurora, CO. http://www.childrenscolorado.org/departments/audiology-speech-learning/daniels-center/ansd-guidelines.

C H A P T E R  T W E N T Y

Global Pediatric Hearing Health – In Search Of Novel Solutions to Current Challenges

De Wet Swanepoel, Ph.D.

Abstract

Hearing loss is a pervasive chronic disability estimated to affect 32 million children around the world. Childhood hearing loss prevalence varies across world regions influenced in part by socio-economic conditions. Significant barriers, including limited professionals and equipment shortages, prevent children in underserved world regions to access secondary preventative ear and hearing health services. As a result, the majority of children who are deaf or have significant degrees of hearing loss do not receive schooling in underserved regions and those with ear disease are prone to complications. Screening and diagnosis for ear and hearing disorders are most commonly unavailable. In an effort to address barriers for children without access to ear and hearing health care services, including screening, diagnosis and intervention, novel solutions that capitalize on the advances in technology and connectivity are required. Two new technical developments to address these barriers in pediatric ear and hearing health care will be reviewed alongside existing evidence.

This presentation is dedicated to Nelson Mandela who passed away only days before the Phonak 6th International Pediatric Audiology Conference began on December 8th, 2013.. It is dedicated in memory of his love for children, especially those with disabilities in South Africa and sub-Saharan Africa.

“Our children are our greatest treasure. They are our future”.

“Disabled children are equally entitled to an exciting and brilliant future”.

Nelson Mandela, (18 July 1918 – 5 December 2013)

Childhood hearing loss has been referred to as a silent disability (Swanepoel, 2010). No clinical examination of a child’s physical status can alert parents or health care providers of a child’s hearing loss in the first few weeks of life. As a result, the condition is not identified early if screening programs that employ electrophysiological test procedures (otoacoustic emissions or auditory brainstem responses) are unavailable. Despite parental suspicion in the first year of life, disabling hearing loss is only identified through initial consequences seen in behavior such as delayed or no speech production and poor responsiveness to sound. At this stage, critical developmental periods for language have already been missed that result in pervasive developmental delays in speech, language, cognitive and socio-emotional development, academic achievement and vocational outcomes (Busa, Harrison, Chappell, Yoshinaga-Itano, Grimes, Brookhouser, et al. 2007; Korver, Konings, Dekker, Beers, Wever, et al., 2010; Russ, Dougherty & Jagadish, 2010; Olusanya, Ruben & Parving, 2006).

Unfortunately for the majority of countries around the world, representing more than 90% of newborns, widespread newborn or infant hearing screening programs are unavailable (WHO, 2010). In a previous contribution to the Sound Foundation through Early Amplification Proceedings (Swanepoel, 2010) various approaches to improve primary and secondary prevention for newborns and infants was considered. The focus of this article is more focused on children as opposed to newborns and infants, with two specific strategies discussed to increase access to ear and hearing health care. The first relates to the issue of ear disease and early identification and treatment in underserved areas as a preventative measure and the second relates to identification of hearing loss in young children entering school systems.

Global Challenges to Childhood Hearing Loss

Prevalence of childhood hearing loss. Permanent disabling hearing loss, characterized by a loss greater than 40 dB and 30 dB in the better ear for adults (≥ 15 years of age) and children (<15 years of age) respectively, is an increasingly prevalent global health care condition (WHO, 2013). In 1995 the World Health Organization estimated that 120 million people suffer from disabling hearing loss. This number more than doubled in 10 years to 278 million in 2005. In 2013 the number of persons with disabling hearing loss was estimated to be 360 million, which constitutes 5.3% of the global population. Of these 32 million children globally with disabling hearing loss the majority reside in South Asia and sub-Saharan Africa (Table 1). Prevalence of childhood hearing loss is exponentially related to economic development with higher prevalence for poorer world regions as illustrated in Figure 1 (WHO, 2013). Since the majority of these children are unable to access early detection and intervention services they are most likely assigned to a life of exclusion and limited outcomes in terms of literacy, academic achievement, vocational outcomes, economic contribution to society with poor quality of life (Olusanya, Ruben & Parving, 2006).

Table 1. Global estimated estimates prevalence of childhood hearing loss across world regions (WHO, 2013)

Figure 1. WHO (2013) estimated regional prevalence of disabling childhood hearing loss according to average gross national income (GNI) per capita.

Apart from permanent hearing losses in children there is also the significant burden of conductive ear diseases, including otitis media (OM), which may result in temporary hearing loss but potentially could also lead to permanent losses (Acuin, 2004; WHO, 2013). According to a recent systematic survey of global OM, an acute otitis media (AOM) incidence rate of 10.85% was reported, translating to 709 million annual cases of which 51% occur in children younger than 5 years (Monasta et al., 2012). Chronic suppurative otitis media (CSOM) incidence rate was reported as 4.8% with 22.6% of cases occurring in children younger than 5 years of age (Table 2). Complications related to OM as shown in Table 2 were estimated to include an OM-related hearing loss prevalence of 3.1 per 1000 and 21000 annual global deaths attributable to OM (Monasta, Ronfani, Marchetti, Montico, Vecchi-Brumatti, et al., 2012). The burden and population characteristics of OM differ greatly between world regions with India and sub-Saharan Africa accounting for the most deaths arising from OM related complications. The prevalence of CSOM in Africa has been classified as high amongst both children and adults, estimated to be between 3 to 6% (Acuin, 2004). The costs, direct and indirect, related to AOM, CSOM and resulting hearing loss is an important and significant burden on health systems and households globally, especially in underserved regions such as sub-Saharan Africa (Monasta et al., 2012)

Table 2. Global incidence of AOM, CSOM and prevalence of OM-related HL and deaths (Adapted from Monasta et al., 2012)

Access to Ear and Hearing Health Care Services

Global inequality is illustrated all too clearly in the area of ear and hearing health care with more than 80% of people with disabling hearing loss residing in underserved areas where services are either absent or very limited (WHO, 2006; Fagan & Jacobs, 2009). In developing countries the average ratio of audiologists to the general population varies between 1:500 000 to as few as one for every 6.25 million people. This is in contrast to a developed country like the UK where the average ratio for audiologists to people is one to every 20,000 persons (Goulios & Patuzzi, 2008; Fagan & Jacobs, 2009). In sub-Saharan Africa many countries do not have any audiology or otolaryngology services available. The dearth of ear and hearing health care professionals is primarily due to a reported lack of government funding, professional and public awareness, and, most significantly, available training programs (Goulios & Patuzzi, 2008). Only two African countries, for example, indicate having any training programs in audiology and many countries also indicate not having any otolaryngology training programs (Fagan & Jacobs, 2009).

