Effect of Hearing Rehabilitation Therapy Program in Hearing Aid Users: A Prospective Randomized Controlled Study

How to Improve Audiology Services: The Patient Perspective

Hearing aid outcomes with open- and closed-canal fittings

The 2014-2016 National Health Interview Survey found that 15.9 percent of U.S. adults reported having hearing loss.1 Self-reports invariably underestimate the true prevalence of hearing loss possibly because of the insidious onset of the most prevalent type of acquired hearing loss: presbyacusis.2 This is confirmed by a recent national audiometric test-based study of a North American population that identified hearing loss prevalence rates as high as 65 percent in adults aged 70 to 79 years old.3iStock/sanjeri, audiology, primary care, hearing aids.Hearing aids are effective4 and common treatment options for hearing loss. However, hearing aid use is low, with only 3.7 percent of U.S. adults with hearing loss reporting owning a hearing aid.5 The reasons for this are uncertain, though subjects have reported being less satisfied with hearing aids than with similar sensory assistive devices such as eyeglasses.6In a literature review, Knudsen, et al.,7 concluded that perceived hearing disability was the only factor that affected both hearing aid use and satisfaction—an important finding illustrating adult hearing loss as a chronic condition that is amenable to management within the chronic care model advocated by Bodenheimer, et al.8 This model highlights that support for self-management and/or delivery system design-focused interventions can yield improved hearing health outcomes, thereby offering an alternative avenue for intervention to the more traditional audiological focus on hearing aid gain, amplification, and fit. The effects of self-management support and delivery system design on hearing aid use were studied in the Cochrane review by Baker, et al.9 Among the 32 studies reviewed, only two studies looked at the effect of self-support management on hearing aid use; however, these were not suitable for meta-analysis. Also, the researchers didn't find any statistically significant evidence that intervention combinations in the self-management and system design domains affected hearing aid use, though they found a reduction in hearing handicap.9 In a systematic review of the literature on hearing aid use and satisfaction, Mousavei, et al.,10searched a combination of keywords in the PubMed, Medline, and Embase databases and included studies published from January 1990 to January 2015 that focused on interventions aimed at improving hearing aid satisfaction and use and determinants of hearing aid use and satisfaction. Peer-reviewed articles that reported quantitative outcomes on a minimum of 20 older adult subjects were included in the review. Twenty-four studies were judged suitable for further study by two independent investigators. The subjects’ perceived severity of hearing loss and expectations of hearing aid benefit were positively correlated with hearing aid use. No specific factors conclusively affected hearing aid satisfaction. Hearing aid use and satisfaction were not affected by the patient's age or sex. No evidence showed that counseling, provided as a delivery system design intervention, improved hearing aid use or satisfaction. STUDY PREVIEW Based on existing literature, a multicenter randomized control trial was undertaken to investigate if a delivery system design intervention that includes a visit to a physician (family doctor or otolaryngologist/head and neck surgeon) during the hearing aid fitting process alter a patient's reported satisfaction with hearing aids.11 The trial was approved by the University of British Columbia's Clinical Research Ethics Board. Study participants were recruited from five audiology clinics in the Vancouver metropolitan area. Participants were adults 55 years of age or older who had hearing aid fitting for a sensorineural hearing loss greater than 25 dB, averaged over pure-tone audiometric measures of four frequencies in one or both ears. They were randomized to undergo standard-of-care hearing aid fitting alone or standard-of-care hearing aid fitting and a visit to their family doctor or an otolaryngologist/head and neck surgeon. At the visit, the physician conducted a Client Oriented Scale of Improvement (COSI)12 interview to see if the patient's hearing had changed following the hearing aid fitting. Participants completed the validated Satisfaction with Amplification in Daily Life (SADL) questionnaire13 three to four months after their initial fitting. At the time of interval analysis of the trial data, 94 patients had been recruited, with 57 and 37 randomized to the control and physician intervention groups, respectively. Eight patients in the control and three in the physician group didn't report for follow-up. SADL questionnaires were pending on nine control and 10 physician intervention patients. Therefore, data of 40 control and 24 physician intervention group patients were analyzed. The two groups were similar in age (72.8 and 70.3 years); sex (50% and 44% male); and PTA (43.1 and 49.2 dBHL). No statistically significant inter-group difference was found in the global SADL scores at three to four months follow-up (5.3 and 5.4; students’ t-test, p = 0.6). A chronic care system design intervention consisting of a single physician visit did not significantly change the level of satisfaction with hearing aids in a group of older adult hearing aid users. This finding is not definitive since a minimum of 40 patients is required in each arm of the study to show a standardized difference of 0.625 (0.5/0.8) at a five percent significance level, with a power of 80 percent based on the sample size nomogram by Altman.14 The physician group data set analyzed includes 24 patients and is thus short of the minimum sample size. The COVID-19 pandemic restrictions have delayed the final data accrual. However, it is anticipated that the shortfall will be filled as the data from patients who have been recruited after the interval analysis become available. The definitive results will then be reported.

