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A Pediatric Prescription for Listening in Noise

Crukley, J. & Scollie, S. (2012). Children’s speech recognition and loudness perception with the Desired Sensation Level v5 Quite and Noise prescriptions. American Journal of Audiology 21, 149-162.

This editorial discusses the clinical implications of an independent research study and does not represent the opinions of the original authors.

 

Most hearing aid prescription formulas attempt to balance audibility of sound with perception of loudness, while keeping the amplified sound within a patient’s dynamic range (Dillon, 2001; Gagne et al., 1991a; Gagne et al., 1991b; Seewald et al., 1985). Use of a prescriptively appropriate hearing aid fitting is particularly important for children with hearing loss. For the needs of language development, they benefit from a higher proportion of audible sound and broader bandwidth than diagnostically similar older children and adults (Pittman & Stelmachowicz, 2000; Stelmachowicz et al., 2000; Stelmachowicz et al., 2001; Stelmachowicz et al., 2004; Stelmachowicz et al., 2007).

Historically, provision of access to speech in quiet has been a primary driver in the development of prescription formulas for hearing aid.  However, difficulty understanding speech in noise is one of the primary complaints of all hearing aid users, including children. In a series of studies compared NAL-NL1 and DSL v4.1 fittings and examined children’s listening needs and preferences (Ching et al., 2010; Ching et al., 2010; Scollie et al., 2010) two distinct listening categories were identified: loud, noisy and reverberant environments and quiet or low-level listening situations. The investigators found that children preferred the DSL fitting in quiet conditions but preferred the NAL fitting for louder sounds and when listening in noisy environments. Examination of the electroacoustic differences between the two fittings showed that the DSL fittings provided more gain overall and approximately 10dB more low-frequency gain than the NAL-NL1 fittings.

To address the concerns of listening in noisy and reverberant conditions, DSL v5 includes separate prescriptions for quiet and noise. Relative to the formula for quiet conditions, the noise formula prescribes higher compression thresholds, lower overall gain, lower low-frequency gain and more relative gain in the high frequencies.  This study of Crukley and Scollie addressed whether the use of the DSL v5 Quiet and Noise formulae resulted in differences in consonant recognition in quiet, sentence recognition in noise and different loudness ratings.  Because of the lower gain in the noise formula, it was expected to reduce loudness ratings and consonant recognition scores in quiet because of potentially reduced audibility. There was no expected difference for speech recognition in noise, as the noise floor was considered the primary limitation to audibility in noisy conditions.

Eleven children participated in the study; five elementary school children with an average age of 8.85 years and six high school children with an average age of 15.18 years. All subjects were experienced, full-time hearing aid users with congenital, sensorineural hearing losses, ranging from moderate to profound.  All participants were fitted with behind-the-ear hearing aids programmed with two separate programs: one for DSL Quiet targets and one for DSL Noise targets. The Noise targets had, on average, 10dB lower low-frequency gain and 5dB lower high-frequency gain, relative to the Quiet targets. Testing took place in two classrooms: one at the elementary school and one at the high school.

Consonant recognition in quiet conditions was tested with the University of Western Ontario Distinctive Features Differences Test (UWO-DFD; Cheesman & Jamieson, 1996). Stimuli were presented at 50dB and 70dB SPL, by a male talker and a female talker. Sentence recognition in noise was performed with the Bamford-Kowal-Bench Speech in Noise Test (BKB-SIN; Niquette et al., 2003). BKB-SIN results are scored as the SNR at which 50% performance can be achieved (SNR-50).

Loudness testing was conducted with the Contour Test of Loudness Perception (Cox et al., 1997; Cox & Gray, 2001), using BKB sentences presented in ascending then descending steps of 4dB from 52dB to 80dB SPL. Subjects rated their perceived loudness on an 8-point scale ranging from “didn’t hear it” up to “uncomfortably loud” and indicated their response on a computer screen. Small children were assisted by a researcher, using a piece of paper with the loudness ratings, and then the researcher entered the response.

The hypotheses outlined above were generally supported by the results of the study. Consonant recognition scores in quiet were better at 70dB than 50dB for both prescriptions and there was no significant difference between the Quiet and Noise fittings. There was, however, a significant interaction between prescription and presentation level, showing that performance for the Quiet fittings was consistent at the two levels but was lower at 50dB than 70dB for the Noise fittings. The change in score from Quiet to Noise at 50dB was 4.2% on average, indicating that reduced audibility in the Noise fitting may have adversely affected scores at the lower presentation level. On the sentence recognition in noise test, BKB-SIN scores did not differ significantly between the Quiet and Noise prescriptions, with some subjects scoring better in the Quiet program, some scoring better in the Noise program and most not demonstrating any significant difference between the two. Loudness ratings were lower on average for the Noise prescription. When ratings for 52-68dB SPL and 72-80dB SPL were analyzed separately, there was no difference between the Quiet and Noise prescriptions for the lower levels but at 72dB and above, the Noise prescription yielded significantly lower loudness ratings.

Although the average consonant recognition scores for the Noise prescription were only slightly lower than those for the Quiet prescription, it may not be advisable to use the Noise prescription as the primary program for regular daily use, because of the risk of reduced audibility. This is especially true for pediatric hearing aid patients, for whom maximal audibility is essential for speech and language development. Rather, the Noise prescription is better used as an alternate program, to be accessed manually by the patient, teacher or caregiver, or via automatic classification algorithms within the hearing aid. Though the Noise prescription did not improve speech recognition in noise, it did not result in a decrement in performance and yielded lower loudness ratings, suggesting that in real world situations it would improve comfort in noise while still maintaining adequate speech intelligibility.

Many audiologists find that patients prefer a primary program set to a prescriptive formula (DSL v5, NAL-NL2 or proprietary targets) for daily use but appreciate a separate, manually accessible noise program with reduced low-frequency gain and increased noise reduction. This is true even for the majority of patients who have automatically switching primary programs, with built-in noise modes. Anecdotal remarks from adult patients using manually accessible noise programs agree with the findings of the present study, in that most people use them for comfort in noisy conditions and find that they are still able to enjoy conversation.

For the pediatric patient, prescription of environment specific memories should be done on a case-by-case basis. Patients functioning as teenagers might be capable of managing manual selection of a noise program in appropriate conditions. Those of a functionally younger age will require assistance from a supervising adult. Personalized, written instructions will assist adult caregivers to ensure that they understand which listening conditions may be uncomfortable and what actions should be taken to adjust the hearing aids. Most modern hearing aids feature some form of automatic environmental classification: ambient noise level estimation being one of the more robust classifications. Automatic classification and switching may be sufficient to address concerns of discomfort. However, the details of this behavior vary greatly among hearing aids. It is essential that the prescribing audiologist is aware of any automatic switching behavior and works to verify each of the accessible hearing aid memories.

Crukley and Scollie’s study supports the use of separate programs for everyday use and noisy conditions and indicates that children could benefit from this approach. The DSL Quiet and Noise prescriptive targets offer a consistent and verifiable method for this approach with children, while also providing potential guidelines for designing alternate noise programs for use by adults with hearing aids.

 

References

Cheesman, M. & Jamieson, D. (1996). Development, evaluation and scoring of a nonsense word test suitable for use with speakers of Canadian English. Canadian Acoustics 24, 3-11.

Ching, T., Scollie, S., Dillon, H. & Seewald, R. (2010). A crossover, double-blind comparison of the NAL-NL1 and the DSL v4.1 prescriptions for children with mild to moderately severe hearing loss. International Journal of Audiology 49 (Suppl. 1), S4-S15.

Ching, T., Scollie, S., Dillon, H., Seewald, R., Britton, L. & Steinberg, J. (2010). Prescribed real-ear and achieved real life differences in children’s hearing aids adjusted according to the NAL-NL1 and the DSL v4.1 prescriptions. International Journal of Audiology 49 (Suppl. 1), S16-25.

Cox, R., Alexander, G., Taylor, I. & Gray, G. (1997). The contour test of loudness perception. Ear and Hearing 18, 388-400.

Cox, R. & Gray, G. (2001). Verifying loudness perception after hearing aid fitting. American Journal of Audiology 10, 91-98.

Crandell, C. & Smaldino, J. (2000). Classroom acoustics for children with normal hearing and hearing impairment. Language, Speech and Hearing Services in Schools 31, 362-370.

Crukley, J. & Scollie, S. (2012). Children’s speech recognition and loudness perception with the Desired Sensation Level v5 Quite and Noise prescriptions. American Journal of Audiology 21, 149-162.

Dillon, H. (2001). Prescribing hearing aid performance. Hearing Aids (pp. 234-278). New York, NY: Thieme.

Jenstad, L., Seewald, R., Cornelisse, L. & Shantz, J. (1999). Comparison of linear gain and wide dynamic range compression hearing aid circuits: Aided speech perception measures. Ear and Hearing 20, 117-126.

Niquette, P., Arcaroli, J., Revit, L., Parkinson, A., Staller, S., Skinner, M. & Killion, M. (2003). Development of the BKB-SIN test. Paper presented at the annual meeting of the American Auditory Society, Scottsdale, AZ.

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

Scollie, S. (2008). Children’s speech recognition scores: The speech intelligibility index and proficiency factors for age and hearing level. Ear and Hearing 29, 543-556.

Scollie, S., Ching, T., Seewald, R., Dillon, H., Britton, L., Steinberg, J. & Corcoran, J. (2010). Evaluation of the NAL-NL1 and DSL v4.1 prescriptions for children: Preference in real world use. International Journal of Audiology 49 (Suppl. 1), S49-S63.

Scollie, S., Ching, T., Seewald, R., Dillon, H., Britton, L., Steinberg, J. & King, K. (2010). Children’s speech perception and loudness ratings when fitted with hearing aids using the DSL v4.1 and NAL-NL1 prescriptions. International Journal of Audiology 49 (Suppl. 1), S26-S34.

Seewald, R., Ross, M. & Spiro, M. (1985). Selecting amplification characteristics for young hearing-impaired children. Ear and Hearing 6, 48-53.

Stelmachowicz, P., Hoover, B., Lewis, D., Kortekaas, R. & Pittman, A. (2000). The relation between stimulus context, speech audibility and perception for normal hearing and hearing impaired children. Journal of Speech, Language and Hearing Research 43, 902-914.

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

Stelmachowicz, P. Pittman, A., Hoover, B. & Lewis, D. (2004). Novel word learning in children with normal hearing and hearing loss. Ear and Hearing 25, 47-56.

Stelmachowicz, P. Pittman, A., Hoover, B., Lewis, D. & Moeller, M. (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.

Stelmachowicz, P., Lewis, D., Choi, S. & Hoover, B. (2007).  Effect of stimulus bandwidth on auditory skills in normal hearing and hearing impaired children.  Ear and Hearing 28, 483-494.

On the prevalence of hearing loss and barriers to hearing aid uptake

Dawes, P., Fortnum, H., Moore, D., Emsley, R., Norman, P., Cruickshanks, K., Davis, A., Edmondson-Jones, M., McCormack, A., Lutman, M. & Munro, K.  (2014) Hearing in middle age: a population snapshot of 40- to 69-year olds in the United Kingdom. Ear & Hearing 35 (3), 44-51.

This editorial discusses the clinical implications of an independent research study and does not represent the opinions of the original authors.

The Biobank is a national program in the United Kingdom, aimed at longitudinal investigation of the prevention, diagnosis and treatment of diseases and health conditions affecting middle-aged individuals. Since 2006, the Biobank has recruited over half a million participants, who complete test procedures, provide biomedical samples and detailed health information and have their health followed over time, periodically providing updated information. One of the health conditions assessed in the Biobank study is hearing loss and over 160,000 participants have completed questionnaires, audiometric assessment and speech-in-noise testing.

Dawes and his colleagues used Biobank data to examine the prevalence of hearing impairment among 164,700 middle-aged respondents in the U.K., “hearing impairment” was defined as reduced or poor performance on a speech recognition in noise test. They assessed how audiologic and demographic factors relate to hearing impairment and the use of hearing aids among individuals in this age group.

For the Biobank database, hearing loss was assessed via audiometric testing and questionnaires covering lifestyle, environment and medical history, including associated symptoms such as tinnitus. Speech recognition in noise was assessed via the Digit Triplet Test (DTT; Smits et al., 2004). The DTT is a large-scale screening tool that can be administered via the telephone and internet.  The test includes 15 sets of monosyllable digit triplets, presented at a comfortable listening level. Noise levels are varied adaptively to arrive at the SNR required for 50% recognition. Speech recognition results were analyzed in relation to several demographic variables: age, work and music related noise exposure socioeconomic status, ethnicity and gender. 