It is not only developing countries that have a shortage of ear and hearing health care personnel however. The need for audiological services in a country like the USA is significantly greater than the current capacity of professionals providing these services. Margolis & Morgan (2008) compared the estimated number of audiograms required annually in the USA with the capacity of current professionals to provide these tests. According to their estimations there was an annual shortfall of 8 million audiograms in the year 2000 that was expected to increase to 15 million by 2050. A more recent study reported that the shortage in audiologists to meet the increasing demand for services in the US is expected to increase. It is estimated that in order to meet the demand, the number of persons to enter the field of audiology in the US should increase by 50% in 2013 and the attrition rate would need to be lowered to 20% (Windmill & Freeman, 2013).

In Search Of Novel Solutions

The prevalence of ear and hearing disorders and the significant and lifelong consequence for young children if timely services are unavailable, as is typical with the global shortage in ear and hearing health services, make it imperative to investigate ways of improving sustainable access. No wonder that alternative strategies have been proposed towards increasing the capacity and reach of existing ear and hearing health care providers (Windmill & Freeman, 2013; Swanepoel, Clark, Koekemoer, Hall, et al., 2010; Margolis & Morgan, 2008). The utilization of advances in technology and the growth in global connectivity is opening doors to new modes and methods of service-delivery in ear and hearing health care. Two examples of this will be considered in the following section.

Remote Diagnosis of Ear Disease

Early diagnosis and treatment of ear disease is not achievable for the majority of the global population, particularly in regions such as sub-Saharan Africa and India (WHO, 2013; Fagan & Jacobs, 2009). This predisposes to complications that may include temporary and permanent hearing loss and even death in some cases (Monasta et al., 2012). Capitalizing on the widespread availability of cellular phone networks and technology may provide a way to increase access to care through telehealth. One such method is the use of video-otoscopy for remote diagnosis of ear disease. By incorporating video-otoscopy at primary health care clinics or referral hospitals where specialist ear and hearing personnel are unavailable allows for images or recordings to be sent for remote interpretation by specialists in urban areas or even abroad (Biagio, Swanepoel, Adeyemo, Hall & Vinck, 2013; Swanepoel et al., 2010; Swanepoel & Hall, 2010). This may allow a way to effect timely diagnoses and treatment recommendations. Telehealth video-otoscopy has previously demonstrated that asynchronous video-otoscopy images are equivalent in quality to onsite otoscopy (Biagio, Swanepoel, Adeyemo, Hall & Vinck, 2013; Lundberg, Westman, Hellstrom & Sandstrom, 2008; Mbao, Eikelboom, Atlas & Gallop, 2003; Patricoski, Kokesh, Ferguson, Koller, Zwack, et al., 2003; Smith, Dowthwaite, Agnew & Wootton, 2008). Importantly, for the purpose of validating video-otoscopy within a hearing telehealth clinic, studies have demonstrated average to good diagnostic concordance between conventional otoscopy and asynchronous video-otoscopy images (Biagio et al., 2013; Lundberg, Westman, Hellstrom & Sandstrom, 2008; Mbao et al., 2003; Patricoski et al., 2003; Smith, Dowthwaite, Agnew, & Wootton, 2008).

The person acquiring the actual video-otoscopic image in reports vary from nurses, general practitioners and otolaryngologists, which may influence the quality of the telehealth video-otoscopy images (Lundberg et al., 2008; Mbao et al., 2003; Patricoski et al., 2003; Smith et al., 2008). Since general practitioners and specialists are usually unavailable at primary health care clinics in underserved areas, the validity of a remote telehealth service depends largely on using non-specialist personnel such as nursing staff or laypersons. A recent study investigated using a telehealth clinic facilitator, with no formal health care training or tertiary education, to capture images from the ear canal of adult patients attending a primary health care clinic (Biagio et al., 2013). The otolaryngologist who conducted the onsite assessment remotely interpreted the images a few weeks later. Diagnostic concordance was moderate and the study findings indicated that a trained telehealth facilitator could acquire adequate quality video-otoscopic images for asynchronous diagnosis of ear disease using video-otoscopy in underserved populations. The fact that the study was conducted on adults was a limitation however, since the primary group affected by middle-ear disorders like OM is young children. Furthermore it was noted that video-otoscopic images lack depth perception, which may be a limitation in accurate diagnosis (Biagio et al., 2013).

In a follow-up study (Biagio, Swanepoel, Laurent & Lundberg, submitted 2014), we sampled a population of 140 children between 2 and 15 years of age attending a primary health care clinic for onsite otomicroscopy by an otologist serving as the gold standard diagnosis of ear canal and tympanic membrane status. Video-otoscopy was conducted by the same telehealth facilitator used in the study by Biagio et al. (2013) using a different video-otoscope. However, instead of images, brief video clips were taken of the ear canal and tympanic membrane (<30 seconds). Onsite training was provided to the facilitator over a two-day period by the otologist on how to conduct video-otoscopy recordings. Training included aspects related to positioning, visual inspection of external ear, appropriate hand position, manipulation of direction of speculum, focus adjustment, recording capture, video-otoscope software use, and equipment cleansing. Video recordings were uploaded to a Dropbox folder and the otologist interpreted these remotely at 4 and 8 weeks subsequent to the onsite examination.

