Standard Audiogram Research Articles

The impact of using the Ida “My Hearing Explained” tool on audiologists’ language and patient understanding of hearing test results: a comparison with standard audiogram explanations

Objective Explore the impact of Ida’s “My Hearing Explained” (MHE) tool on audiologists’ language and patients’ understanding/interpretation of hearing test results. Design Audiologists were video-recorded in two sequential conditions: 1) giving standard audiogram explanations to 13 patients and, 2) following discretionary self-training, giving explanations using the MHE tool (nine patients). Outcomes of interest were audiologists’ language complexity, use of jargon, and audiologist-patient interactivity. Semi-structured patient interviews, conducted 1-7 days after appointments, were analysed using inductive qualitative content analysis. Patient recall was verified. Study Sample Four audiologists from one United Kingdom audiology service, and 22 patients (mean age 63.5 yrs) participated. Results In comparison to standard audiogram explanations, audiologists’ language was simpler and audiologist-patient interactivity greater with the MHE tool. Interview data analysis revealed differences between explanation types within the themes of “Understanding” and “Interpretation.” 54% (standard audiogram) and 22% (MHE tool) of patients expressed a desire for takeaway information. 31% (standard audiogram) and 67% (MHE tool) of patients reported their explanation helped them relay their results to others. Four patients (one receiving the MHE tool) incorrectly recalled information, suggesting inadequate understanding in these cases. Conclusions The MHE tool has potential for improving the accessibility and comprehensibility of hearing test results.

In-situ hearing threshold estimation using Gaussian process classification

One in six Americans suffers from hearing loss. While treatment with amplification is possible for many, the acceptance rate of hearing aids is low. Poor device fitting is one of the reasons. The hearing aid fitting starts with a detailed hearing assessment by a trained audiologist in a sound-controlled environment, using standard equipment. The hearing aid is adjusted step-by-step, following well-described procedures based on the audiogram. However, for many patients in rural settings, considerable travel time to a hearing center discourages them from receiving a hearing test and treatment. We hypothesize that hearing assessment with the patient’s hearing aid can reliably substitute the hearing test in the clinic. Over-the-counter hearing aids could be programmed from a distance and fine-tuned by the hearing aid wearer. This study shows that a patient-controlled hearing assessment via a hearing aid in a non-clinical setting is not statistically different from an audiologist-controlled hearing assessment in a clinical setting. The differences in hearing obtained with our device and the Gaussian Process are within 3 dB of the standard audiogram. At 250 Hz, the sound delivery with the hearing aid used in this study added an additional reduction of sound level, which was not compensated.

Functional consequences of extended high frequency hearing impairment: Evidence from the speech, spatial, and qualities of hearing scale.

Hearing loss in the extended high frequencies, despite a normal audiogram, could affect speech-in-noise recognition. However, it is not known if extended high frequency (EHF) hearing loss is associated with everyday listening and communication deficits. The present study aimed to determine the functional effects of impaired EHF hearing among adults using the Speech, Spatial, and Qualities of Hearing Scale (SSQ). A secondary objective was to evaluate the relationship between objective (speech-in-noise recognition) and subjective (SSQ) measures of hearing function. Listeners with EHF hearing loss provided lower SSQ ratings compared with their EHF-normal counterparts. The lower ratings could not be attributed to the age or standard audiogram of the listeners. Ratings from more than 50% of EHF-impaired listeners were below the 2 SD cutoff point obtained from EHF-normal listeners. The mean speech recognition threshold was poorer for EHF-impaired listeners, and a poorer speech recognition threshold was associated with lower SSQ ratings, i.e., poorer self-reported hearing ability. For some listeners, EHF hearing loss could be the missing link between self-reported hearing difficulty in the presence of a normal audiogram. These findings provide evidence for the functional deficits associated with EHF hearing loss and invoke the need for future investigations into the management of EHF loss.