10.7 % of participants had hearing impairment, as measured by the DTT. Tinnitus was reported by 16.9% of the subjects, which is consistent with previous reports (Davis 1995).  The results show, not surprisingly, that the prevalence of hearing loss increases with increasing age, with an acceleration of prevalence beginning in the 55-59 year old age group. The increase in prevalence with increasing age is consistent with previously published reports for this age group (Plomp & Mimpen, 1979; Wilson & Strouse, 2002; Smits et al., 2006). Tinnitus showed a more consistent increase with increasing age, without a steeper increase for respondents in their 50’s.  Hearing aid use was only 2% for the entire sample and increased with age.  Only 21% of the participants with Poor DTT scores reported using hearing aids.  Those who did use hearing aids had significantly higher socioeconomic status than those without hearing aids.

Only 2.0% of the middle-aged individuals in this study reported hearing aid use. This is similar to an earlier report in which hearing aid use for 41-70 year olds was 2.8% (Davis, 1995). The persistently low proportion of hearing aid use contrasts with the fact that 9.4% of the respondents in the current study had average pure tone thresholds of at least 35 dBHL in the better ear. There are many potential explanations for the low proportion of hearing aid use among hearing impaired individuals. Cost is a commonly cited explanation, though cost is not likely to have influenced the present report, as hearing aids are provided free in the United Kingdom and the participants included in this report probably did not purchase their hearing aids privately. Insufficient value and uncomfortable fit have also been reported as explanations for low hearing aid use (McCormack & Fortnum, 2013). Other proposed barriers to hearing aid use are related to motivation, expectations and attitudes toward hearing aids, with self-recognition of hearing handicap being the most consistently related factor to hearing aid use (Vestergaard-Knudsen et al., 2010).

One mechanism for addressing the concern of hearing aid cost is through the unbundling of the hearing aid and services provided. Bundled pricing (the packaging of hearing aid and services into one price) is typical in the U.S. Unbundling may encourage initial uptake because it allows hearing aid users to pay less at the outset and divide additional expenditures into smaller, more manageable amounts, paying fees at each visit after the initial service period. There is some concern that unbundled pricing will make hearing aid users less likely to obtain needed care, but this fear may be overstated. Hearing aid users generally indicate that verification measures and counseling increase satisfaction and perceived value of hearing aids (Kochkin, 2010; 2011), so follow-up care can be perceived by the patient as a valuable part of the rehabilitative process. Unbundling offers the additional benefit for private practices because fee-for-service appointments lead to more consistent monthly cash flow than bundled fees in which a large initial payment is received with free services for a long time thereafter.

The manner in which hearing aids are represented to the general public may further impact uptake. Hearing aids are best positioned as medical devices, prescribed by skilled professionals, in clinical settings where testing is performed in controlled acoustic environments. If price is prioritized, then testing, verification and follow-up care may be abbreviated to control costs. If cosmetic appeal is prioritized, patients may select the smallest devices, perhaps without adequate venting or directional microphones, though this might not be the best option for their loss and listening needs. The potential outcome of both scenarios is disappointment with the performance and comfort of the hearing instruments, resulting in either lack of use or return for credit.  Instead, hearing aid users need to be fully educated about the options that are available and counseled as to why some models are better for their needs than others. This cannot be achieved in an environment that emphasizes price over functionality and service.

As Dawes points out, hearing impairment may be better defined by speech recognition ability in everyday situations, rather than pure tone audiometry. Even so, it is arguable whether either of these measures alone should be used to define hearing aid candidacy. Instead, clinicians gain more insight into their patients’ motivation and readiness by examining how the hearing loss affects their ability to function in their regular activities. A mildly-impaired individual with a quiet, socially inactive lifestyle is less likely to be motivated for hearing aids than a similarly impaired individual who works full time and has an active social life. A thorough patient history and needs assessment, coupled with objective testing can more accurately identify hearing aid candidates than relying on degree of hearing loss alone. The authors of this article cite a study of Swiss hearing aid use and satisfaction, stating that in Switzerland, hearing aid candidacy is “based on the degree of social and emotional handicap due to hearing loss” and that the dispensing process focuses on ongoing counseling and care after the fitting.  This study reported high rates of long-term hearing aid use and satisfaction, where 97% of Swiss hearing aid owners reported using their hearing aids and only 3% were non-users (Bertoli, 2009).

It makes sense to advise unmotivated individuals to assess their difficulties, making note of every time they ask for repetition, misunderstand a word or sentence, or smile and “fake” their way through a conversation. I instruct patients to consider whether their hearing loss causes them to avoid places or situations that they might otherwise enjoy or if the hearing loss affects their ability to perform important work-related or social activities.  With a little patience and attention, most people can determine the point at which they are ready to proceed with a hearing aid purchase. Self-recognition of need is strongly associated with eventual hearing aid uptake and use (Vestergaard-Knudsen et al., 2010), meaning that a person who returns for a consultation after taking time to evaluate their difficulties is more likely to keep their hearing aids and follow through with proper use and care.

Even as testing techniques and prevalence data improve our ability to identify those with hearing impairment and those at risk, there remain barriers to hearing aid use. Consistent representation of hearing aids as medical devices that are fitted by clinical professionals may improve the perception and attitudes of the general public. Unbundled pricing may lower the cost barrier by making the initial purchase more affordable and concomitantly emphasizing the value of follow-up care. Finally, development and adherence to a thorough fitting protocol will ensure that those who do purchase hearing aids will receive a well-prescribed medical device and become an example of success to others.

 

References

Davis, A. (1995). Hearing in adults. London, United Kingdom: Whurr Publishers Ltd. XXX.

Davis, A., Smith, P., Ferguson, M. (2008).  Acceptability: benefit and costs of early screening for hearing disability: A study of potential screening tests and models. Health Technology Assessment 11 (42), 1-294.

Dawes, P., Fortnum, H., Moore, D., Emsley, R., Norman, P., Cruickshanks, K., Davis, A., Edmondson-Jones, M., McCormack, A., Lutman, M. & Munro, K.  (2014) Hearing in middle age: a population snapshot of 40- to 69-year olds in the United Kingdom. Ear & Hearing 35 (3), 44-51.

Department of Health (2001). Health Survey for England 1999: The health of minority ethnic groups. Retrieved from http://webarchiv.nationalarchives.gov.uk/+/www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsStatistics/DH_4009393.

Kochkin, S. (2010). MarkeTrak VIII: Customer satisfaction with hearing aids is slowly increasing. Hearing Journal 63(1), 11-19.

Kochkin, S. (2011). MarkeTrak VIII: Reducing patient visits through verification and validation. Hearing Review 18 (6), 10-12.

McCormack, A. & Fortnum, H. (2013). Why do people fitted with hearing aids not wear them? International Journal of Audiology 52, 360-368.

Plomp, R. & Mimpen, A. (1979). Speech reception threshold for sentences as a function of age and noise level. Journal of the Acoustical Society of America 66, 1333-1342.

Smits, C., Kapteyn, T. & Houtgast, T. .(2004). Development and validation of an automatic speech-in-noise screening test by telephone. International Journal of Audiology 43, 15-28.

Smits, Kramer, S. & Houtgast, T. (2006). Speech reception thresholds in noise and self-reported hearing disability in a general adult population. Ear and Hearing 27, 538-549.

Vestergaard-Knudsen, L., Oberg, M. & Nielsen, C. (2010). Factors influencing help seeking, hearing aid uptake, hearing aid use and satisfaction with hearing aids: A review of the literature. Trends in Amplification 14, 127-154.

Wilson, D. & Strouse, A. (2002). Northwestern University Auditory Test No. 6 in multi-talker babble: A preliminary report. Journal of Rehabilitation Research and Development 39, 105-113.

The most important factors behind directional microphone benefit

Keidser, G., Dillon, H., Convery, E. & Mejia, J. (2013). Factors influencing individual variation in perceptual directional microphone benefit. Journal of the American Academy of Audiology 24, 955-968.

This editorial discusses the clinical implications of an independent research study and does not represent the opinions of the original authors.

Understanding conversation in noisy environments is one of the most common difficulties for individuals with hearing loss. Counseling and training in communication strategies can help listeners with hearing loss make use of supplemental cues to improve speech understanding in noise. However, no hearing aid feature or clinical intervention is as likely to improve the ability to function in noise as directional microphones. Directional microphones, usually twin microphone designs, offer small but helpful increases in the signal-to-noise ratio, facilitating more comfortable listening and an improved ability to understand speech and function in noisy everyday situations.

Directionality consistently demonstrates benefits to speech perception performance in laboratory studies but the amount of directional benefit achieved by subjects is highly variable, even in studies with similar methods and procedures (Freyaldenhoven et al., 2005). A number of factors have been studied and reports have indicated that variability in directional benefit was unrelated to age (Wu, 2010; O’Brien et al, 2009), degree or configuration of hearing loss (Jesperson & Olsen, 2003; Ricketts & Mueller, 2000) or vent size (Ricketts, 2000; O’Brien et al, 2009). Furthermore, laboratory studies may not always predict everyday performance (Walden et al., 2000; Cord et al., 2002; Cord et al., 2004) so it is unclear how numerous factors could converge to affect individual directional benefit in everyday hearing aid use.

Recently emerging evidence has suggested that cognitive capacity may affect a listener’s ability to make use of directional benefits. Working memory affected hearing aid users’ performance with regard to different compression time constants (Gatehouse et al., 2003; Cox & Xu, 2010) and spatial separation ability (Neher et al., 2009). Dawes et al (2010) reported that differences in hearing aid benefit were partly determined by performance on speed of processing, selective attention and switching tasks. Humes (2007) further reported that cognition may affect individual speech perception abilities in noise. Though cognition declines with age, the changes vary tremendously across individuals and cannot be predicted by age alone (Glisky, 2007), so age and cognition, though related, may affect hearing aid use and speech perception in different ways.

The primary goal of Keidser et al’s study was to investigate the factors that contribute to variability in perceptual directional microphone benefit as measured in the laboratory. Specifically, they were interested in the effects and interaction of three potential sources of variability: differences in the individual SNR achieved by physical directional benefit, differences in the ability to make use of SNR improvements and variability related to measurement error.

Fifty-nine subjects participated in the study. All had bilateral, mild-to-moderate, sensorineural hearing loss.  Age ranged from 54 to 91 years, with an average of 74 years. Of the 59 subjects, 51 had experience with amplification, whereas 8 had never worn hearing aids. For the purpose of the study, subjects were fitted with binaural, behind-the-ear hearing aids with dual-microphones and wide dynamic range compression. Advanced signal processing such as noise reduction and adaptive directionality was turned off. Hearing aids were programmed according to NAL-NL2 targets and had two programs: omnidirectional and directional.

Participants attended two experimental sessions. At the first session, subjects completed cognitive testing. First, they were administered subtests of the Test of Everyday Attention (TEA; Robertson et al., 1996) which uses real-life scenarios to measure auditory selective attention and speed of processing. Working memory was assessed using the Reading Span Test (RST; Daneman & Carpenter, 1980).  In the RST, sentences are presented on a computer screen and subjects indicate whether the sentence was meaningful or not, subjects must also recall either the first or last word of each sentence.

At the second session, hearing aids and earmolds were fitted and vent diameters were measured. The frequency range of amplification was measured, with the low frequency limit (f-amp) defined as the point at which real-ear insertion gain exceeded 3dB. The angle of the microphone ports was measured with reference to the loudspeaker axis. Speech in noise testing was completed, using the Australian Bamford-Kowal-Bench (BKB/A) sentences (Bench et al., 1979) in the presence of 8-talker babble from the NAL Speech and Noise for Hearing Aid Evaluation CD (Keidser et al, 2002). Speech was presented from a loudspeaker 1m in front of the subject. A constant level of uncorrelated multi-talker babble was presented from four loudspeakers surrounding the subject at a distance of 2m. Speech levels were adjusted to arrive at the SNR required to achieve 50% performance.