Childhood hearing loss is a significant risk factor for language and academic delays.1–5 At the same time, the current generation of children with hearing loss show enormous variability in outcomes, with some children with hearing loss performing at the level of children with normal hearing, while others fall significantly behind.5 There has been a notable interest in recent years to determine the locus of variability in outcomes in children with hearing loss, including children with mild-to-severe hearing loss (i.e., children who are hard of hearing) who wear hearing aids. Researchers have pinpointed various factors that account for individual differences in children who are hard of hearing, including the quality and quantity of hearing intervention (e.g., amount of hearing aid use, amount that the hearing aid adequately restores access to speech),3–6 as well as cognitive factors such as working memory and attention.7,8 However, a comprehensive understanding of how these factors interact is still in its infancy, and the neural mechanisms underlying these interactions is unknown.www.shutterstock.com, audiology, hearing impaired, neural dynamics.Figure 1: Differences in brain activity between children with and without hearing loss. There was an increase in activity in the rightfrontal and parietal cortices in children who are hard of hearing (CHH) relative to children with normal hearing (CNH). Activity inthese regions correlated with verbal intelligence across groups. Audiology, hearing impaired, neural dynamics.Figure 2: Impact of hearing aid use on neural activity. Increased hearing aid (HA) use, especially more than ~8.5 hours of use,was correlated with more typical patterns of brain activity serving working memory processing. Audiology, hearing impaired, neural dynamics.On the heels of recent work using electroencephalography (EEG) and functional magnetic resonance imaging in people with severe-to-profound hearing loss,9–12 our lab is taking a new approach to understanding the impact of auditory experience on cognitive development by quantifying the real-time neural dynamics underlying these language and cognitive processes using magnetoencephalography (MEG). MEG is a noninvasive neuroimaging technique that records the small magnetic fields that naturally emanate from active neuronal populations in real time while a participant performs a task. MEG has a good combination of spatial accuracy (4-5 mm) and temporal precision (1 ms), which allows us to investigate the complex neural dynamics underlying cognitive and language processes as they evolve. In other words, these data provide a quantitative measure of neural activity throughout the brain during each stage of a behavioral process. This tool holds significant promise in determining the brain mechanisms and cognitive subprocesses that underlie differences in behavioral performance between children with normal hearing (CNH) and children who are hard of hearing (CHH), as well as between individual CHH. CURRENT STUDIES We had two goals in the current studies.13,14 The first goal was to identify the impact of hearing loss on the neural dynamics underlying verbal working memory processing groupwise between CHH and CNH, and the second was to determine the impact of the amount of hearing aid use on individual variability in brain activity within the hard-of-hearing group only. We analyzed data from a total of 30 children ages 7-15 years old, including 14 children with mild-to-severe hearing loss (9 females) and 16 children with normal hearing (8 females), who underwent neuroimaging with MEG while they performed a letter-based version of the Sternberg working memory task, as well as neuropsychological testing. During the verbal working memory task, participants were initially presented visually with six consonants for 2.0s (encoding period). The letters disappeared for 3.0s (maintenance period), then a probe letter appeared (retrieval period). Participants were asked to respond with a button press whether the probe letter was one of the previous six letters. The two groups did not significantly differ in reaction time or accuracy on this task. Finally, participants completed the Weschler Abbreviated Scale of Intelligence (WASI-II). Scores from the WASI-II were used to determine each participant’s verbal intelligence, nonverbal intelligence, and overall IQ. Parents also filled out questionnaires regarding the child’s hearing aid use that included questions such as, “How many hours per day does your child wear their hearing aids during the school year Mon-Fri? What about Sat-Sun?” Finally, degree of hearing loss was calculated in the children who are hard of hearing using their most recent audiogram. We used the MEG data to create whole-brain images of encoding- and maintenance-related neural responses separately, then compared the images groupwise to probe whether children who are hard of hearing showed differences in the neural patterns underlying each phase of verbal working memory compared to their normal hearing peers.13 We found that children who are hard of hearing exhibited significant elevations in right frontal activity during encoding, as well as elevations in maintenance-related right parietal activity relative to children with normal hearing. For context, the right prefrontal cortex is homologous to one of the most important regions for encoding verbal stimuli into memory storage,15,16 while the right parietal cortex is critical for working memory maintenance.17 Thus, increases in activity in these regions in the hard-of-hearing group was likely compensatory, which enabled the children to perform the task as well as their normal hearing peers. Crucially, we also found that activity in these two regions significantly correlated with verbal intelligence across groups, suggesting a tight link between working memory-related neural activity and language ability, in line with previous work (Figure 1).7,13,18,19 Our second goal was to determine whether working memory--related neural activity was sensitive to amount of hearing aid use in the children who are hard of hearing only.14 To this end, we performed whole-brain correlations between hours of hearing aid use and encoding-related and maintenance-related brain images separately, controlling for degree of hearing loss. We found significant correlations between hearing aid use and bilateral occipital and right precentral encoding-related activity, as well as maintenance-related activity in the right frontal cortex, above and beyond any effects of degree of hearing loss. In all these regions, more hearing aid use was correlated with a “normalization” of neural activity. Specifically, occipital encoding-related activity is known to be important for effective working memory encoding, and greater hearing aid use was associated with an increase in occipital responses. On the contrary, precentral and right prefrontal responses are generally considered atypical or compensatory in these types of tasks, and increased hearing aid use was associated with a decrease in activity in these regions (Figure 2). Critically, the “break even” point in these data, or the amount of hearing aid use that was related to more typical neural patterns, was at least 8.5 hours per day.14 CLINICAL IMPLICATIONS These data provide striking evidence that children with mild-to-severe hearing loss exhibit compensatory alterations in brain physiology during the performance of cognitive tasks. More consistent hearing aid use was associated with normalized neural patterns in children who are hard of hearing. It is important to note that brain differences were found despite there being no differences in behavioral performance between groups. These tasks were performed in a controlled laboratory setting, so it is possible that real-life environments, where there are multiple cognitive demands or distractions, may lead to an exhaustion of these compensatory resources and eventual behavioral decrements in children who are hard of hearing. Expanding on this idea, variability in the neural patterns that serve language and cognitive processes, especially relative to the difficulty of a given task, may explain why some studies find behavioral differences between those with and without hearing loss, while others find no such differences. Even more remarkable is the relationship between hearing aid use and neural activity in children with hearing loss. We found significant relationships between the neural patterns serving each phase of working memory and hearing aid use, such that consistent hearing aid use was related to more prototypical neural dynamics. These data suggest that the amount of quality auditory experience has substantial effects on their underlying brain physiology, and that at least 8.5 hours of hearing aid use seems to be beneficial, at least from a neural perspective. This aligns well with previous work suggesting that at least 8-10 hours of hearing aid use relates to better behavioral outcomes in these children.5,8 More broadly, our studies provide preliminary evidence that neuroimaging may hold promise in uncovering the mechanisms underlying differences in language and cognitive development between children with and without hearing loss, and may help explain the variability in outcomes between individuals with hearing loss.