Pure tone audiometry as assessed by a commercially-available mobile phone application compared to formal audiometry

PurposeComparison of audiometric measurements of commercially available smartphone audiogram application thresholds as compared to gold standard audiometric evaluation. Materials and methodsA single-institution, original contribution. Ninety consecutive adult patients presenting to a tertiary care auditory clinic with auditory complaints were evaluated using standard audiometric testing and an application-based hearing test. Correlation between app results and standard audiogram for air conduction pure tone thresholds was evaluated. ResultsMimi™ (Berlin, Germany) results for audiometric thresholds were moderately correlated with standard audiogram (r = 0.51–0.68) depending on severity. The percentage of patients whose hearing loss severity on formal audiometry results were accurately reflected in the Mimi™ (app-based hearing test: ABHT)11ABHT: app-based hearing test. results ranged from 18.2 to 80 %. Among patients whose results were at the extremes of hearing performance, app and standard audiogram results were similar. ABHT yielded an overall sensitivity of 35.5 % and specificity of 97.1 % for normal hearing, and an overall sensitivity of 80 % and specificity of 96 % for severe hearing loss. ConclusionsResults from an audiometric smart phone application showed accurate categorization of hearing loss at the high and extremes as compared to standard audiometry. However, correlation of pure tone values was more variable and dependent on hearing level.

Impaired auditory neural performance, another dimension of hearing loss in type-2 diabetes mellitus

AimTo evaluate auditory performance in subjects with poorly controlled type-2 diabetes mellitus, using a simple test battery assessing sensitivity to pure tones and neuronal function. MethodsEnrolled subjects, aged between 23 and 79 years, reported several auditory dysfunctions. They were tested using pure-tone audiometry, otoacoustic emissions for cochlear-function evaluation, and measurement of middle-ear muscle-reflex thresholds in search of an auditory neuropathy. ResultsCompared to the standard established for an age-matched normative population, the distribution of averaged pure-tone thresholds in enrolled subjects shifted by about one standard deviation with respect to the normal distribution, in line with past reports of mild sensorineural hearing impairment in diabetes, even though many diabetic subjects fell well within the normative interval of audiometric thresholds. Otoacoustic emissions showed that pure-tone thresholds correctly predicted the status of cochlear sensory cells that, by amplifying sound, ensure normal hearing sensitivity. Whereas the observed hearing losses should not have affected the acoustic levels above which the protective middle-ear muscle reflex is triggered by intense sounds, this reflex was undetectable in around 40% enrolled subjects, a marker of auditory neuropathy. ConclusionAuditory-neural function should be evaluated to identify diabetic subjects whose hearing is impaired. Simple automatic tests are available for this purpose, for example middle-ear muscle reflex detection, which turns out to be more sensitive than the standard audiogram.

Satisfaction with hearing assessment feedback using the My Hearing Explained tool: client and audiologist perceptions

Objective To determine the perceived satisfaction and understanding of hearing assessment feedback, using the Ida My Hearing Explained Tool (IMHET), compared to the standard audiogram reported by adult clients and audiologists. Design This study is a mixed-method design comparing clients and audiologists’ perceptions through a single-blinded, randomised control trial and focus group discussions. After using either the audiogram or IMHET for feedback, clients and audiologists completed the adapted Patient Satisfaction Questionnaire (PSQ). Study Sample During client’s initial audiological consultations, audiologists provided hearing assessment feedback (Total = 51) using the IMHET or audiogram. Twenty-seven clients and seven audiologists participated in focus groups, and/or open-ended questions. Results Satisfaction was not significantly different (p > 0.05) between the IMHET (76.18; SD: 2.66) or audiogram (75.63; SD: 4.73) for the overall PSQ scores reported by clients and audiologists. Two shared main themes, understanding and satisfaction, were identified for both tools from the focus groups and open-ended questions. A third main theme, recommendations, was identified only for the IMHET. Conclusions The IMHET is a valuable resource for clients during hearing assessment feedback. Audiologists recommend that the audiogram be used as a supplement when using the IMHET to provide feedback.

When to Refer a Hearing-impaired Patient for a Cochlear Implant Evaluation.

To explore the predictive value of utilizing routine audiometry to best determine cochlear implant (CI) candidacy using AzBio sentences. A retrospective chart review was performed between 2011 and 2018 for 206 adult patients who underwent CI evaluation assessed with AzBio sentences. Better hearing ear word recognition score (WRS) using Northwestern University-6 word lists presented at decibel hearing level from a standard audiogram was used to determine when best to refer a patient for CI evaluation. Predicted AzBio scores from multivariate regression models were calculated and compared with the actual CI candidacy to assess accuracy of the regression models. Race, marital status, hearing aid type, better hearing ear WRS, and HL were all independently and significantly associated with AzBio testing in quiet on univariate analyses. Better hearing ear WRS and better hearing ear decibel hearing level predicted AzBio Quiet on multivariate regression analysis. For AzBio +10 dB signal-to-noise ratio (SNR), sex, and better hearing ear WRS each significantly predicted speech perception testing. Predicted CI candidacy was based on AzBio sentence testing of ≤60% for the ease of statistical analysis. Regression models for AzBio sentence testing in quiet and +10 dB SNR agreed with the actual testing most of the time (85.0 and 87.9%, respectively). A generalized linear model was built for both AzBio testing in quiet and +10 dB SNR. A WRS of <60% in the better hearing ear derived from a routine audiogram will identify 83.1% of CI candidates while appropriately excluding 63.8% of patients.