Following speech in noise testing, individual in-situ SNR levels were measured to determine how room acoustics may have affected hearing aid performance.  Individual 3D AI-DI measurements were obtained to ascertain the physical directional benefit for each subject in the test environment. The 3D AI-DI scores are directivity measurements weighted by the Articulation Index model, as measured in the center of a 3D array of 41 loudspeakers (Killion et al, 1998). In-situ SNR and 3D-AI-DI measures were computed for broadband (BB), low-frequency (LF, <2000Hz) and high-frequency (HF, >2000Hz) ranges.

Cognitive test scores were weakly correlated. The only auditory cognitive test, the ASA, was not correlated with audiological pure tone average (PTA) but was weakly correlated with age. For the physical measures, broadband (BB) and low-frequency (LF) in-situ SNRs were strongly correlated with each other. The low-frequency limit or f-amp, was highly correlated to the LF in-situ measures as well as to PTA and vent diameter. These correlations indicate that participants who had higher PTAs (more hearing loss) had smaller vent diameters, frequency responses extending further into the low-frequencies and more physical benefit from directional microphones at low frequencies.

The average perceptual directional benefit as measured by SRTn was 2.7dB, with a range from 0.3 to 5.3dB.  No participants showed negative effects of directionality.  When comparing benefit ranges in individual trials versus the mean of the three trials, effectively removing any variability attributable to random measurement errors, the range of benefit was reduced from around 9.2 dB to 5.0dB. Therefore, about half of the variation in directional microphone benefit was explained by measurement errors.  Variation in perceptual directional benefit was not correlated with age or configuration (slope) of hearing loss. Analysis of the cognitive and the in-situ measures of physical directionality showed that the only factors exerting a significant effect on perceptual benefit were LF 3D AI-DI, ASA scores and microphone angle.

With reference to the goals of their study, Keidser and her colleagues found that measurement error, physical directionality and the individual ability to make use of directional cues may contribute to variability in perceptual directional benefit. About half of the variability in measured perceptual directional benefit was attributable to measurement error associated with speech-in-noise testing. Measurement error could include head movements during testing causing brief head shadow effects, problems with speech test list equivalence (Dillon, 1982) and potential practice effects. The authors suggest that multiple measurements of perceptual directional benefit, in each test condition, should always be carried out in order to mitigate the effects of measurement error.

In agreement with previous reports, there was no direct relation between perceptual directional benefit and age, PTA or configuration of hearing loss, though there was a relation to vent diameter. Greater perceptual directional benefit was derived when greater physical directivity was achieved in the low frequencies, which was related to decreased vent diameter. This result is in agreement with previous work showing increased directional benefit with more occluded molds as compared to more open fittings (Ricketts, 2000; Fabry, 2006; Klemp & Dhar, 2008).

A more upward-pointing microphone angle was associated with improved perceptual directional benefit. This is in agreement with a report by Ricketts (2000) that showed increased physical directivity as microphone angle exceeded 20 degrees from the horizontal plane. The effect of microphone angle in the current study was small, accounting for only 4% of the variation. Because the interaction of microphone angle with other hearing aid and environmental characteristics is unknown, the authors do not recommend that clinicians deliberately fit hearing aids with microphones pointing upward.

The outcomes of this study emphasize the importance of low-frequency amplification to achieve optimal directional benefit. The lower limit of the amplification range as well as vent diameter have an effect on physical directivity that affects the perceptual benefit that can be derived from directionality. Thus, it is of particular importance for clinicians to not only select appropriate venting characteristics for each individual, but to ensure that the range of amplification is set in a manner that accounts for venting effects. Programming software requires the entry of acoustic parameters to guide frequency response characteristics, especially in the low frequency range; failure to enter the correct acoustic properties risks over or under amplifying the low-frequency range.

Of course there are many factors to consider when choosing venting, gain and output characteristics, but achieving optimal directional benefit should be considered among them.  Equalizing low-frequency gain in a directional program for use in noise may be advisable to achieve better directivity, but conversely, reduction of low-frequency gain in noise programs may be more comfortable and therefore more desirable for hearing aid users. Careful consideration of the way in which these variables interact for each individual is critical to their success with hearing aids in their daily activities.

 

References

Bench, R., Doyle, J., Daly, N. & Lind, C. (1979). The BKB/A Speech Reading (Lipreading) Test. Victoria: La Trobe University.

Cord, M., Surr, R., Walden, B. & Olson, L. (2002). Performance of directional microphone hearing aids in everyday life. Journal of the American Academy of Audiology 13 (6), 295-307.

Cord, M., Surr, R., Walden, B. & Dyrlund, O. (2004). Relationship between laboratory measures of directional advantage and everyday success with directional microphone hearing aids. Journal of the American Academy of Audiology 15(5), 353-364.

Cox, R. & Xu, J. (2010). Short and long compression release times: speech understanding, real world preferences and association with cognitive ability. Journal of the American Academy of Audiology 21(2), 121-138.

Daneman, M. & Carpenter, P. (1980). Individual differences in working memory and reading. Journal of Verbal Learning and Verbal Behavior 19(4), 450-466.

Dawes, P., Munro, K., Kalluri, S., Nooraei, N. & Edwards, B. (2010). Older adults, hearing aids and listening effort. Paper presented at IHCON, August 11-15, Lake Tahoe.

Dillon, H. (1982). A quantitative examination of the sources of speech discrimination test score variability. Ear and Hearing, 3(2), 51-58.

Fabry, D. (2006). Facts vs. myths: the “skinny” on open-fit hearing aids. Hearing Review 13, 20-25.

Freyaldenhoven, M., Nabelek, A., Burchfield, S. & Thelin, J. (2005). Acceptable noise level as a measure of directional hearing aid benefit. Journal of the American Academy of Audiology 16(4), 228-236.

Gatehouse, S., Naylor, G. & Elberling, C. (2003). Benefits from hearing aids in relation to the interaction between the user and the environment. International Journal of Audiology 42 (Suppl. 1), S77-S85.

Glisky, E. (2007). Changes in cognitive function in human aging. In: Riddle DR, ed. Brain Aging: Models, Methods and Mechanisms. Boca Raton, FL: CRC Press, chpt. 1. www.ncbi.nlm.nih.gov/books/NBK3885.

Humes, L. (2007). The contributions of audibility and cognitive factors to the benefit provided by amplified speech to older adults. Journal of the American Academy of Audiology 18(7), 590-603.

Jesperson, C. & Olsen, S. (2003). Does directional benefit vary systematically with omnidirectional performance? Hearing Review 10, 16-24, 62.

Keidser, G., Ching, T. & Dillon, H. (2002). The National Acoustic Laboratories’ (NAL) CDs of Speech and Noise for Hearing Aid Evaluation: normative data and potential applications. Australian New Zealand Journal of Audiology 24(1), 16-35.

Keidser, G., Dillon, H., Convery, E. & Mejia, J. (2013). Factors influencing individual variation in perceptual directional microphone benefit. Journal of the American Academy of Audiology 24, 955-968.

Killion, M., Schulein, R. & Christensen, L. (1998). Real-world performance of an ITE directional microphone. Hearing Journal 51(4), 24-38.

Klemp, E. & Dhar, S. (2008). Speech perception in noise using directional microphones in open canal hearing aids. Journal of the American Academy of Audiology 19(7), 571-578.

Neher, T., Behrens, T. & Carlile, S. (2009). Benefit from spatial separation of multiple talkers in bilateral hearing aid users: effects of hearing loss, age and cognition. International Journal of Audiology 48 (11), 758-774.

O’Brien, A., McLelland, M. & Keidser, G. (2009). The Effect of Asymmetric Directionality on Speech Recognition in Noise. NAL Report 019. Sydney: National Acoustic Laboratories.

Ricketts, T. & Mueller, H. (2000). Predicting directional hearing aid benefit for individual listeners. Journal of the American Academy of Audiology 11(10), 561-569.

Ricketts, T. (2000). Directivity quantification in hearing aids: fitting and measurement effects. Ear and Hearing 21(1), 45-58.

Robertson, I., Ward, T., Ridgeway, V. & Nimmo-Smith, I. (1996). The structure of normal human attention: the Test of Everyday Attention. Journal of the International Neuropsychological Society 2(6), 525-534.

Walden, B., Surr, R., Cord, M., Edwards, B. & Olson, L. (2000). Comparison of benefits provided by different hearing aid technologies. Journal of the American Academy of Audiology 11(10), 540-560.

Wu, Y. (2010). Effect of age on directional microphone hearing aid benefit and preference. Journal of the American Academy of Audiology 21(2), 78-89.

 

Acclimatizing to hearing aids may not mean what you think it means

Dawes, P., Munro, K., Kalluri, S., & Edwards, B. (2014). Acclimatization to hearing aids. Ear and Hearing, Published Ahead-of-Print.

This editorial discusses the clinical implications of an independent research study and does not represent the opinions of the original authors.

New patients frequently report that their new hearing aids sound tinny, metallic, loud, or unnatural. The clinical audiologist recognizes that these comments will decrease in frequency with time. A process often described as acclimatization: a reaction to new hearing aids that occurs because the patient has adjusted to hearing sound filtered by their hearing loss. When amplification is introduced, the subsequent increase in audibility and loudness perception is unfamiliar and therefore unnatural.

A smooth transition to hearing aid use can be achieved through counseling prior to fitting, preparing the individual for a period of unnatural sound quality. At the fitting, the instruments can be set below prescribed target, allowing the listener a more comfortable period of adjustment. Most individuals will accept increased gains, approaching prescribed target over 2 or 3 months. Some patients, however, require a much longer period of acclimatization of one to two years (Keidser, et al., 2008).

In addition to changes in the preferred gain of new hearing aid users, other improvements due to acclimatization have been proposed: speech discrimination over time (Bentler, et al.1993a, Gatehouse, 1992), subjective benefit and sound quality over time (Bentler, et al., 1993b; Ovegard, et al., 1997) and loudness perception and intensity discrimination over time (Olsen, et al., 1999; Philibert et al., 2002). Most of these studies reported small but significant acclimatization effects; while others found no significant differences between new and experienced hearing aid users (Smeds et al, 2006a, 2006b).

Ultimately, there is little agreement on the definition of this effect and even less agreement in the methods that quantify these changes. A high degree of response variability is usually noted, indicating that several factors (degree, etiology, and configuration of hearing loss) may contribute to the adjustment that is experienced by new hearing aid users.

Dawes and his colleagues outlined a number of goals for their study:  First, they hoped to determine if there is an acclimatization effect for aided speech recognition with current, nonlinear hearing aids and if there is a difference between unilateral and bilateral fittings. Second, they wanted to know if new hearing aid users’ self-reports would indicate a period of acclimatization. Third, they sought to determine if acclimatization could be predicted by the degree of hearing loss, prior hearing aid use or cognitive capacity.

Forty-nine subjects participated in the study, recruited from four audiology clinics. There were 16 new unilateral hearing aid users, 16 new bilateral users and 17 experienced users, including 8 bilateral and 9 unilateral users. Experienced subjects used their own hearing aids and new users were fitted with BTE or CIC instruments with comparable circuit technology.  New instruments were fitted to NAL-NL1 targets and verified with real-ear measurements. Newly-fitted subjects had a few days of hearing aid use prior to commencement of the study and were allowed gain adjustments only if necessary due to discomfort with prescribed gain levels.

To measure speech recognition, a 4-alternative forced-choice procedure was used, in which listeners were asked to select one word from a closed set of four rhyming words, in response to the prompt, “Can you hear the word X clearly?” In addition to the speech recognition test, subjects completed the Spatial, Speech and Qualities of Hearing Questionnaire – Difference version (SSQ-D; Gatehouse & Noble, 2004), as well as two measures of cognitive processing. The SSQ-D was administered after 12 weeks and allowed the subjects to judge their own changes in performance and listening effort with the hearing aids over the course of the study.

Two cognitive tests were administered. The first, a visual reaction time task, required participants to watch digits presented on a computer monitor and press the corresponding numbers on a keypad as quickly as possible. Responses were scored as correct or incorrect and response times were measured in milliseconds. Working memory was also evaluated, using the Digits Backwards subtest from the Weschler Adult Intelligence Scale – III (WAIS-III; Wechsler, 1997).  Subjects listened to lists of digits and were asked to repeat them in reverse order. Lists increased in length as the test progressed and responses were correct if all digits were repeated in the correct order.

In all test conditions, variability was high and a small improvement was noted over time, likely due to practice effects. The mean SNR required to achieve 50% performance did not differ between new unilateral and new bilateral hearing aid users, but experienced users required significantly more favorable SNRs to achieve this level of performance, compared to new users. This was attributed to the older average age and poorer hearing thresholds of the experienced user group.