Consistency of hearing aid and remote microphone system use declines as school-age children with hearing loss age. One indicator of hearing aid use time is data logging, another is parent report. Recent data suggest that parents overestimate their children's hearing aid use time relative to data logging. The potential reasons for this disparity remain unclear. Because school-age children spend the majority of their day away from their parents and with their teachers, reports from teachers might serve as a valuable and additional tool for estimating hearing aid use time and management. This study expands previous research on factors influencing hearing aid use time in school-age children using data logging records. Discrepancies between data logging records and parent reports were explored using custom surveys designed for parents and teachers. Responses from parents and teachers were used to examine hearing aid use, remote microphone system use, and hearing aid management in school-age children. Thirteen children with mild-to-moderate hearing loss between the ages of 7 and 10 yr and their parents participated in this study. Teachers of ten of these children also participated. Parents and teachers of children completed written surveys about each child's hearing aid use, remote microphone system use, and hearing aid management skills. Data logs were read from hearing aids using manufacturer's software. Multiple linear regression analysis and an intraclass correlation coefficient were used to examine factors influencing hearing aid use time and parent agreement with data logs. Parent report of hearing aid use time was compared across various activities and school and nonschool days. Survey responses from parents and teachers were compared to explore areas requiring potential improvement in audiological counseling. Average daily hearing aid use time was ∼6 hr per day as recorded with data logging technology. Children exhibiting greater degrees of hearing loss and those with poorer vocabulary were more likely to use hearing aids consistently than children with less hearing loss and better vocabulary. Parents overestimated hearing aid use by ∼1 hr per day relative to data logging records. Parent-reported use of hearing aids varied across activities but not across school and nonschool days. Overall, parents and teachers showed excellent agreement on hearing aid and remote microphone system use during school instruction but poor agreement when asked about the child's ability to manage their hearing devices independently. Parental reports of hearing aid use in young school-age children are largely consistent with data logging records and with teacher reports of hearing aid use in the classroom. Audiologists might find teacher reports helpful in learning more about children's hearing aid management and remote microphone system use during their time at school. This supplementary information can serve as an additional counseling tool to facilitate discussion about remote microphone system use and hearing aid management in school-age children with hearing loss.