The findings of this follow-up study indicated that an unskilled telehealth facilitator could be trained to acquire good quality video-otoscopy recordings for a pediatric sample. Concordance of diagnoses for video-otoscopy recordings interpreted remotely compared to onsite otomicroscopy was better than previous research concordance with video-otoscopy images. Asynchronous video-otoscopy recordings also demonstrated high intrarater reliability. These findings support the possibility of delivering remote specialist diagnoses for ear disease in pediatric populations living in underserved areas through telehealth. Video-otoscopy is a powerful tool that can be used by unskilled, but trained, personnel to acquire adequate recordings (video clips as opposed to static images) for sharing through cellular networks for remote interpretations and diagnoses. This may ensure timely and accurate treatments to minimize complications related to ear disease. High quality recordings can be assessed within a minute or two for diagnostic purposes and may be time and cost-efficient.

School-based Hearing Screening and Diagnosis

Benefits of early detection for hearing loss through newborn hearing screening (NHS) programs is widely established and accepted (Busa et al. 2007). Nonetheless a significant number of permanent hearing losses are only identified around the time of school entry (Bamford et al., 2007; AAA, 2011). A number of reasons may lead to this and include the fact that screen technologies target hearing losses of 30 to 40 dB and miss low-frequency hearing losses. Furthermore some infants referred from newborn hearing screening services do not receive diagnostic services and then there are also cases of of late-onset, acquired or progressive losses (AAA, 2011; Bamford, Fortnum, Bristow, Smith, Vamvakas & Davies, 2007). For underserved regions like sub-Sahara Africa where newborn screening programs for hearing loss are unavailable, school screening may provide the first opportunity to detect a hearing loss (Olusanya, Swanepoel, Castillo, Chapchap, Habib, Mukari, et al., 2007).

Major challenges that hinder the successful implementation of schoolbased screening programs include challenges related to the expense of screening audiometry equipment, poor training of screening personnel, ambient noise leading to over-referrals, and in many underserved regions the lack of electricity necessitating battery-operated systems. Furthermore the lack of data capturing facilities integrated into systems allowing for data surveillance and monitoring is another important limitation to the majority of current audiometers.

Figure 2. The hearScreenTM application being used to screen an adult.

In an attempt to address these challenges we have developed a smartphone-based screening audiometry application (Android OS) calibrated with a supra-aural headset (University of Pretoria Patent, trademarked as hearScreenTM). Although other hearing screening smartphone applications have been reported on (Foulad, Bui & Djalilian, 2013; Handzel et al., 2013; Khoza-Shangase & Kassner, 2013; Szudek et al., 2012) these have revealed mixed findings and have all been developed for the more expensive Apple OS products. This product has been developed on the Android operating system to function on budget smartphones typically used in developing countries.

The hearScreenTM application (Figure 2) follows an automated protocol whereby the screener presents the sound and then indicates whether the child heard the sound or not. The response initiates the next step in the protocol, which means the screener does not have to make in protocol decisions. As a result, very little training in audiometric principles is required and it ensures that the screening protocols across screeners can be enforced in a standardized fashion. Additionally, the application is the first to employ a noise-monitoring feature using the integrated microphone of the smartphone to monitor environmental noise levels. This monitoring feature is calibrated for the selected model of phone (UP Patent). In addition to these features, the application also allows for data capturing on the phone with a sharing function for emailing the database or uploading it to a secure online server. In this way, data can be geo-tagged and uploaded from school sites for surveillance purposes. The initial laboratory and clinical results (Swanepoel, Myburgh, Howe, Mohamed & Eikelboom, submitted 2014) from this development have demonstrated real promise as a mobile hearing screening solution that is cost-effective, requires minimal training, monitors ambient noise level for compliance to maximum permissible ambient noise levels, is battery-operated for a full-day of testing and allows for data capturing and sharing for monitoring program efficacy.

Conclusion

There is an overwhelming shortage of ear and hearing health care providers to adequately serve the number of children with hearing loss and ear disease. Advances in technology and connectivity offer a way to improve the efficiency and accessibility of current service-delivery models towards improving outcomes. We considered two examples of novel technologies that in combination with the growing global connectivity offer ways to make ear and hearing health care services more accessible and sustainable. A non-specialist person with hands-on training can acquire video-otoscopy recordings of the ear canal and tympanic membrane and those video clips can be used for reliable remote diagnoses in children. Furthermore cost-effective mobile screening audiometry can be done using smartphone applications designed for calibration of the stimuli. Quality control can also be ensured by integrating noise monitoring using the smartphone microphone during testing and including data capturing and sharing facilities.

References

Acuin, J. (2004). Chronic suppurative otitis media: Burden of illness. Retrieved 31 January, 2014, from http://www.who.int/pbd/deafness/activities/hearing_care/otitis_media.pdf.

American Academy of Audiology. (2011). Childhood hearing screening. Retrieved 17 January, 2013, from http://www.audiology.org/resources/documentlibrary/Documents/ChildhoodScreeningGuidelines.pdf

Bamford, J., Fortnum, H., Bristow, K., Smith, J., Vamvakas, G., & Davies, L. (2007). Current practice, accuracy, effectiveness and cost-effectiveness of the school entry hearing screen. Health Technology Assessment, 11, 32.

Biagio, L., Swanepoel, D., Adeyemo, A., Hall, J. W. III, & Vinck, B. (2013). Asynchronous video-otoscopy by a telehealth facilitator. Telemed Journal e-Health, 19(4), 252-258.