For the new user groups, if acclimatization occurred it was expected that performance would improve in aided conditions over time. Instead there were small trends of improvements in unaided and aided conditions. For unilateral users, the trend was noted in the fitted ear, whereas for bilateral users, small improvements were noted for both ears.  Of all the variables studied, the only one to have a significant effect on performance was time, which yielded a small consistent improvement across groups and listening conditions.  When place, manner and voicing errors were analyzed, there was no significant difference for type of error, nor was there a significant interaction with the other variables of group, aiding, ear or presentation level.

Because of the high variability in responses, correlations were measured for effects of hearing aid usage, degree of hearing loss, cognitive capacity, and a change in audibility referred to as “stimulus novelty”. For new hearing aid users, there was no significant correlation between the change speech recognition scores, severity of hearing loss, cognitive test score, or hearing aid variables. Older age was only correlated with slower reaction time scores and a higher amount of time spent in quiet conditions. There were no significant correlations for SSQ-D scores and change in aided performance in any of the listening conditions. Disparate SSQ-D scores did indicate that new hearing aid users perceived improvements over the course of the study, whereas experienced users did not.

Though there were small increases in speech recognition performance over time in all conditions, this was consistent with a practice effect and was not taken as evidence for acclimatization. Self-reports from the SSQ-D showed that new users experienced improvements with amplification that were significantly greater than those reported for experienced users. It is not surprising that SSQ-D scores might still show improvement, as the SSQ-D probes subjective perceptions of performance, including listening effort and sound quality. These elements may well improve with consistent use of new hearing aids even if actual speech recognition has not changed significantly. Improved audibility may allow the listener to function well in everyday environments with significantly less effort, making a positive impression on the listener, more so than small but measurable improvements in word recognition.

Another potential explanation for the lack of agreement between objective and subjective measures in this study could be related to the actual comparison that was made by the subjects when the responded to the SSQ-D items.  Because new users probably experienced noticeable benefits from the hearing aids, they may have had trouble comparing their performance immediately post-fitting versus 12 weeks later and may have inadvertently compared pre-fitting and post-fitting performance, yielding a larger SSQ-D score.

Though the results of this study did not support an acclimatization effect for speech recognition, they do not rule out the existence of acclimatization altogether. Preferred gain, perceived listening effort, and sound quality improvements, among other effects, may well occur for most new hearing aid users, to varying degrees based on degree of hearing loss, duration of prior hearing loss and prior experience with hearing aids.

The subjects in this study were fitted with either BTE or CIC hearing aids but the hearing aid style was not examined with regard to acclimatization. CIC users often experience occlusion and adjustment to their own voices in the early days of hearing aid use; much more so than BTE users who probably have less occlusion than commonly found with CIC hearing aids. Whether this could have an impact on speech recognition acclimatization is questionable, but it could have affect subjective reports. Similarly, individuals using hearing aid features such as frequency-lowering or wireless routing of signal may demonstrate other perceptual learning or acclimatization effects.

Perhaps the greatest finding of this study was the contrast between measurable outcomes in the domain of subjective spatial perception and traditional measures of speech recognition. Many failed attempts to document acclimatization have focused on speech recognition or loudness perception rather than probing the patient’s perception of their acoustic environment—something achieved with the SSQ-D. The apparent sensitivity of this measure should direct future experimental design in this area. For the practicing clinician, this contrast can aid in developing counseling approaches: it’s clear that speech recognition won’t change over time, but the complexity or overwhelming nature of the acoustic environment may become simpler with time.

References

Bentler, R.A., Niebuhr, D.P., Getta, J.P. & Anderson, C.V. 1993a. Longitudinal study of hearing aid effectiveness. I. Objective measures.  Journal of Speech and Hearing Research 36, 808-819.

Gatehouse, S. 1992. The time course and magnitude of perceptual acclimatization to frequency responses: Evidence from monaural fitting of hearing aids. Journal of the Acoustical Society of America 92, 1258-1268.

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

Keidser, G., O’Brien, A., Carter, L., McLelland, M., and Yeend, I. (2008). Variation in Preferred Gain with Experience for Hearing-Aid Users.  International Journal of Audiology 47 (10), 621 – 635.

Munro, K.J. & Lutman, M.E. 2003. The effect of speech presentation level on measurement of auditory acclimatization to amplified speech.  Journal of the Acoustical Society of America, 114, 484-495.

Ovegard, A., Lundberg, G., Hagerman, B., Gabrielsson, A., Bengtsson, M. 1997. Sound quality judgment during acclimatization of hearing aid. Scandinavian Audiology, 26, 43-51.

Palmer, C.V., Nelson, C.T. & Lindley, G.A. 1998. The functionally and physiologically plastic adult auditory system. Journal of the Acoustical Society of America, 103, 1705-1721.

Philibert, B., Collet, L., Vesson, J.F. & Veuillet, E. 2002. Intensity-related performances are modified by long-term hearing aid use: A functional plasticity? Hearing Research, 165, 142-151.

Philibert, B., Collet, L., Vesson, J.F. & Veuillet, E. 2005. The auditory acclimatization effect in sensorineural hearing-impaired listeners: Evidence for functional plasticity. Hearing Research, 205, 131-142.

Ronnberg, J., Rudner, M. & Foo, C. (2008). Cognition counts: A working memory system for ease of language understanding (ELU). International Journal of Audiology 47 (Suppl 2), S99-105.

Saunders, G.H. & Cienkowski, K. (1997). Acclimatization to hearing aids. Ear and Hearing 18, 129-139.

Smeds, K., Keidser, G., Zakis, J., Dillon, H., Leijon, A. 2006a. Preferred overall loudness. I. Sound field presentation in the laboratory. International Journal of Audiology, 45, 12-25.

Smeds, K., Keidser, G., Zakis, J., Dillon, H., Leijon, A. 2006b. Preferred overall loudness. II. Listening through hearing aids in field and laboratory tests. International Journal of Audiology, 45, 12-25.

Taubman, L., Palmer, C. & Durrant, J. (1999). Accuracy of hearing aid use time as reported by experienced hearing aid wearers. Ear and Hearing 20, 299-305.

Wechsler, D. (1997). Wechsler Adult Intelligence Scale (3rd ed.) Oxford: Pearson Assessment.

Willott, J.F. 1996. Physiological plasticity in the auditory system and its possible relevance to hearing aid use, deprivation effects, and acclimatization. Ear and Hearing, 17, 66S-77S.

Yund, E.W., Roup, C.M. & Simon, H.J. (2006). Acclimatization in wide dynamic range multichannel compression and linear amplification hearing aids.  Journal of Rehabilitation Research and Development 43, 517-536.

On the Prevalence of Cochlear Dead Regions

Pepler, A., Munro, K., Lewis, K. & Kluk, K. (2014). Prevalence of Cochlear Dead Regions in New Referrals and Existing Adult Hearing Aid Users. Ear and Hearing 20(10), 1-11.

This editorial discusses the clinical implications of an independent research study and does not represent the opinions of the original authors.

Cochlear dead regions are areas in which, due to inner hair cell and/or nerve damage, responses to acoustic stimuli occur not at the area of peak basilar membrane stimulation but instead occur at adjacent regions in the cochlea. Professor Brian Moore defined dead regions as a total loss of inner hair cell function across a limited region of the basilar membrane (Moore, et al., 1999b). This hair cell loss does not result in an inability to perceive sound at a given frequency range, rather the sound is perceived via off-place or off-frequency listening, a spread of excitation to adjacent regions in the cochlea where inner hair cells are still functioning (Moore, 2004).  Because the response is spread across a broad tonotopic area, individuals with cochlear dead regions may perceive pure tones as “clicks”, “buzzes” or “whooshes”.

Cochlear dead regions are identified and measured by a variety of masking techniques. The most accurate method is the calculation of psychophysical tuning curves (PTCs), originally developed to measure frequency selectivity (Moore & Alcantara 2001). A PTC plots the level required to mask a stimulus frequency as a function of the masker frequency. For a normally hearing ear, the PTC peak will align with the point at which the stimulus can be masked by the lowest level masker.  In ears with dead regions, the tip of the PTC is shifted off of the signal frequency to indicate that the signal is being detected in an adjacent region. Though PTCs are an effective method of identifying and delineating the edges of cochlear dead regions, they are time consuming and ill-suited to clinical use.

The test used most frequently for clinical identification of cochlear dead regions is the Threshold Equalizing Test (TEN; Moore et al., 2000; 2004). The TEN test was developed with the idea that tones detected by off-frequency listening, in ears with dead regions, should be easier to mask with broadband noise than they would in ears without dead regions. With the TEN (HL) test, masked thresholds are measured across the range of 500Hz to 4000Hz, allowing the approximate identification of a cochlear dead region.

There are currently no standards for clinical management of cochlear dead regions. Some reports suggest that affect speech, pitch, loudness perception, and general sound quality (Vickers et al., 2001; Baer et al., 2002; Mackersie et al., 2004; Huss et al., 2005a; 2005b). Some researchers have specified amplification characteristics to be used with patients with diagnosed dead regions, but there is no consensus and different studies have arrived at conflicting recommendations. While some recommend limiting amplification to a range up to 1.7 times the edge frequency of the dead region (Vickers et al., 2001; Baer et al., 2002), others advise the use of prescribed settings and recommend against limiting high frequency amplification (Cox et al., 2012; see link for a review).  Because of these conflicting recommendations, it remains unclear how clinicians should modify their treatment plans, if at all, for hearing aid patients with dead regions.

Previous research on the prevalence of dead regions has reported widely varying results, possibly due to differences in test methodology or subject characteristics. In a study of hearing aid candidates, Cox et al. (2011) reported a dead region prevalence of 31%, but their strict inclusion criteria likely missed individuals with milder hearing losses, so their prevalence estimate may be different from that of hearing aid candidates at large. Vinay and Moore (2007) reported higher prevalence of 57% in a study that did include individuals with thresholds down to 15dB HL at some frequencies, but the median hearing loss of their subjects was higher than that of the Cox et al. study, which likely impacted the higher prevalence estimate in their subject group.

In the study being reviewed, Pepler and her colleagues aimed to determine how prevalent cochlear dead regions are among a population of individuals who have or are being assessed for hearing aids. Because dead regions become more likely as hearing loss increases, and established hearing aid patients are more likely to have greater degrees of hearing loss, they also investigated whether established hearing aid patients would be more likely to have dead regions than newly referred individuals.  Finally, they studied whether age, gender, hearing thresholds or slope of hearing loss could predict the presence of cochlear dead regions.

The researchers gathered data from a group of 376 patients selected from the database of a hospital audiology clinic in Manchester, UK. Of the original group, 343 individuals met inclusion criteria; 193 were new referrals and 150 were established patients and experienced hearing aid users.  Of the new referrals, 161 individuals were offered and accepted hearing aids, 16 were offered and declined hearing aids and 16 were not offered hearing aids because their losses were of mild degree.  The 161 individuals who were fitted with new hearing aids were referred to as “new” hearing aid users for the purposes of the study. All subjects had normal middle ear function and otoscopic examinations and on average had moderate sensorineural hearing losses.

When reported as a proportion of the total subjects in the study, Pepler and her colleagues found dead region prevalence of 36%.  When reported as the proportion of ears with dead regions, the prevalence was 26% indicating that some subjects had dead regions in one ear only. Follow-up analysis on 64 patients with unilateral dead regions revealed that the ears with dead regions had significantly greater audiometric thresholds than the ears without dead regions. Only 3% of study participants had dead regions extending across at three or more consecutive test frequencies. Ears with contiguous dead regions had greater hearing loss than those without.  Among new hearing aid users, 33% had dead regions while the prevalence was 43% among experienced hearing aid users. On average, the experienced hearing aid users had poorer audiometric thresholds on average than new users.

Pepler and colleagues excluded hearing losses above 85dB HL because effective TEN masking could not be achieved. Therefore, dead regions were most common in hearing losses from 50 to 85dB HL, though a few were measured below that range. There were no measurable dead regions for hearing thresholds below 40dB HL. Ears with greater audiometric slopes were more likely to have dead regions, but further analysis revealed that only 4 kHz thresholds had a significant predictive contribution and the slopes of high-frequency hearing loss only predicted dead regions because of the increased degree of hearing loss at 4 kHz.