Dual sensory loss (DSL; concurrent vision and hearing loss) negatively affects quality of life. As speechreading is hampered, use of hearing aids (HAs) is important for older adults with DSL. However, due to vision loss, use of small and complex HAs is assumed to be difficult. An integrative DSL protocol that addresses rehabilitative care for older adults with DSL, including proper HA use, was implemented in low vision rehabilitation centers. The present study aims to evaluate the effectiveness of the DSL protocol among HA owners on HA outcomes (i.e., HA use, benefit, satisfaction with HAs, and hearing with HAs). In a randomized controlled trial, the DSL protocol was compared to a waiting list control group among clients (aged ≥50 years) of low vision rehabilitation centers with DSL. The International Outcome Inventory for Hearing Aids (IOI-HA) and the HA Fitting Questionnaire (HAFQ) were administered at baseline and 3 months follow-up. Participants (n = 128) were randomly allocated to either the intervention (n = 63) or control group (n = 65). Intention-to-treat analyses showed a near significant effect on IOI-HA Residual problems (effect size, 0.35; p = 0.063). Per-protocol analyses showed similar (nonsignificant) results on the main outcomes, and a ceiling effect was found on the HAFQ. Significant effects were found in subgroups of patients: among patients with low HAFQ scores (HAFQ-Use: effect size = 0.56, p = 0.046; HAFQ-Hearing with HAs: effect size = 0.64, p = 0.019), male participants (effect size = 0.80; p = 0.003), and those with moderate hearing loss (effect size = 0.72; p = 0.028), significantly better IOI-HA scores were found in the intervention group at 3 months follow-up. Although the per-protocol and subgroup analyses need to be interpreted with caution, DSL patients who experience HA difficulties could benefit from the DSL protocol by making better use of their HAs. The increasing prevalence and impact of DSL on a person's independence and social participation call for more awareness of concurrent sensory impairments in both low vision and audiology rehabilitation. Interdisciplinary training for rehabilitation professionals could be an important step, followed by integration of vision and hearing services using the DSL protocol.