Biagio L, Swanepoel D, Laurent C, Lundberg T (2014). Video-otoscopy recordings for diagnosis of childhood ear disease using telehealth at primary health care level. Journal of Telemedicine and Telecare, ePub Ahead of Print.

Busa, J., Harrison, J., Chappell, J., Yoshinaga-Itano, C., Grimes, A., Brookhouser, P. E., Mason, P. (2007). Principles and guidelines for early detection and intervention programs. Pediatrics, 120(4), 898-921.

Fagan, J. J., & Jacobs, M. (2009). Survey of ENT services in Africa: Need for a comprehensive intervention. Global Health Action, doi:10.3402/gha.v2i0.1932

Foulad, A., Bui, P., & Djalilian, H. (2013). Automated audiometry using Apple iOS-based application technology. Otolaryngology Head & Neck Surgery, Epub ahead of print.

Goulios, H., & Patuzzi, R. B. (2008). Audiology education and practice from an international perspective. International Journal of Audiology, 47, 647-664.

Handzel, O., Ben-Ari, O., Damian, D., Priel, M. M., Cohen, J., & Himmelfarb, M. (2013). Smartphone-based hearing test as an aid in the initial evaluation of unilateral sudden sensorineural hearing loss. Audiology and Neurotology, 18(4), 201-207.

Khoza-Shangase, K., & Kassner, L. (2013). Automated screening audiometry in the digital age: Exploring uhearTM and its use in a resource-stricken developing country. International Journal of Technological Assess to Health Care, 29(1), 42-47.

Korver, A. M. H., Konings, S., Dekker, F. W., Beers, M., Wever, C. C., Frijns, J. H. M., & Oudesluys-Murphy, A. M. (2010). Newborn hearing screening vs later hearing screening and developmental outcomes in children with permanent childhood hearing impairment. Journal of the American Medical Association, 304(15), 1701-1708.

Lundberg, T., Westman, G., Hellstrom, S., & Sandstrom, H. (2008). Digital imaging and telemedicine as a tool for studying inflammatory conditions in the middle ear evaluation of image quality and agreement between examiners. International Journal of Pediatric Otorhinolaryngology, 72(1), 73-79.

Margolis, R. H., & Morgan, D. E. (2008). Automated pure-tone audiometry: An analysis of capacity, need, and benefit. American Journal of Audiology, 17, 109-113.

Mboa, M. N., Eikelboom, R. H., Atlas, M. D., & Gallop, M. A. (2003). Evaluation of video-otoscopes suitable for tele-otology. Telemedical Journal e-Health, 9(4), 325-331.

Monasta, L., Ronfani, L., Marchetti, F., Montico, M., Vecchi Brumatti, L., Bavcar, A., … Tamburlini, G. (2012). Burden of disease caused by ototis media: Systematic review and global estimates. PLoS One, 7(4), e36226.

Oluysanya, B., Swanepoel, D., Castillo, H., Chap-chap, M. J., Habib, H., Mukari, S. Z., McPherson, B. (2007). Ealy detection of infant hearing loss: An epidemiological trend in developing countries. BMC Health Service Research, 7, 14.

Oluysanya, B. O., Ruben, R. J., & Parving, A. (2006). Reducing the burden of communication disorders in the developing world: An opportunity for the millennium development project. Journal of the American Medical Association, 296(4), 441-444.

Patricoski, C., Kokesh, J., Ferguson, A. S., Koller, K., Zwack, G., Provost, E., & Holck, P. (2003). A comparison of in-person examination and video otoscopy imaging for tympanostomy tube follow-up. Telemedical Journal e-Health, 9(4), 331-344.

Russ, S. A., Dougherty, D., & Jagadish, P. (2010). Accelerating evidence into practice for the benefit of children with early hearing loss. Pediatrics, 1, S7S18.

Smith, A. C., Dowthwaite, S., Agnew, J., & Wootton, R. (2008). Concordance between real-time telemedicing assessments and face-to-face consultations in paediatric otolaryngology. Medical Journal of Australia, 188(8), 457-460.

Swanepoel, D. (2010). The global epidemic of infant hearing loss priorities for prevention. Retrieved 3 February, 2014, from http://www.phonakpro.com/content/dam/phonak/gc_hq/b2b/en/events/2010/ Proceedings/Pho_Chap_01_Swanepoel_final.pdf

Swanepoel, D., Clark, J. L., Koekemoer, D., Hall, J. W., Krumm, M., Ferrari, D., …Barajas, J. (2010). Telehealth in audiology the need and potential to research underserved communities. International Journal of Audiology, 49, 195-202.

Swanepoel, D., & Hall, J. W. (2010). A systematic review of telehealth applications in audiology. Telemedical Journal e-Health, 16(2), 181-200.

Swanepoel D, Myburgh HC, Howe D, Mahomed F, Eikelboom RH (2014). Smartphone hearing screening with integrated quality control and data management. International Journal of Audiology, ePub Ahead of Print.

Szudek, J., Ostevik, A., Dziegielewski, P., Robinson-Anagor, J., Gomaa, N., Hodgetts, B., & Ho, A. (2012). Can u hear me? Validation of an iPod-based hearing loss screening test. Journal of Otolaryngology Head & Neck Surgery, 41(1), S78-S84.

Windmill, I. M., & Freeman, B. A. (2013). Demand for audiology services: 30-yr projections and impact on academic programs. Journal of the American Academy of Audiology, 24(5), 407-416.

World Health Organization. (2006). Primary ear and hearing care training manuals. Retrieved 11 June, 2009, from http://www.who.int/pbd/deafness/activities/hearing_care/en/index.html.

World Health Organization. (2010). Newborn and infant hearing screening: Current issues and guiding principles for action. Outcome of a WHO informal consultation held at WHO headquarters, Geneva, Switzerland, 9-10 November 2009.

World Health Organization. (2013). Millions of people in the world have hearing loss that can be treated or prevented. Retrieved 30 January, 2014, from http:// www.who.int/pbd/deafness/news/Millionslivewithhearingloss.pdf?ua=1.