Demographically, more men than women had dead regions in at least one ear, but their audiometric configurations were different: women had poorer low frequency thresholds whereas men had poorer high frequency thresholds. It appears that the gender effect actually due to the difference in audiometric configuration, specifically the men’s poorer high frequency thresholds. A similar result was reported for the analysis of age effects. Older subjects had a higher prevalence of dead regions but also had significantly poorer hearing thresholds.  Though poorer hearing thresholds at 4kHz did slightly increase the likelihood of dead regions, regression analysis of the variables of age, gender and hearing thresholds found that none of these factors were significant predictors.

Pepler et al’s prevalence data agree with the 31% reported by Cox et al (2012), but are lower than that reported by Vinay and Moore (2007), possibly because the subjects in the latter study had greater average hearing loss than those in the other studies.  But when Pepler and her colleagues used similar inclusion criteria to the Cox study, they found a prevalence of 59%, much higher than the report by Cox and her colleagues and likely due to the exclusion of subjects with normal low frequency hearing in the Cox study. The authors proposed that Cox’s exclusion of subjects with normal low frequency thresholds could have reduced the overall prevalence by increasing the proportion of subjects with metabolic presbyacusis and eliminating some subjects with sensory presbyacusis—sensory presbyacusis is often associated with steeply sloping hearing loss and involves atrophy of cochlear structures (Shuknecht, 1964).

 In summary:

The study reported here shows that roughly a third of established and newly referred hearing aid patients are likely to have at least one cochlear dead region, in at least one ear. A very low proportion (3% reported here) of individuals are likely to have dead regions spanning multiple octaves. The only factor that predicted the presence of dead regions was hearing threshold at 4 kHz.

On the lack of clinical guidance:

As more information is gained about prevalence and risk factors, what remains missing are clinical guidelines for management of hearing aid users with diagnosed high-frequency dead regions. Conflicting recommendations have been proposed for either limiting high frequency amplification or preserving high frequency amplification and working within prescribed targets. The data available today suggest that prevalence of contiguous multi-octave dead regions is very low and a further subset of hearing aid users with contiguous dead regions experience any negative effects of high-frequency amplification. With consideration to these observations, it seems prudent that the prescription of high-frequency gain should adhere to the prescribed targets for all patients at the initial fitting. Any reduction to high-frequency gains should be managed as a result of subjective feedback from the patient after they have completed a trial period with their hearing aids.

On frequency lowering and dead regions:

Some clarity is required regarding the role of frequency lowering and the treatment of cochlear dead regions. Because acoustic information in speech extends out to 10 kHz and because most hearing aid frequency responses roll off significantly after 4-5 kHz, the mild prescription of frequency lowering can be beneficial to many hearing aid users. It must be noted that the benefits of this technology arise largely from the acoustic limitations of the device and not the presence or absence of a cochlear dead region. There are presently no recommendations for the selection of frequency lowering parameters in cases of cochlear dead regions. In the absence of these recommendations, the best practice for the prescription of frequency lowering would follow the same guidelines as any other patient with hearing loss; validation and verification should be performed to document benefit with the algorithm and identify appropriate selection of algorithm parameters.

On the low-frequency dead region: 

The effects of low-frequency dead regions are not well studied and may have more significant impact on hearing aid performance.  Hornsby (2011) reported potential negative effects of low frequency amplification if it extends into the range of low-frequency dead regions (Vinay et al., 2007; 2008). In some cases performance decrements reached 30%, so the authors recommended using low-frequency gain limits of 0.57 times the low-frequency edge of the dead region in order to preserve speech recognition ability. Though dead regions are less common in the low frequencies than in the high frequencies, more study on this topic is needed to determine clinical testing and treatment implications.

References

Baer, T., Moore, B. C. and Kluk, K. (2002). Effects of low pass filtering on the intelligibility of speech in noise for people with and without dead regions at high frequencies. Journal of the Acoustical Society of America 112(3 Pt 1), 1133-44.

Cox, R., Alexander, G., Johnson, J., Rivera, I. (2011). Cochlear dead regions in typical hearing aid candidates: Prevalence and implications for use of high-frequency speech cues. Ear and Hearing 32(3), 339 – 348.

Cox, R.M., Johnson, J.A. & Alexander, G.C. (2012).  Implications of high-frequency cochlear dead regions for fitting hearing aids to adults with mild to moderately severe hearing loss. Ear and Hearing 33(5), 573-87.

Hornsby, B. (2011) Dead regions and hearing aid fitting. Ask the Experts, Audiology Online October 3, 2011.

Huss, M. & Moore, B. (2005a). Dead regions and pitch perception. Journal of the Acoustical Society of America 117, 3841-3852.

Huss, M. & Moore, B. (2005b). Dead regions and noisiness of pure tones. International Journal of Audiology 44, 599-611.

Mackersie, C. L., Crocker, T. L. and Davis, R. A. (2004). Limiting high-frequency hearing aid gain in listeners with and without suspected cochlear dead regions. Journal of the American Academy of Audiology 15(7), 498-507.

Moore, B., Huss, M. & Vickers, D. (2000). A test for the diagnosis of dead regions in the cochlea. British Journal of Audiology 34, 205-224.

Moore, B. (2004). Dead regions in the cochlea: Conceptual foundations, diagnosis and clinical applications. Ear and Hearing 25, 98-116.

Moore, B. & Alcantara, J. (2001). The use of psychophysical tuning curves to explore dead regions in the cochlea. Ear and Hearing 22, 268-278.

Moore, B.C., Glasberg, B. & Vickers, D.A. (1999b). Further evaluation of a model of loudness perception applied to cochlear hearing loss. Journal of the Acoustical Society of America 106, 898-907.

Pepler, A., Munro, K., Lewis, K. & Kluk, K. (2014). Prevalence of Cochlear Dead Regions in New Referrals and Existing Adult Hearing Aid Users. Ear and Hearing 20(10), 1-11.

Schuknecht HF. Further observations on the pathology of presbycusis. Archives of Otolaryngology 1964;80:369—382

Vickers, D., Moore, B. & Baer, , T. (2001). Effects of low-pass filtering on the intelligibility of speech in quiet for people with and without dead regions at high frequencies. Journal of the Acoustical Society of America 110, 1164-1175.

Vinay and Moore, B. C. (2007). Speech recognition as a function of high-pass filter cutoff frequency for people with and without low-frequency cochlear dead regions. Journal of the Acoustical Society of America 122(1), 542-53.

Vinay, Baer, T. and Moore, B. C. (2008). Speech recognition in noise as a function of high pass-filter cutoff frequency for people with and without low-frequency cochlear dead regions. Journal of the Acoustical Society of America 123(2), 606-9.

Should you prescribe digital noise reduction to children?

Pittman, A. (2011). Age-related benefits of digital noise reduction for short term word learning in children with hearing loss. Journal of Speech, Language and Hearing Research 54, 1448-1463.

This editorial discusses the clinical implications of an independent research study and does not represent the opinions of the original authors.

A child’s ability to learn new words has important implications for language acquisition, mental and social development as well as academic achievement.  How easily a child acquires new vocabulary words can be affected by numerous factors, including age, working memory and current vocabulary (Alt, 2010). Hearing loss is known to adversely affect children’s ability to learn new words and the more severe the loss, the more significant the effect on word learning (Pittman, et al., 2005; Blamey et al., 2001). The effect of hearing loss on word learning may be related to a decreased ability to encode the degraded stimuli into working memory. Indeed, in a study with normal-hearing and hearing-impaired children, Pittman found that word stimuli that were modified with narrowed bandwidths were harder for children to learn (Pittman, 2008). Similar results indicating that degraded perception adversely affects children’s phonological processing have been reported elsewhere (Briscoe, et al., 2001).

In many everyday listening situations, speech must be perceived in the presence of noise or other competing sounds. Noise can degrade the speech information, making words more difficult to encode into working memory and identify correctly. Individuals with hearing loss are more adversely affected by the presence of background noise (Kochkin, 2002; McCoy et al., 2005; Picou et al., 2013), which is of particular concern when the effects of noise on word learning are considered. Hearing aids can at least partially mitigate effects of background noise with the use advanced signal processing like directional microphones and digital noise reduction (DNR). However, little evidence exists to support beneficial effects of DNR on word learning. Pittman suggests that there is reason for concern as DNR could impose negative effects on word learning because of reductions in overall amplification. Additionally, the effect of DNR on connected speech, which offers semantic and syntactic context, may be very different than the effects on isolated word learning, so the everyday experience of hearing aid users could be different from laboratory results that measured perception of isolated words.

This study examined how DNR affects word learning in hearing-impaired children with hearing aids. The authors presented these hypotheses:

1)              Word learning would decrease in noise for children with normal hearing and those with hearing loss.

2)              Word learning rates would slow in noise, due to the reduction in overall amplification imposed by DNR.

Forty-one children with normal hearing and 26 participants with mild-to-moderate hearing loss participated in the study. The treatment groups were comprised of two age sub-groups: a younger group of children from age 8-10 and a slightly older group of children from age 11-12. The children with hearing loss had been diagnosed at an average age of approximately 3 years and all but one wore personal hearing aids. Participants with hearing loss were fitted with BTE hearing aids programmed to DSL v5.0 targets, verified with real-ear measures and set with two programs. In Program 1, advanced signal processing features like noise reduction, impulse reduction, wind noise reduction and feedback management were turned off. In Program 2, these features remained disabled except for noise reduction, which was set to maximum.

Word learning was tested using nonsense words, presented in three sets of five words each. All were two-syllable words and each list contained words with the same vowels in the first and last syllables. Stimuli were presented in sound field by a female talker at a level of 50dB SPL and SNR of 0dB. Children were seated at a small table about one meter away from the speaker. Nonsense words were presented on a computer screen, along with five pictures of nonsense objects categorized as toys, flowers or aliens. The children were asked to select the appropriate picture to go with the word and were given positive reinforcement for selecting the correct picture. No reinforcement was provided for selecting the wrong picture. Children therefore learned the new words via a process of trial and error.

The first goal of the study was to examine the impact on noise on children’s word learning ability. Statistical analyses indicated that NH participants learned words faster than the HL participants did, older children learned faster than younger children and learning in quiet was faster than learning in noise. The presence of noise resulted in further decrements in performance for HL listeners, indicating that noise had a more deleterious effect on word learning in noise for participants with hearing loss than it did for normally hearing participants.

The second goal of the study was to determine if DNR affected word learning for children with hearing loss. When DNR trials were compared to quiet and noise trials, younger children performed the same in noise whether or not they were using DNR in their hearing aids. Performance for both noise conditions was significantly poorer than performance in quiet. In contrast, the performance of older participants improved with DNR, with DNR performance closely approximating performance in quiet.

When results from the word learning task were examined with reference to Peabody vocabulary scores, the results indicated that participants with hearing loss had lower vocabulary ages than the normally hearing participants. For the experimental tasks, normally hearing participants required fewer trials to reach 70% performance than the participants with hearing loss. Further analysis revealed that the age of identification, age of amplification and years of amplification use accounted for 85% of the variance, but follow-up tests revealed significant relations between word learning and age, but not word learning and hearing history. These results suggest that despite individual variability, word learning in noise was most related to the factors of age and vocabulary.

In sum, the results of this investigation suggest that DNR did not have an effect, positive or negative, on younger participants. It did improve performance for older children, however, regardless of their hearing history or years of amplification. The author points out that childrens’ speech perception in noise is known to improve with age (Elliott, 1979; Scollie, 2008) but the participants in this study demonstrated age effects only when DNR was used. It appears that the combination of DNR and greater vocabulary knowledge allowed the older listeners to demonstrate superior word learning.

There are many factors to consider when prescribing amplification characteristics for children. Word learning is a critical developmental process for children, with important implications for future social and academic accomplishments.  The documented beneficial effects of DNR on word learning in complex listening environments could be a strong motivator for selection in a pediatric hearing aid. In addition to potential word learning benefits, DNR could make amplification more comfortable in noisy conditions, thereby increasing the acceptance of hearing aids and expanding potential opportunities for communication and further word learning.

Some caution should be voiced in the selection of DNR for pediatric use. Many of these algorithms reduce frequency-specific hearing aid gains, presenting the opportunity to compromise audibility of some speech sounds when listening in noise. Prior to consideration of any DNR algorithm in pediatric populations, data should be presented that ensure the maintenance of speech audibility when that particular DNR algorithm is active and noise is presented at a levels typical of the child’s academic setting (see: Stelmachowicz et al., 2010).