Hearing Aid User Perspectives: Reasons and Recommendations for Prescription and Over-The-Counter Device Uptake

Objective. To investigate cortical auditory evoked potentials (CAEPs) in pediatric hearing aid (HA) users, with and without language impairment. Design. CAEPs were measured in 11 pediatric HA users (age: 8–12 years) with moderate bilateral sensorineural hearing loss (HL); participants were classified according to language ability. CAEPs were also measured for a control group of 11 age-matched, normal-hearing (NH) children. Results. HL children without language impairment exhibited normal CAEPs. HL children with language impairment exhibited atypical temporal CAEPs, characterized by the absence of N1c; frontocentral responses displayed normal age-related patterns. Conclusion. Results suggest that abnormal temporal brain function may underlie language impairment in pediatric HA users with moderate sensorineural HL.

Despite a high prevalence of age-related hearing loss in older people, there is an unexplained low level of hearing aid adoption and use. Further research is required to determine the reason because hearing aids can vastly improve the quality of life for those with hearing loss. The aim of this study was to explore factors associated with hearing aid adoption and use, and to determine whether these differed between groups with different hearing aid use behaviors. Individual face-to-face semistructured interviews. Three groups of older people with hearing loss in Northern Ireland were recruited: (1) regular hearing aid users (n = 12), (2) irregular hearing aid users (n = 10), and (3) hearing aid nonowners (n = 10). Qualitative thematic analysis, using principles of grounded theory, was used to code the data and extract emerging themes for each of the three groups to distinguish similarities and differences between the groups. One-way analysis of variance and χ² tests were used to determine the difference in continuous and categorical variables, respectively, between the three groups. Similar themes emerged across the three groups: the complexity of low hearing aid use and attitudes to hearing loss/hearing aid use. A third theme, inadequacy of audiology services, was identified in both groups using hearing aids. Older age people having more severe hearing loss and longer duration of hearing aid ownership were associated with greater hearing aid adoption and use. Similar themes emerged from qualitative analysis across groups of people with hearing loss. More information for those with hearing loss and those with hearing aids and scheduled follow-up appointments for those with hearing aids are essential to improve hearing aid adoption and use in older people. Further research should focus on the most suitable methods of distributing this information and how often follow-up appointments should take place to achieve optimal hearing aid adoption and use.

Audiology Convention Keynote Addresses

Considerations on Health Literacy and Hearing Aid Use

Hearing Aid Use in Nursing Homes, Part 2: Barriers to Effective Utilization of Hearing Aids

Do Hearing Aids Help Prevent Cognitive Decline?