C H A P T E R  T W E N T Y - O N E

Conference Endnote Address:

A Quick Look Back and a Charge Going For ward

Anne Marie Tharpe, Ph.D.

Abstract

“If, when a child becomes two years old, they suspect that he is handicapped by deafness or partial deafness, they may apply to their Local Education Authority, which must arrange for a medical examination.” (Ewing & Ewing, 1947)

There is a long and storied history of newborn hearing screening and intervention in our professions. This history reflects the efforts of numerous pioneers all of whom have contributed to remarkable improvements in the lives of children with hearing loss and their families over the decades. Today, we have the knowledge, technology, and systems in the developed world that will pave the way for children with hearing loss to maximize their potential and live satisfying and productive lives. However, there is still much work to do. There are hearing healthcare disparities within countries and across the globe – disparities that might be reduced by technological linkages between the developed and undeveloped worlds. Furthermore, we are beginning to see new opportunities for genetic screening for hearing loss and a possibility of identifying those children who have unapparent hearing loss at birth. The future promises the possibility of our preventing, not just treating, some types of childhood hearing loss. This presentation highlights some of the many opportunities ready for us to embrace today and some awaiting us tomorrow – opportunities that we can hardly imagine today.

A Look Back

One thing we can always count on is that time will change our perspective on things – the way we view things from the past, the way we view things in the present, and the way we will view things in the future. In 1913, the Children’s Bureau (now the Maternal Child Health Bureau) published the first in a series of monographs on mother and infant care in response to high infant mortality rates throughout the United States (U.S.). As stated on the opening pages of one monograph, “It (the monograph) endeavors to present the accepted views of the best authorities at the present time” (West, 1914; p. 7). Our views of the recommendations from that series of monographs have definitely changed over time. For example, one recommendation to new mothers was “The beneficial effect of sunlight is best obtained when the rays reach the skin directly. Clothing or ordinary window glass keeps out the ultra-violet rays – the rays that prevent and cure rickets. Sun baths may be begun when the baby is about 3 or 4 weeks old” (West, 1914; p. 42). Of course, we view a baby’s exposure to direct sunlight much differently now. Today, the American Academy of Pediatrics recommends that babies “avoid direct sunlight” (Hagan, Shaw, Duncan, 2008; p. 5). Numerous examples of such scientific opinions that were widely accepted at the time but are rather alarming today, exist in these early publications.

Just as standards of care for infants have changed over time, our views about the appropriate care of children with hearing loss have changed as well. In 1947, Ewing and Ewing, preeminent leaders and advocates of early intervention and education for deaf children in England, wrote a comprehensive account of their views and experiences entitled “Opportunity and the Deaf Child”. In this text, the Ewings stated “If, when a child becomes two years old, they (parents) suspect that he is handicapped by deafness or partial deafness…they must arrange for a medical examination” (pp. 8-9). Almost 10 years later, they modified their recommendations in “New Opportunities for Deaf Children”, stating “…the writers are convinced that all babies should be given screening tests of hearing, by the ninth to twelfth month” (p. 34; 1958). Of course, the rest is history as efforts continued over time to reduce the age of identification of hearing loss in infants and young children. In the 1960s, there was interest in using high-risk registers to reduce the overall number of babies to be screened and focus efforts toward those babies most likely to have hearing loss (Advisory Committee on Education of the Deaf, 1967). However, a significant number of babies with hearing loss had no risk factors and were missed by this method. Numerous screening devices were designed to measure trunk and limb movements, startle responses, and infant respiratory changes in response to sound in newborn nurseries. Unfortunately, attempts to automate such screeners were disappointing and found to be time consuming and unreliable (e.g., McFarland, Simmons, & Jones, 1980).

In the 1990s, audiologists transitioned from behavioral screening methods to physiologic methods – auditory brainstem responses and otoacoustic emissions. Enthusiasm with those new approaches to screening led to an eagerness to implement universal screening programs throughout the U.S. Although few would argue that early identification of hearing loss was not a noble objective, debates ensued in this country about the best way to proceed with implementation (e.g., Bess & Paradise, 1994). The disagreements generated by these deliberations stimulated numerous studies that resulted in a body of research that demonstrated the feasibility of mass newborn hearing screening and, ultimately, the benefits of same. Today, we have newborn hearing screening tools with good reliability, sensitivity, and specificity. Although some countries are still struggling to get screening programs in place, feasibility has been demonstrated in numerous countries including Australia, Canada, the U.S, and some European countries where between 80% and 97% of newborns are screened (Lehnhardt, 2009; NIDCD, 2011). As a result of these efforts, permanent hearing loss in infants is now identified on average by two to four months of age, as opposed to two to three years of age just a couple of decades ago in the U.S. (White, Forsman, Eichwald, & Munoz, 2010).

And, while we have successfully implemented newborn screening programs, we are still challenged by initiating timely intervention services. Reports from the Centers for Disease Control and Prevention (2011) note that only 57% of those babies who do not pass their newborn screenings are documented as having received follow-up care. Although no strong evidence exists identifying the factors that contribute to loss-to-follow-up, numerous reasons have been proffered including family proximity to resources (ASHA, 2008). Today, we are just beginning to see the vast possibilities of widespread telepractice for reducing the impact of distance from early intervention resources for families. Through telepractice, we can now provide remote newborn hearing screening, audiologic assessments, hearing aid support services, and cochlear implant programming. In addition, we can provide remote consultations with parents and professionals all around the globe, and we can provide early intervention services directly in a child’s home. We are only seeing the tip of the iceberg in terms of what we can accomplish with telepractice (Eikelboom, Atlas, Mbao, & Gallop, 2002). Forty-two percent of states in the U.S. report having implemented some telepractice efforts for providing intervention to infants and children with hearing loss (NCHAM, 2010). Of those 42%, 79% are in the planning or pilot stages – clearly, we have a long way to go but the promise of effective intervention through remote practice is upon us. We can look forward to reducing the hearing health care disparities currently in existence around the world by engaging these new technologies.