The outcomes reported here provide general support for the use of DNR in school-age children. It must be clarified that the documented benefits do not suggest improved speech understanding, as this is not a function of the algorithm. Rather, the documented improvements in word learning most likely arise from the fact that noise in the absence of speech was reduced in level, reducing the effort required to listen to the individual words as they were presented.

For additional information on the prescription of hearing aid signal processing features in pediatric populations, please reference the 2013 Pedatric Amplification Guidelines, published by the American Academy of Audiology: http://audiology.org/resources/documentlibrary/Documents/PediatricAmplificationGuidelines.pdf

 

References

Alt, M. (2010). Phonological working memory impairments in children with specific language impairment: Where does the problem lie? Journal of Communication Disorders 44, 173-185.

Bentler, R., Wu, Y., Kettel, J. & Hurtig, R. (2008). Digital noise reduction: Outcomes from laboratory and field studies. International Journal of Audiology 47, 447-460.

Blamey, P., Sarant, J., Paatsch, L., Barry, J., Bow, C., Wales, R. & Rattigan, K. (2001). Relationships among speech perception, production, language, hearing loss and age in children with impaired hearing. Journal of Speech, Language and Hearing Research 44, 264-285.

Briscoe, J., Bishop, D. & Norbury, C. (2001). Phonological processing, language and literacy: a comparison of children with mild-to-moderate sensorineural hearing loss and those with specific language impairment. Journal of Child Psychology and Psychiatry and Allied Disciplines 42, 329-340.

Dunn, L. & Dunn, L. (2006). Peabody Picture Vocabulary Test – III. Circle Pines, MN:AGS.

Kochkin, S. (2002). MarkeTrak VI: 10-year customer satisfaction trends in the US hearing instrument market. The Hearing Review 9 (10), 14-25, 46.

McCoy, S.L., Tun, P.A. & Cox, L.C. (2005). Hearing loss and perceptual effort: downstream effects on older adults’ memory for speech. Quarterly Journal of Experimental Psychology A, 58, 22-33.

Picou, E.M., Ricketts, T.A. & Hornsby, B.W.Y. (2013). How hearing aids, background noise and visual cues influence objective listening effort. Ear and Hearing 34 (5).

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

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.

Pittman, A. (2011). Age-related benefits of digital noise reduction for short term word learning in children with hearing loss. Journal of Speech, Language and Hearing Research 54, 1448-1463.

Ng, E., Rudner, M., Lunner, T., Syskind Pedersen, M. & Rönnberg, J. (2013).  Effects of noise and working memory capacity on memory processing of speech for hearing aid users. International Journal of Audiology, Early Online: 1–9

Ricketts, T. & Hornsby, B. (2005). Sound quality measures for speech in noise through a commercial hearing aid implementing digital noise reduction. Journal of the American Academy of Audiology 16, 270-277.

Sarampalis, A., Kalluri, S. & Edwards, B. (2009). Objective measures of listening effort: effects of background noise and noise reduction. Journal of Speech Language and Hearing Research 52, 1230-1240.

Stelmachowicz, P., Lewis, D., Hoover, B., Nishi, K., McCreery, R. & Woods, W. (2010). Effects of digital noise reduction on speech perception for children with hearing loss. Ear and Hearing 31, 245-355.

The Top 5 Hearing Aid Research Articles from 2013!

1) The Clinical Practice Guidelines in Pediatric Amplification

After a 10-year wait, the guidelines for prescription of hearing aids to children were updated in 2013—making them the most modern of any peer-reviewed guidelines. There is little doubt that these recommendations will impact future publication and fitting protocols at clinical sites around the world. The guidelines are freely available at the link below.

American Academy of Audiology. (2013). Clinical Practice Guidelines Pediatric Amplification. Reston, VA: Ching, T., Galster, J., Grimes, A., Johnson, C., Lewis, D., McCreery, R…Yoshinago-Itano, C.

http://buff.ly/18TNGsz

2) Placebo effects in hearing aid trials are reliable

This article echoes publications from the early 2000’s (e.g., Bentler et al., 2003) that reported on blinded comparisons of analog and digital hearing aids. In those early studies, participants showed clear bias when primed to believe that option ‘A’ was a higher technology than option ‘B’. That early work was more focused on comparing technologies than this insightful report on placebo effects. Dawes and colleagues share an important reminder that placebo is real and should be accounted for in experimental design, whenever possible.

Dawes, P., Hopkins, R., & Munro, K. (2013). Placebo effects in hearing aid trials are reliable. International Journal of Audiology, 52(7), 472-477.

http://buff.ly/JF7DHM

3) Effects of hearing aid use on listening effort and mental fatigue

In the last few years, a number of research audiologists and hearing scientists have worked to document relationships between cognitive capacity, listening effort, and hearing aid use. An undertone of these efforts has been the assumption that a person with hearing loss will be less fatigued when listening with hearing aids. This article is one of the first published attempts at clearly documenting this fatiguing effect.

Hornsby, B.W. (2013). Effects of hearing aid use on listening effort and mental fatigue associated with sustained speech processing demands. Ear & Hearing, 34(5), 523-534.

http://buff.ly/JF7vrH

4) Characteristics of hearing aid fittings in infants and young children

The recent publication of updated pediatric fitting guidelines leads one to wonder how well fundamental aspects of these recommendations are being followed. This report from McCreery and colleagues is a clear indication that superior pediatric hearing care is uncommon and most often found in large pediatric medical centers. They also reinforce the consideration that consistent care from a single center may result in the most prescriptively appropriate hearing aid fitting.

McCreery, R., Bentler, R., & Roush, P. (2013). Characteristics of hearing aid fittings in infants and young children. Ear & Hearing, 34(6), 701-710.

http://buff.ly/18TNnhp

5) The Style Preference Survey (SPS): a report on psychometric properties and a cross-validation experiment

Closing out the Top 5: this article warrants high regard for rigor in design and quality of reporting. The authors delivered an article that will educate future researchers on the development and validation of questionnaires. Beyond this utility, the results are some of the first to identify the dimensions of preference that underlie the well-established bias toward preference of open-canal hearing aids.

Smith, S., Ricketts, T., McArdle, R., Chisolm, T., Alexander, G., & Bratt, G. (2013). Style preference survey: a report on the psychometric properties and a cross-validation experiement. Journal of the American Academy of Audiology, 24(2), 89-104.

http://buff.ly/JF740H

Patients with higher cognitive function may benefit more from hearing aid features

Ng, E.H.N., Rudner, M., Lunner, T., Pedersen, M.S., & Ronnberg, J. (2013). Effects of noise and working memory capacity on memory processing of speech for hearing-aid users. International Journal of Audiology, Early Online, 1-9.

This editorial discusses the clinical implications of an independent research study and does not represent the opinions of the original authors.

Research reports as well as clinical observations indicate that competing noise increases the cognitive demands of listening, an effect that is especially impactful for individuals with hearing loss (McCoy et al., 2005; Picou et al., 2013; Rudner et al., 2011).  Listening effort is a cognitive dimension of listening that is thought to represent the allocation of cognitive resources needed for speech recognition (Hick & Tharpe, 2002). Working memory, is a further dimension of cognition that involves the simultaneous processing and storage of information; its effect on speech processing may vary depending on the listening conditions (Rudner et al., 2011).

The concept of effortful listening can be characterized with the Ease of Language Understanding (ELU) model (Ronnberg, 2003; Ronnberg et al., 2008). In quiet conditions when the speech is audible and clear, the speech input is intact and is automatically and easily matched to stored representations in the lexicon. When speech inputs are weak, distorted or obscured by noise, mismatches may occur and speech inputs may need to be compared to multiple stored representations to arrive at the most likely match. In these conditions, allocation of additional cognitive resources, is required. Efficient cognitive functioning and large working memory capacity allows more rapid and successful matches between speech inputs and stored representations. Several studies have indicated a relationship between cognitive ability and speech perception: Humes (2007) found that cognitive function was the best predictor of speech understanding in noise and Lunner (2003) reported that participants with better working memory capacity and verbal processing speed had better speech perception performance.

Following the ELU model, hearing aids may allow listeners to match inputs and stored representations more successfully, with less explicit processing. Noise reduction, as implemented in hearing aids, has been proposed as a technology that may ease effortful listening. In contrast, however, it has been suggested that hearing aid signal processing may introduce unwanted artifacts or alter the speech inputs so that more explicit processing is required to match them to stored images (Lunner et al., 2009). If this is the case, hearing aid users with good working memory may function better with amplification because their expanded working memory capacity allows more resources to be applied to the task of matching speech inputs to long-term memory stores.

Elaine Ng and her colleagues investigated the effect of noise and noise reduction on word recall and identification and examined whether individuals were affected by these variables differently based on their working memory capacity. The authors had several hypotheses:

1. Noise would adversely affect memory, with poorer memory performance for speech in noise than in quiet.

2. Memory performance in noise would be at least partially restored by the use of noise reduction.

3. The effect of noise reduction on memory would be greater for items in late list positions because participants were older and therefore likely to have slower memory encoding speeds.

4. Memory in competing speech would be worse than in stationary noise because of the stronger masking effect of competing speech.

5. Overall memory performance would be better for participants with higher working memory capacity in the presence of noise reduction. This effect should be more apparent for late list items presented with competing speech babble.

Twenty-six native Swedish-speaking individuals with moderate to moderately-severe, high-frequency sensorineural hearing loss participated in the authors’ study. Prior to commencement of the study, participants were tested to ensure that they had age-appropriate cognitive performance. A battery of tests was administered and results were comparable to previously reported performance for their age group (Ronnberg, 1990).

Two tests were administered to study participants. First, a reading span test evaluated working memory capacity.  Participants were presented with a total of 24 three-word sentences and sub-lists of 3, 4 and 5 sentences were presented in ascending order. Participants were asked to judge whether the sentences were sensible or nonsense. At the end of each sub-list of sentences, listeners were prompted to recall either the first or final words of each sentence, in the order in which they were presented. Tests were scored as the total number of items correctly recalled.

The second test was a sentence-final word identification and recall (SWIR) test, consisting of 140 everyday sentences from the Swedish Hearing In Noise Test (HINT; Hallgren et al, 2006). This test involved two different tasks. The first was an identification task in which participants were asked to report the final word of each sentence immediately after listening to it.  The second task was a free recall task; after reporting the final word of the eighth sentence of the list, they were asked to recall all the words that they had previously reported. Three of seven tested conditions included variations of noise reduction algorithms, ranging from one similar to those implemented in modern hearing aids to an ‘ideal’ noise reduction algorithm.

Prior to the main analyses of working memory and recall performance, two sets of groups were created based on reading span scores, using two different grouping methods. In the first set, two groups were created by splitting the group at the median score so that 13 individuals were in a high reading span group and the remaining 13 were in a low reading span group. In the second set, participants who scored in the mid-range on the reading span test were excluded from the analysis, creating High reading span and Low reading span groups of 10 participants each. There was no significant difference between groups based on age, pure tone average or word identification performance, in any of the noise conditions. Overall reading span scores for participants in this study were comparable to previously reported results (Lunner, 2003; Foo, 2007).

Also prior to the main analysis, the SWIR results were analyzed to compare noise reduction and ideal noise reduction conditions. There was no significant difference between noise reduction and ideal noise reduction conditions in the identification or free recall tasks, nor was there an interaction of noise reduction condition with reading span score. Therefore, only the noise reduction condition was considered in the subsequent analyses.

The relationship between reading span score (representing working memory capacity) and SWIR recall was examined for all the test conditions. Reading span score correlated with overall recall performance in all conditions but one. When recall was analyzed as a function of list position (beginning or final), reading span scores correlated significantly with beginning (primacy) positions in quiet and most noise conditions. There was no significant correlation between overall reading span scores and items in final (recency) position in any of the noise conditions.

There were significant main effects for noise, list position and reading span group. In other words, when noise reduction was implemented, the negative effects of noise were lessened. There was a recency effect, in that performance was better for late list positions than for early list positions. Overall, the high reading span groups scored better than the low reading span groups, for both median-split and mid-range exclusion groups. The high reading span groups showed improved recall with noise reduction, whereas the low reading span groups exhibited no change in performance with noise reduction versus quiet.  The use of four-talker babble had a negative effect on late list positions, but did not affect items in other positions, suggesting that four-talker babble disrupted working memory more than steady-state noise. These analyses supported hypotheses 1, 2, 3 and 5, indicating that noise adversely affects memory performance (1), that noise reduction and list position interact with this effect (2,3) especially for individuals with high working memory capacity (5).