Following a brief tutorial on the application of factor analysis to hearing aid outcome measures, three studies of hearing aid outcome measures in elderly adults are presented and analyzed. Two of the studies were completed at Indiana University (IU-1 and IU-2), and one was a collaborative multisite study by the Veterans Administration and the National Institute of Deafness and other Communication Disorders (NIDCD/VA). IU-1 measured hearing aid outcome in 173 elderly wearers of single-channel, linear, in-the-ear hearing aids with output-limiting compression, whereas IU-2 obtained the same extensive set of outcome measures from 53 elderly wearers of two-channel, wide-dynamic-range compression, in-the-canal hearing aids. In the NIDCD/VA study, 333 to 338 participants wore three single-channel circuits in succession, with each circuit housed within an in-the-ear shell. The three circuits included in that study and in this analysis were: (1) linear with peak clipping, (2) linear with output-limiting compression, and (3) single-channel, wide-dynamic-range compression. Evaluation of the many outcome measures completed in each study using principal components factor analysis revealed that from three (both IU studies) to five (NIDCD/VA study) principal components captured the individual differences in hearing aid outcome. This was independent of hearing aid type (in-the-ear or in-the-canal) and circuitry. Subsequent multiple regression analyses of individual differences in performance along each dimension of hearing aid outcome revealed that these individual differences could be accounted for reasonably well by various prefit variables for some dimensions of outcome, but not others. In general, measures of speech recognition performance were well accounted for by prefit measures, with the best predictors being hearing loss, cognitive performance, and age. Measures of hearing aid usage were less well accounted for by prefit measures, with the most accurate predictor of current hearing aid use being prior hearing aid use. The outcome dimension accounted for most poorly was that associated with hearing aid satisfaction, with subjective measures of aided sound quality being the best predictor of performance along this dimension of hearing aid outcome. Additional multicenter, large-scale studies are needed to develop more complete models of hearing aid outcome and to identify the variables that influence various aspects of hearing aid outcome. It is only through this additional research that it will be possible to optimize outcome for hearing aid wearers.

Data suggest that having high expectations about hearing aids results in better overall outcome. However, some have postulated that excessively high expectations will result in disappointment and thus poor outcome. It has been suggested that counseling patients with unrealistic expectations about hearing aids prior to fitting may be beneficial. Data, however, are mixed as to the effectiveness of such counseling, in terms of both changes in expectations and final outcome. The primary purpose of this study was to determine whether supplementing prefitting counseling with demonstration of real-world listening can (1) alter expectations of new hearing aid users and (2) increase satisfaction over verbal-only counseling. Secondary goals of the study were to examine (1) the relationship between prefitting expectations and postfitting outcome, and (2) the effect of hearing aid fine-tuning on hearing aid outcome. Sixty new hearing aid users were fitted binaurally with Beltone Oria behind-the-ear digital hearing aids. Forty participants received prefitting counseling and demonstration of listening situations with the Beltone AVE (Audio Verification Environment) system; 20 received prefitting counseling without a demonstration of listening situations. Hearing aid expectations were measured at initial contact and following prefitting counseling. Reported hearing aid outcome was measured after eight to ten weeks of hearing aid use. Sixty new hearing aid users aged between 55 and 81 years with symmetrical sensorineural hearing loss. Participants were randomly assigned to one of three experimental groups, between which the prefitting counseling and follow-up differed: Group 1 received prefitting counseling in combination with demonstration of listening situations. Additionally, if the participant had complaints about sound quality at the follow-up visit, the hearing aids were fine-tuned using the Beltone AVE system. Group 2 received prefitting counseling in combination with demonstration of listening situations with the Beltone AVE system, but no fine-tuning was provided at follow-up. Group 3 received prefitting hearing aid counseling that did not include demonstration of listening, and the hearing aids were not fine-tuned at the follow-up appointment. The results showed that prefitting hearing aid counseling had small but significant effects on expectations. The two forms of counseling did not differ in their effectiveness at changing expectations; however, anecdotally, we learned from many participants that that they enjoyed listening to the auditory demonstrations and that they found them to be an interesting listening exercise. The data also show that positive expectations result in more positive outcome and that hearing aid fine-tuning is beneficial to the user. We conclude that prefitting counseling can be advantageous to hearing aid outcome and recommend the addition of prefitting counseling to address expectations associated with quality of life and self-image. The data emphasize the need to address unrealistic expectations prior to fitting hearing aids cautiously, so as not to decrease expectations to the extent of discouraging and demotivating the patient. Data also show that positive expectations regarding the impact hearing aids will have on psychosocial well-being are important for successful hearing aid outcome.