A Charge Forward

Just like the Children’s Bureau publications in the 1920s, throughout this conference our speakers have attempted to present the most current, state-of-the-art views on issues related to childhood hearing loss. No doubt that in years to come, we will get a chuckle from some of the views presented over the last few days – perhaps some of our current ideas will not be successful or long lasting. But, we are still challenged to face the same questions faced by those who came before us. Where do we go from here? What are our future directions for improving the lives of those with hearing loss and their families? Are there new and improved ways to identify hearing loss early?

One such challenge is how we will face the inevitability of genetic screening for hearing loss. At least two thirds of permanent hearing loss present at birth has a genetic cause and 70% of that is non-syndromic. But, even in the case of syndromic hearing loss, symptoms may be non-apparent at birth. Hearing loss is genetically quite heterogeneous and involves mutations in many genes (Van Camp, Willems, & Smith, 1997). Therefore, selecting a single gene or a group of genes for testing will not allow for the prediction of hearing loss risk. For each of the six most frequent causative genes that have been identified to date for autosomal recessive non-syndromic hearing loss (GJB2, SLC26A4, MYO15A, OTOF, CDH23, TMC1), at least 20 mutations have been reported (Phillips et al., 2013). GJB2 is a small gene that contains a single coding exon but over 300 different mutations have been reported (Human Gene Mutation Database, n.d.). It is suspected that over 500 genes, with some containing hundreds of mutations, are likely to contribute to hearing loss. Furthermore, interactions among several genes could be required for some individuals to exhibit hearing loss. Despite the current availability of some limited testing for specific genes that are believed to cause hearing loss, the reality of genetic complexity still makes it difficult to predict which newborns will develop hearing loss.

To counter this limitation in our current ability to identify genetic hearing loss, it is likely that technology will yield the possibility of entire genome sequencing within 10 years. Although that is an exciting prospect, it is accompanied by many challenges. Moving from genetic screening for babies known to have hearing loss to population-based screening will require considerable public input, advances in technology, and improved knowledge of genetic causes of hearing loss. The benefits of such screening and the potential limitations will need careful consideration – much like our transition from high-risk screening to universal screening for hearing loss in the 1990s. However, the stakes today are likely even higher. Incidental findings will be a concern (Phillips et al., 2013). That is, if the whole genome is sequenced, what are our ethical or moral obligations to report all mutations that could give rise to future genetic diseases rather than just the mutations associated with hearing loss? It is probable that one-disease/condition screening programs will no longer be sustainable given the implementation costs. Advocates for early identification of hearing loss in infancy will likely be part of a larger genetic screening initiative for multiple childhood conditions and disorders in the future.

In addition to genetic testing of infants, there are efforts underway that can potentially prevent hearing loss in children that are not yet fully understood or commonplace in our provision of care. One such example is exploration of the audiologic impact of aminoglycoside exposure in neonates with MTRNR1 mutations. These mutations lead to hearing loss in patients treated with aminoglycoside antibiotics, which is distinct from the ototoxicity associated with therapeutic levels of these drugs. However, the precise role of MTRNR1 mutations in pediatric aminoglycoside ototoxicity has not yet been fully explored. The American College of Medical Genetics recommends testing for these mutations in patients who have been identified with hearing loss (ACMG, 2002). In the future, we may be able to genotype mothers while pregnant to determine which infants are at increased risk of aminoglycoside ototoxicity and utilize alternative treatments.

Another challenge to identification of early hearing loss is congenital cytomegalovirus (cCMV), the leading cause of non-genetic sensorineural hearing loss in children. Ninety to ninety-five percent of infants born with cCMV will have no apparent clinical abnormalities at birth and will not be identified via routine examination. Therefore, infants with cCMV are likely to pass a newborn hearing screening only to have 10-15% develop hearing loss later in childhood. Clearly, if we could identify those babies with cCMV, they could receive targeted audiologic monitoring resulting in quick intervention as indicated. Although definitive testing for cCMV is available, such methods are not automated and, therefore, are not suited for mass newborn screening. Studies have been ongoing to determine fast and effective methods for mass cCMV screening of newborns. Evaluation of polymerase chain reaction (PCR) screening methods that use dried blood spots and methods that assay infant saliva have been the focus of research attention in the last decade (e.g., Boppana et al., 2011).

Another approach to prevent hearing loss, as opposed to simply identifying/treating, is through the use of protective agents when utilizing ototoxic chemotherapies. A good example of such chemotherapies is cisplatnin, one of the most ototoxic drugs known, for the treatment of pediatric cancers, resulting in hearing loss in between 20% to 90% of children receiving the drug. Young children are at the greatest risk for acquiring hearing loss from cisplatnin, which is typically permanent, bilateral, and high frequency. Sodium thiosulfate has provided protection against platinum-induced hearing loss in animals and human patients and several other thiol-based agents have also shown otoprotection in animal models (Dickey, Muldoon, Kraemer, & Neuwelt, 2004; Doolittle et al., 2001).

The discussion herein suggests a fundamental change in the future of newborn hearing screening, and identification and management of childhood hearing loss more generally. Whereas the past and current purpose of screening has been to identify children who have hearing loss, the future goal is likely to include additional components of preventing hearing loss and identifying children who are likely to have hearing loss but are not yet manifesting symptoms. Performing anticipatory testing does not identify patients with a disease per se but, rather, those with an increased risk for an adverse reaction to medication, or those with special dosing requirements, thus allowing for the avoidance of certain medications that could result in hearing loss. Perhaps we will return to a type of “high-risk” screening after all. And, rather than requiring children and families to travel to large healthcare institutions for services, we may be reaching out to them in their own remote communities via telepractice. The elimination of hearing health care disparities around the globe is almost within our reach!