The results also supported hypothesis 4, which suggested that competing speech babble would affect memory performance more than steady state noise. Recall performance was significantly better in the presence of steady-state noise than it was in 4-talker babble. Though there was no significant effect of noise reduction overall, high reading span participants once again outperformed low reading span participants with noise reduction.

In summary, the results of this study determined that noise had an adverse effect on recall, but that this effect was mildly mitigated by the use of noise reduction. Four-talker babble was more disruptive to recall performance than was steady-state noise. Recall performance was better for individuals with higher working memory capacity. These individuals also demonstrated more of a benefit from noise reduction than did those with lower working memory capacity.

Recall performance is better in quiet conditions than in noise because presumably fewer cognitive resources are required to encode the speech input (Murphy, et al., 2000). Ng and her colleagues suggest that noise reduction helps to perceptually segregate speech from noise, allowing the speech input to be matched to stored lexical representations with less cognitive demand. So, noise reduction may at least partially reverse the negative effect of noise on working memory.

Competing speech babble is more likely to be cognitively demanding than steady-state noise (such as an air conditioner) because it contains meaningful information that is more distracting and harder to separate from the speech of interest (Sorqvist & Ronnberg, 2012). Not only is the speech signal of interest degraded by the presence of competing sound and therefore harder to encode, but additional cognitive resources are required to inhibit the unwanted or irrelevant linguistic information (Macken, 2009).  Because competing speech puts more demands on cognitive resources, it is more potentially disruptive than steady-state noise to perception of the speech signal of interest.

Unfortunately, much of the background noise encountered by hearing aid wearers is competing speech. The classic example of the cocktail party illustrates one of the most challenging situations for hearing-impaired individuals, in which they must try to attend to a proximal conversation while ignoring multiple conversations surrounding them. The results of this study suggest that noise reduction may be more useful in these situations for listeners with better working memory capacity; however, noise reduction should still be considered for all hearing aid users, with comprehensive follow-up care to make adjustments for individuals who are not functioning well in noisy conditions. Noise reduction may generally alleviate perceived effort or annoyance, allowing a listener to be more attentive to the speech signal of interest or to remain in a noisy situation that would otherwise be uncomfortable or aggravating.

More research is needed on the effects of noise, noise reduction and advanced signal processing on listening effort and memory in everyday situations. It is likely that performance is affected by numerous variables of the hearing aid, including compression characteristics, directionality, noise reduction, as well as the automatic implementation or adjustment of these features. These variables in turn combine with user-related characteristics such as age, degree of hearing loss, word recognition ability, cognitive capacity and more.

References

Foo, C., Rudner, M., & Ronnberg, J. (2007). Recognition of speech in noise with new hearing instrument compression release settings requires explicit cognitive storage and processing capacity. Journal of the American Academy of Audiology 18, 618-631.

Hallgren, M., Larsby, B. & Arlinger, S. (2006). A Swedish version of the hearing in noise test (HINT) for measurement of speech recognition. International Journal of Audiology 45, 227-237.

Hick, C. B., & Tharpe, A. M. (2002). Listening effort and fatigue in school-age children with and without hearing loss. Journal of Speech Language and Hearing Research 45, 573–584.

Humes, L. (2007). The contributions of audibility and cognitive factors to the benefit provided by amplified speech to older adults. Journal of the American Academy of Audiology 18, 590-603.

Lunner, T. (2003). Cognitive function in relation to hearing aid use. International Journal of Audiology 42, (Suppl. 1), S49-S58.

Lunner, T., Rudner, M. & Ronnberg, J. (2009). Cognition and hearing aids. Scandinavian Journal of Psychology 50, 395-403.

Macken, W.J., Phelps, F.G. & Jones, D.M. (2009). What causes auditory distraction? Psychonomic Bulletin and Review 16, 139-144.

McCoy, S.L., Tun, P.A. & Cox, L.C. (2005). Hearing loss and perceptual effort: downstream effects on older adults’ memory for speech. Quarterly Journal of Experimental Psychology A, 58, 22-33.

Picou, E.M., Ricketts, T.A. & Hornsby, B.W.Y. (2013). How hearing aids, background noise and visual cues influence objective listening effort. Ear and Hearing 34 (5).

Ronnberg, J. (2003). Cognition in the hearing impaired and deaf as a bridge between signal and dialogue: a framework and a model. International Journal of Audiology 42 (Suppl. 1), S68-S76.

Ronnberg, J., Rudner, M. & Foo, C. (2008). Cognition counts: A working memory system for ease of language understanding (ELU). International Journal of Audiology 47 (Suppl. 2), S99-S105.

Rudner, M., Ronnberg, J. & Lunner, T. (2011). Working memory supports listening in noise for persons with hearing impairment. Journal of the American Academy of Audiology 22, 156-167.

Sorqvist, P. & Ronnberg, J. (2012). Episodic long-term memory of spoken discourse masked by speech: What role for working memory capacity? Journal of Speech Language and Hearing Research 55, 210-218.

Do the benefits of tinnitus therapy increase with time?

Parazzini, M., Del Bo, L., Jastreboff, M., Tognola, G. & Ravazzani, P. (2011). Open ear hearing aids in tinnitus therapy: An efficacy comparison with sound generators. International Journal of Audiology, 50(8), 548-553.

This editorial discusses the clinical implications of an independent research study and does not represent the opinions of the original authors.

Tinnitus management can include a variety of treatment approaches but the most effective usually include a combination of counseling and sound therapy (Jastreboff, 1990; Jastreboff & Hazell, 2004). For many individuals with hearing loss and tinnitus, hearing aids may be the only tinnitus treatment they participate in. Specific treatment recommendations vary depending on a number of patient characteristics, such as degree of hearing loss and severity of the tinnitus disturbance.

Tinnitus Retraining Therapy (TRT; Jastreboff, 1995; Henry et al., 2002, 2003; Jastreboff & Jastreboff, 2006) is a widely known therapeutic approach using counseling and sound therapy, based on the neurophysiological model of tinnitus, that stresses the importance of helping individuals understand their condition, reducing awareness and attention to the tinnitus, providing or restoring appropriate auditory input and eventually training the auditory system to habituate to the tinnitus. Jastreboff & Hazell (2004) have proposed a classification system in which patients are assigned to one of five categories: 0 = mild or recent tinnitus, 1 = normal hearing and severe tinnitus, 2 = significant hearing loss, 3 = hyperacusis and 4 = prolonged worsening of tinnitus or hyperacusis following sound exposure. A patient’s classification on this scale can guide treatment recommendations thereafter. Counseling educates patients about their hearing loss and tinnitus, helping them cope with the stress and annoyance of tinnitus in their everyday lives. Sound therapy treatment aims to help patients habituate to their tinnitus, employing ear-level sound generators for individuals without hearing loss (category 1; described above) whereas hearing aids are recommended for tinnitus sufferers with significant hearing loss (category 2).

Individuals who fall into the borderline area between categories 1 and 2 could theoretically be treated with either sound generators or hearing aids. Presently, there is little evidence to suggest that one of these approaches is superior to the other. Therefore, the purpose of Parazzini et al.’s study was to compare the efficacy of sound therapy treatments with sound generators versus open-fit hearing aids for tinnitus patients whose characteristics fall between categories 1 and 2.

91 participants completed the study. All participants met the requirements for tinnitus categorization between Jastreboff categories 1 and 2, with pure tone thresholds equal to or less than 25dB HL at 2kHz and greater than or equal to 25dB at frequencies higher than 2kHz. None of the participants had used hearing aids or been treated with tinnitus retraining therapy prior to the study. Participants were randomly assigned to one of two treatment groups: those fitted with small, ear-level sound generators (SG group) and those fitted with binaural open fit hearing aids (HA group). All participants used the devices for at least 8 hours per day. Participants completed the Tinnitus Handicap Inventory (THI; Newman et al., 1996) at each of four appointments scheduled at three-month intervals over a year. Structured interviews were completed at each visit. During these interviews the following variables were examined: the effect of tinnitus on life, tinnitus loudness and tinnitus annoyance.

Analysis revealed that participants showed a marked reduction in scores over time, beginning at the first session three months after initiation of therapy and continuing progressively over subsequent measurements every three months up to the last visit at 12 months.  Results with ear-level sound generators and those with hearing aids were essentially identical. All three variables decreased by approximately 50% from the initial assessment to the final session at 12 months. The mean THI score decreased 52% from 57.9 to 27.9, the effect of tinnitus on life decreased 51% from 6.5 to 3.2, and tinnitus loudness ratings decreased from 7 to 3.6, a reduction of 48%. The common clinical criteria for significant improvement on the THI is 20 points (Newman et al., 1998) and 62% of the participants in the current study reached this goal by 6 months and 74% reached it by 12 months. Applying a criterion of 40% improvement to reflect a reduction in tinnitus disturbance—as proposed by P.J. Jastreboff—51% of the subjects achieved the goal by 6 months and 72% reached it by 12 months.

For all recorded variables, the time of treatment was always statistically significant, indicating that subjects were improving steadily over time. There was never a significant difference based on the type of device, indicating that sound generators and open-fit hearing aids were equally successful at alleviating tinnitus symptoms and reactions, at least for the subjects in this population, whose characteristics fell between categories 1 and 2 in Jastreboff & Hazell’s classification system.

Parazzini and colleagues evaluated tinnitus sufferers with mild high frequency hearing loss and measured their responses for up to 12 months. Though there was no evidence of plateaus in the data, it remains unknown whether improvements would continue if treatment were to continue beyond this point. Longer term studies would be valuable to determine at what point improvements plateau and if longer measurement periods yield differences between hearing aids and sound generator devices.

The instruments used in Parazzini’s study were either sound generators or hearing aids; none of the devices had both features. Many hearing aids available today offer tinnitus masking stimuli along with traditional amplification features. A similar paradigm examining hearing aids as well as combination devices could offer practical insight into tinnitus treatment options with currently available hearing instrument product lines. Because a goal of tinnitus retraining therapy is to restore auditory inputs to reduce awareness of the tinnitus, hearing aids could have particular benefits over sound generators, because they stimulate the auditory system with meaningful environmental sounds which may more effective at drawing attention away from the tinnitus, in addition to masking the tinnitus with the amplified sound.

Open-fit, behind-the-ear hearing aids appear to be a good solution for tinnitus patients: the ear canal remains open and unoccluded, thereby reducing the likelihood of increased tinnitus awareness. Another consideration is whether receiver-in-canal (RIC) instruments would be an even better choice. RICs are equally as effective as traditional open-fit hearing aids at minimizing occlusion and offer the opportunity to provide a broader high frequency range and more stable high frequency gain than is available when sound is routed thin or standard thickness tubing (Alworth, et al., 2010). This opportunity to provide an extended high-frequency amplification would be expected to increase auditory input in the frequency range where tinnitus is often perceived. Therefore, RICs may more effectively mask the tinnitus via amplification of environmental sounds, reducing tinnitus awareness and potentially, tinnitus annoyance and stress.

Parazzini’s study offers strong support for the use of open-fit hearing aids with tinnitus patients. Advances in hearing aid technology, such as feedback management, automatic signal processing, and the availability of tinnitus masking stimuli may make modern hearing aids even better suited for this purpose. As mentioned earlier, many opportunities exist for research in the treatment of tinnitus with hearing aids: effects of hearing aid style, sound therapy parameters, treatment and counseling strategies, and duration of treatment all remain white space for future researchers.

References

Alworth, L.N., Plyler, P.N., Bertges-Reber, M. & Johnstone, P.M. (2010). Microphone, performance and subjective measures with open canal hearing instruments. Journal of the American Academy of Audiology 21(4), 249-266.

Del Bo, L. & Ambrosetti, U. (2007). Hearing aids for the treatment of tinnitus. Progress in Brain Research 166, 341-345.

Henry J.A., Jastreboff M.M., Jastreboff P.J., Schechter M.A. & Fausti S.A.(2002).  Assessment of patients for treatment with tinnitus retraining therapy. Journal of the American Academy of Audiology, 13, 523 – 44.

Henry J.A., Jastreboff M.M., Jastreboff P.J., Schechter M.A. & Fausti S.A. (2003). Guide to conducting tinnitus retraining therapy initial and follow-up interviews. Journal of Rehabilitation Research and Development 40, 157 – 177.

Jastreboff, P.J. (1990). Phantom auditory perception (tinnitus): Mechanisms of generation and perception. Neuroscience Research 8, 221-254.

Jastreboff, P.J. & Hazell, J.W.P. (2004). Tinnitus Retraining Therapy: Implementing the Neurophysiological Model. Cambridge University Press.

Jastreboff P.J. & Jastreboff M.M. 2006. Tinnitus retraining therapy: A different view on tinnitus. Otorhinolaryngology and Related Specialties 68, 23 – 29.

Newman, C.W., Jacobson, G.P. & Spitzer, J.B. (1996). Development of the Tinnitus Handicap Inventory. Archives of Otolaryngology Head Neck Surgery 122, 143-148.

Newman, C.W., Sandridge, S.A. & Jacobson, G.P. (1998). Psychometric adequacy of the Tinnitus Handicap Inventory (THI) for evaluating treatment outcome. Journal of the American Academy of Audiology 9, 153-160.

Parazzini, M., Del Bo, L., Jastreboff, M., Tognola, G. & Ravazzani, P. (2011). Open ear hearing aids in tinnitus therapy: An efficacy comparison with sound generators. International Journal of Audiology, 50(8), 548-553.

Hearing Aids Alone can be Adjusted to Help with Tinnitus Relief

Shekhawat, G.S., Searchfield, G.D., Kobayashi, K. & Stinear, C. (2013). Prescription of hearing aid output for tinnitus relief. International Journal of Audiology 2013, early online: 1-9.

This editorial discusses the clinical implications of an independent research study and does not represent the opinions of the original authors.

The American Tinnitus Association (ATA) reports that approximately 50 million people in the United States experience some degree of tinnitus.About one third of tinnitus sufferers consider it severe enough to seek medical attention. Fortunately only a small proportion of tinnitus sufferers experience symptoms that are debilitating enough that they feel they cannot function normally. But even if it does not cause debilitating symptoms, for many tinnitus still causes a number of disruptive effects such as sleep interference, difficulty concentrating, anxiety, frustration and depression  (Tyler & Baker, 1983; Stouffer & Tyler, 1990; Axelsson, 1992; Meikle 1992; Dobie, 2004).

Therapeutic treatments for tinnitus include the use of tinnitus maskers, tinnitus retraining therapy, biofeedback and counseling . Though these methods provide relief for many the tendency for tinnitus to co-occur with sensorineural hearing loss (Hoffman & Reed, 2004) leads the majority of individuals to attempt management of tinnitus with the use of hearing aids alone (Henry, et al., 2005; Kochkin & Tyler, 2008; Shekhawat et al., 2013).  There are a number of benefits that hearing aids may offer for individuals with tinnitus:  audiological counseling during the fitting process may provide the individual with a better understanding of hearing loss and tinnitus (Searchfield et al., 2010); hearing aids may reduce the stress related to struggling to hear and understand; amplification of environmental sound may reduce perceived loudness of tinnitus (Tyler, 2008).

Prescriptive hearing aid fitting procedures are designed to improve audibility and assist hearing loss rather than address tinnitus concerns. Yet the majority of studies show that hearing aids alone can be useful for tinnitus management (Shekhawat et al., 2013). The Better Hearing Institute reports that approximately 28% of hearing aid users achieve moderate to substantial tinnitus relief with hearing aid use (Tyler, 2008). Approximately 66% of these individuals said their hearing aids offered tinnitus relief most or all the time and 29% reported that their hearing aids relieved their tinnitus all the time. However, little is known about how hearing aids should be adjusted to optimize this apparent relief from tinnitus. In a study comparing DSL I/O v4.0 and NAL-NL1, Wise (2003) found that low compression kneepoints in the DSL formula reduced tinnitus awareness for 80% of subjects, but these settings also made environmental sounds more annoying. Conversely, they had higher word recognition scores with NAL-NL1 but did not receive equal tinnitus reduction. The proposed explanation for this was the increased low-intensity, low-frequency gain of the DSL I/O formula versus the increased high frequency emphasis of NAL-NL1. Based on these findings, the author suggested the use of separate programs for regular use and for tinnitus relief.

Shekhawat and his colleagues began to address the issue of prescriptive hearing aid fitting for tinnitus by studying how output characteristics should be tailored to meet the needs of hearing aid users with tinnitus.  Specifically, they examined how modifying the high frequency characteristics of the DSL v5 (Scollie et al., 2005) prescription would affect subjects’ short term tinnitus perception.  Speech files with variable high frequency cut-offs and gain settings were designed and presented to subjects in matched pairs to arrive at the most favorable configuration for tinnitus relief.

Twenty-five participants mild to moderate high-frequency sensorineural hearing loss were recruited for participation. None of the participants had used hearing aids before but all indicated interest in trying hearing aids to alleviate their tinnitus.  All subjects had experienced chronic, bothersome tinnitus for at least two years and the average perception of tinnitus loudness was 62.6 on a scale from 1-100, where 1 is very faint and 100 is very loud. Subjects had a mean Tinnitus Functional Index (TFI; Meikle et al., 2012) score of 39.30. Six participants reported unilateral tinnitus localized to the left side, 15 had bilateral tinnitus and 4 reported tinnitus that localized to the center of the head, which is likely to be present bilaterally though not necessarily symmetrical.  The majority (40%) of the subjects reported their tinnitus quality as tonal, whereas 28% described it as noise, 20% as crickets and 12% as a combination of sound qualities. Tinnitus pitch matching was conducted using pairs of tones in which subjects were repeatedly asked to indicate which of the tones more closely matched the pitch of their tinnitus. The average matched tinnitus pitch was 7.892kHz with a range from 800Hz to 14.5kHz. When asked to describe the pitch of their tinnitus, most subjects defined it as “very high pitched”, some said “high pitched” and some said “medium pitched”.

There were 13 speech files, based on sentences spoken by a female talker, with variable high frequency characteristics. There were three cut-off frequencies (2, 4 and 6kHz) and four high frequency gain settings (+6, +3, -3 and -6dB). Stimuli were presented via a master hearing aid with settings programmed to match DSL I/O v5.0 prescriptive targets for each subject’s hearing loss.  Pairs of sentences were presented in a round robin tournament procedure  and subjects were asked to choose which one interfered most with their tinnitus and made it less audible. A computer program tabulated the number of “wins” for each sentence and collapsed the information across subjects to determine a “winner”, or the sentence that was most effective at reducing tinnitus audibility.  Real-ear measures were used to compare DSL v5 prescribed settings with the characteristics of the winning sentence and outputs were recorded from 250Hz to 6000Hz.

The most preferred output for interfering with tinnitus perception was a 6dB reduction at 2kHz, which was chosen by 26.47% of the participants.  A 6dB reduction at 4kHz was preferred by 14.74% of the subjects, followed by a 3dB reduction at 2kHz, which was preferred by 11.76%.  There were no significant differences between the preferences for any of these settings.

They found that when tinnitus pitch was lower than 4kHz, the preferred setting had lower output than DSL v5 across the frequency range. The difference was small (1-3dB) and became smaller as tinnitus pitch increased. When tinnitus pitch was between 4-8kHz, subjects preferred slightly less output than DSL v5 for high frequencies and slightly more output for low frequencies, though these differences were minimal as well. When tinnitus pitch was higher than 8kHz, participants preferred output that was slightly greater than DSL v5 at three frequencies: 750Hz, 1kHz and 6kHz. From these results a trend emerged: as tinnitus pitch increased, preferred output became lower than DSL v5 though the differences were not statistically significant.

Few studies investigating the use of hearing aids for tinnitus management have considered the perceived pitch of the tinnitus or the prescriptive method of the hearing aids (Shekhawat et al., 2013). The results of this study suggest that DSL v5 could be an effective prescriptive formula for hearing aids used in a tinnitus treatment plan, though the pitch of the individual’s tinnitus might affect the optimal output settings. In general, they found that the higher the tinnitus pitch, the more the preferred output matched with DSL I.O v5.0 targets. This study agrees with an earlier report by Wise (2003) in which subjects preferred DSL v5 over NAL-NL1 for interfering with and reducing tinnitus. It is unknown how NAL-NL2 targets would fare in a similar comparison, though the NAL-NL2 formula may provide more tinnitus relief than its predecessor because it tends to prescribe slightly higher gain for low frequencies and lower compression ratios which could potentially provide more of a masking effect from environmental sounds. The NAL-NL2 formula should be studied as it pertains to tinnitus management, perhaps along with consideration of other factors including degree of loss, gender and prior experience with hearing aids, since these affect the targets prescribed by the updated formula (Keidser & Dillon, 2006; Keidser et al., 2008). The subjects in the present study had similar degrees of loss and all lacked prior experience with amplification; the NAL-NL2 formula takes these factors into consideration, prescribing slightly different gain based on degree of loss or for those who have used hearing aids before.

The authors recommend offering separate hearing aid programs for use when the listener desires tinnitus relief. Most fitting formulae are designed to optimize speech intelligibility and audibility, and based on previous reports, an individual might prefer one formula when speech understanding and communication is their top priority, and may prefer another, used with or without an added noise masker, when their tinnitus is bothering them.

They also propose that tinnitus pitch matching should be considered when programming hearing aids, though there is often quite a bit of variability in results and testing needs to be repeated several times to increase reliability.  Still, their study agrees with prior work in suggesting that the pitch of the tinnitus affects how likely hearing aids are to reduce it and whether output adjustments can impact how effective the hearing aids are to this end. Schaette (2010) found that individuals with tinnitus pitch lower than 6kHz showed more reduction of tinnitus with hearing aid use than did subjects whose pitch was higher than 6kHz. This makes sense because of the typical bandwidth of hearing aids, in which most gain is delivered below this frequency range. Not surprisingly, another study reported that hearing aids were most effective at reducing tinnitus when the pitch of the tinnitus was within the frequency response range of the hearing aids (McNeil et al., 2012).  Though incorporating tinnitus pitch matching into a clinical protocol might seem daunting or time consuming, it is probably possible to use an informal bracketing procedure, similar to one used for MCLs, to get an idea of the individual’s tinnitus pitch range. Testing can be repeated at subsequent visits to eventually arrive at a more reliable estimate.  If pitch matching measures are not possible, clinicians can question the patient about their perceived tinnitus pitch range and, with reference the current study, adjust outputs in the 2kHz to 4kHz range to determine if the individual experiences improvement in tinnitus relief.

Proposed are a series of considerations for fitting hearing instruments on tinnitus sufferers and for employing dedicated tinnitus programs:

- noise reduction should be disabled;

- fixed activation of omnidirectional microphones introduce more environmental noise;

- in contrast to the previous recommendation, full-time activation of directional microphones will increase the hearing aid noise floor;

- lower compression knee points increase amplification for softer sounds;

- expansion should be turned off to increase amplification of low-level background sound;

- efforts should be made to  minimize occlusion, which can emphasize the perception of tinnitus;

- ensuring physical comfort of the devices can minimize the user’s general awareness of their ears and the hearing aids, potentially reducing their attention to the tinnitus as well (Sheldrake & Jastreboff, 2004; Searchfield, 2006);

- user controls are important as they allow access to alternate hearing aid programs and sound therapy options.

Dr. Shekhawat and his colleagues also underscore the importance of counseling tinnitus sufferers who choose hearing aids. Clinicians need to ensure that these patients have realistic expectations about the potential benefits of hearing aids and that they know the devices will not cure their tinnitus. Follow-up care is especially important to determine if adjustments or further training is necessary to improve the performance of the aids for all of their intended purposes.

Currently, little is known about how to optimize hearing aid settings for tinnitus relief and there are no prescriptive recommendations targeted specifically for tinnitus sufferers. Shekhawat and his colleagues propose that the DSL v5 formula may be an appropriate starting point for these individuals, as their basic program and/or in an alternate program designated for use when their tinnitus is particularly bothersome.  Most importantly, however, are the observations that intentional manipulation of parameters common to most hearing aid fittings may increase likelihood of tinnitus relief with hearing aid use. Further investigation into the optimization of these fitting parameters may reveal a prescriptive combination that audiologists can leverage to benefit individuals with hearing loss who also seek relief from the stress and annoyance of tinnitus.

 

References

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