References

Advisory Committee on Education of the Deaf (1967). Education of the Deaf in the United States: Report of the Advisory Committee on Education of the Deaf, Washington, DC: U.S. Government Printing Office.

American College of Medical Genetics (2002). Genetics Evaluation guidelines for the etiologic diagnosis of congenital hearing loss. Genetics in Medicine, 4(3), 162-171.

American Speech-Language-Hearing Association (2008). Loss to Follow-Up in Early Hearing Detection and Intervention [Technical report]. Retrieved from www. asha.org/policy.

Bess, F. H., & Paradise, J. L. (1994). Universal screening for infant hearing impairment: Not simple, not risk-free, not necessarily beneficial, and not presently justified. Pediatrics, 93, 330-334.

Boppana, S. B., Ross, S. A., Shimamura, M., Palmer, A.L., Ahmed, A., Michaels, M. G., Sanchez, P. J., Bernstein, D. I., Tolan, R. W., Novak, Z., Chowdhury, N., Britt, W. J., & Fowler, K. B. (2011). Saliva polymerase-chain-reaction assay for cytomegalovirus screening in newborns. New England Journal of Medicine, 364(22), 2111-2118.

Centers for Disease Control and Prevention (2011). 2011 National CDC EHDI Data. Retrieved from http:// www.cdc.gov/ncbddd/hearingloss/2011-ata/2011_ ehdi_hsfs_summary_a.pdf.

Dickey, D. T., Muldoon, L. L., Kraemer, D. F., & Neuwelt, E. A. (2004). Protection against cisplatin-induced ototoxicity and nephrotoxicity by N-acetylcysteine in a rat model. Hearing Research, 193, 25-30.

Doolittle, N. D., Muldoon, L. L., Brummett, R. E., Tyson, R. M., Lacy, C., Bubalo, J. S., Kraemer, D. F., Heinrich, M. C., Henry, J. A., & Neuwelt, E. A. (2001). Delayed sodium thiosulfate as an otoprotectant against carboplatin-induced hearing loss in patients with malignant brain tumors. Clinical Cancer Research, 7, 493-500.

Eikelboom, R., Atlas, M., Mbao, M., & Gallop, M. (2002). Tele-otology: planning, design, development and implementation. Journal of Telemedicine and Telecare, 8(Suppl. 3), 14-17.

Ewing, I. R., & Ewing, A. W. G. (1947). Opportunity and the Deaf Child (pp. 8-9). London: University of London Press, Ltd.

Ewing, I. R., & Ewing, A. W. G. (1958). New Opportunities for Deaf Children (p. 34). Springfield: Charles C. Thomas, Publisher.

Hagan, J. F., Shaw, J. S., & Duncan, P. (Eds; 2008). Bright Futures: Guidelines for Health Supervision of Infants, Children, and Adolescents (p. 5), 3rd Edition. Pocket Guide. Elk Grove Village, IL: American Academy of Pediatrics.

Human Gene Mutation Database (n.d.). Retrieved from www.hgmd.org.

Lehnhardt, E. (2009). Neonatal hearing screening: A survey on the situation worldwide. Presentation at the Ear Nose and Throat Conference, Yerevan, Armenia. McFarland, W. H., Simmons, F. B., & Jones, F. R. (1980). An automated hearing screening technique for newborns. Journal of Speech and Hearing Disorders, 45, 495-503.

National Institute on Deafness and Other Communication Disorders (2011). NIDCD Fact Sheet: It’s Important to Have Your Baby’s Hearing Screened. NIH Publication No. 11-4968.

National Center for Hearing Assessment and Management (2010). 2010 Telehealth Survey. Retrieved from http://www.infanthearing.org/telehealth/index. html.

Phillips, L. L., Bitner-Glindzicz, M., Lench, N., Steel, K.P., Langford, C., Dawson, S. J., …Packer, C. (2013). The future role of genetic screening to detect newborns at risk of childhood-onset hearing loss. International of Journal Audiology, 52, 124-133.

Van Camp, G., Willems, P. J., & Smith, R. J. (1997). Non-syndromic hearing impairment Unparalleled heterogeneity. American Journal of Human Genetics, 60, 758-764.

West, W. (1914). Infant Care, Care of Children Series No. 2, Bureau Publication No. 8. Washington: Government Printing Office.

White, K. R., Forsman, I., Eichwald, J., & Munoz, K. (2010). The evolution of early hearing detection and intervention programs in the United States. Seminars in Perinatology, 34(2), 170-179.

Table of Contents

P r e f a c e

C o n t r i b u t o r s

S e c t i o n I

Taking Our Pulse:How Are We Doing Now?

C h a p t e r  O n e

Conference Keynote Address: Awakening the Auditor y System Binaural Benefit Revisited

Abstract

References

C h a p t e r  T w o

Physiologic Assessment of Young Infants – Puzzles and Challenges in Early Hearing Detection and Inter vention

Abstract

Accurate, Early ANSD Diagnosis – Sometimes Easy, Often Challenging or Impossible

Extraordinary ABR Waveforms

Late Auditory Cortical Evoked Potentials– Forgotten Findings

Brainstem (80 Hz) ASSRs & ABRs

Challenges with Comparative Studies

ABR Threshold Estimation Efficiency – So Much Wasted Time!

References

C h a p t e r  T h r e e

Children Who Are Hard of Hearing: Still Forgotten?

Abstract

Design and Methods

A Hypothesis About Factors Influencing Outcomes

Modeling Factors That Impact Access toLinguistic Input

Summary of Protective Factors

Clinical Implications

Acknowledgments

References

C h a p t e r  F o u r

Are We on Target With OurPediatric Hearing Aid Fittings?

Abstract

Speech Audibility

Hearing Aid Use

Data Logging

Parent Report Measures

Predictors of Variation in Hearing Aid Use

Clinical Implications

Summary

Acknowledgement

References

C h a p t e r  F i v e

Monitoring Outcomes of Infants and Children Who Wear Hearing Aids

Abstract

The University of Western OntarioPediatric Auditory Monitoring Protocol

Detection of Speech Sounds

Summary

Acknowledgements

References

C h a p t e r  S i x

Where Are We Now and Where Do We Need To Be? A Perspective From New Zealand

Abstract

Philosophical Perspective

How Are We Doing?

Four Themes

Parent’s Perspectives

Time

Process

Relationships

Opportunities

Paediatric Audiologist at KDEC

Concluding Remarks

Acknowledgement

References

S e c t i o n  I I

Meeting the Diverse Listening Needs of Children in Today’s World:The Environment and Technology

C h a p t e r  S e v e n

The Complexities of Listeningand Understanding in Children with Minimal/Mild Hearing Loss

Abstract

Heterogeneity of HearingLoss Configurations

Perceptions Regarding the Impact of MMHL

Tests Used to Examine the Impact of MMHL

Summary

Acknowledgement

References

C h a p t e r  E i g h t

The Use of FM Technology for Pre-School Children with Hearing Loss

Abstract

Study 1: Quantitative Evaluation of FM use with Pre-School Children

Study 2: Qualitative Evaluation of FM Use with Pre-School Children

Study 3: Language ENvironment Analysis(LENA)

Discussion

Acknowledgement

References

C h a p t e r  N i n e

Flying to the Moon on Radio Waves:Optimizing Outcomes with RF Technologies

Abstract

Basic Characteristics of Wireless Radio

Frequency Technology

Phonak Roger Technology

Research with Adaptive DigitalTechnology

Additional Wireless Technologies

Digital Near-Field Magnetic Induction for Audio Streaming

Case Study

Acknowledgement

References

S e c t i o n  I I I

Integration of Hearing Aids and Cochlear Implants

C h a p t e r  T e n

Frequency Lowering Hearing Aids:

Procedures for Assessing Candidacy and Fine Tuning

Abstract

Recommended Protocols

Case 1: Tuning to Improve Benefit

Case 2: Verification to DetermineCandidacy

Case 3: Asymmetrical Fittings

Summary and Implications

References

C h a p t e r  E l e v e n

What Do We Know About the Fitting and Daily Life Usage of Hearing Instruments in Pediatrics?

Abstract

Tools and Method

Patient Profiles

Use of Hearing Instruments

Application of Styles and Features

WorkFlow

Conclusions

Acknowledgments

References

C h a p t e r  T w e l v e

The Impact of Multiple Technologies on Families: Considerations in Real Life

Abstract

The Limitations of Technology and theMiracles of Technology

Considerations in Real Life

How Audiologists Can Help: RelationshipBuilding

How Audiologists Can Help: EncourageFamily Involvement

The Story of Anthony

Conclusion

References

S e c t i o n  IV

Challenges in Pediatric Service Delivery

C h a p t e r  T h i r t e e n

Bimodal Hearing for Children:Effect of Frequency Region and Acoustic Bandwidth

Abstract

Experimental Details

Results and Discussion

Summary

References

C h a p t e r  F o u r t e e n

Results in Individuals with Asymmetric HearingLoss Using a Cochlear Implant and a Hearing Aid

Abstract

Study 1: Asymmetric Hearing Loss – Adults

Study 2: Varied Forms of AsymmetricHearing – Adults

Study 3: Asymmetric Hearing Loss – Children

Summary and Future Clinical Considerations

Acknowledgements

References

C h a p t e r  F i f t e e n

Fitting Bimodal Devices in Children – A Review

Abstract

Summary

Conclusion

References

C h a p t e r  S i x t e e n

Understanding the Needs of Children Who areDeaf/Hard of Hearing Plus

Abstract

Typical Developmental Progression

Motor Development

Cognitive Development

Language Development

Appropriate Goals and Functional SkillDevelopment

Partnerships and Team Building

Conclusion

References

C h a p t e r  S e v e n t e e n

An Update on Auditor y Neuropathy Spectrum Disorder in Children

Abstract

Etiology of ANSD

Audiometric Presentation

Auditory Processing

Functional Hearing (Speech Perception)

Speech Perception in Background Noise

Management of Children with ANSD Using Hearing Aids and Cochlear Implants

Hearing Aid Amplification

Cochlear Implantation

Long-Term Outcomes

Summary

References

C h a p t e r  E i g h t e e n

Decision Support Guide for Hearing Aid Usein Infants and Children with Minimal/MildBilateral Hearing Loss

Abstract

Configuration and Degree of HearingLoss

Ear Canal and Earmold Acoustics

Hearing Aid Gain/Output and NoiseFloor

Child Factors

Family Factors

Decision Support Guide

Acknowledgements

Summary

References

C h a p t e r  N i n e t e e n

Supporting Families of Children withAuditor y Neuropathy Spectrum Disorder

Abstract

Experiences During Transitions: Birth toThree Years

Experiences During Transitions: Preschool Years – Three to Five Years

Experiences During Transitions: Elementary School Six Year to 11 Years

Experiences During Transitions:Middle School (6th grade) – 11 Years to13 Years

Summary

Reference

C h a p t e r  T w e n t y

Global Pediatric Hearing Health – In Search OfNovel Solutions to Current Challenges

Abstract

Global Challenges to Childhood HearingLoss

Access to Ear and Hearing Health CareServices

In Search Of Novel Solutions

Remote Diagnosis of Ear Disease

School-based Hearing Screening andDiagnosis

Conclusion

References

C h a p t e r  T w e n t y - o n e

Conference Endnote Address:A Quick Look Back and a Charge Going For ward

Abstract

A Look Back

A Charge Forward

References