Dynamically Masked Audiograms With Machine Learning Audiometry.

When one ear of an individual can hear significantly better than the other ear, evaluating the worse ear with loud probe tones may require delivering masking noise to the better ear to prevent the probe tones from inadvertently being heard by the better ear. Current masking protocols are confusing, laborious, and time consuming. Adding a standardized masking protocol to an active machine learning audiogram procedure could potentially alleviate all of these drawbacks by dynamically adapting the masking as needed for each individual. The goal of this study is to determine the accuracy and efficiency of automated machine learning masking for obtaining true hearing thresholds. Dynamically masked automated audiograms were collected for 29 participants between the ages of 21 and 83 (mean 43, SD 20) with a wide range of hearing abilities. Normal-hearing listeners were given unmasked and masked machine learning audiogram tests. Listeners with hearing loss were given a standard audiogram test by an audiologist, with masking stimuli added as clinically determined, followed by a masked machine learning audiogram test. The hearing thresholds estimated for each pair of techniques were compared at standard audiogram frequencies (i.e., 0.25, 0.5, 1, 2, 4, 8 kHz). Masked and unmasked machine learning audiogram threshold estimates matched each other well in normal-hearing listeners, with a mean absolute difference between threshold estimates of 3.4 dB. Masked machine learning audiogram thresholds also matched well the thresholds determined by a conventional masking procedure, with a mean absolute difference between threshold estimates for listeners with low asymmetry and high asymmetry between the ears, respectively, of 4.9 and 2.6 dB. Notably, out of 6200 masked machine learning audiogram tone deliveries for this study, no instances of tones detected by the nontest ear were documented. The machine learning methods were also generally faster than the manual methods, and for some listeners, substantially so. Dynamically masked audiograms achieve accurate true threshold estimates and reduce test time compared with current clinical masking procedures. Dynamic masking is a compelling alternative to the methods currently used to evaluate individuals with highly asymmetric hearing, yet can also be used effectively and efficiently for anyone.

Screening for Hearing Impairment in Older Adults by Smartphone-Based Audiometry, Self-Perception, HHIE Screening Questionnaire, and Free-Field Voice Test: Comparative Evaluation of the Screening Accuracy With Standard Pure-Tone Audiometry.

BackgroundHearing impairment is the most frequent sensory deficit in humans, affecting more than 360 million people worldwide. In fact, hearing impairment is not merely a health problem, but it also has a great impact on the educational performance, economic income, and quality of life. Hearing impairment is therefore an important social concern.ObjectiveWe aimed to evaluate and compare the accuracy of self-perception, Hearing Handicap Inventory for the Elderly-Screening (HHIE-S) questionnaire, free-field voice test, and smartphone-based audiometry as tests for screening moderate hearing impairment in older adults in China.MethodsIn this study, 41 patients were recruited through a single otology practice. All patients were older than 65 years. Patients with otorrhea and cognitive impairment were excluded. Moderate hearing impairment was defined as mean hearing thresholds at 500, 1000, 2000, and 4000 Hz >40 dB hearing loss (pure-tone average > 40 dB hearing loss). All patients completed 5 hearing tests, namely, the self-perception test, HHIE-S questionnaire test, free-field voice test, smartphone-based audiometry test, and standard pure-tone audiometry by the same audiologist. We compared the results of these tests to the standard audiogram in the better-hearing ear.ResultsThe sensitivity and the specificity of the self-perception test were 0.58 (95% CI 0.29-0.84) and 0.34 (95% CI 0.19-0.54), respectively. The sensitivity and the specificity of the HHIE-S questionnaire test were 0.67 (95% CI 0.35-0.89) and 0.31 (95% CI 0.316-0.51), respectively. The sensitivity and the specificity of the free-field voice test were 0.83 (95% CI 0.51-0.97) and 0.41 (95% CI 0.24-0.61), respectively. The sensitivity and the specificity of the smartphone-based audiometry test were 0.92 (95% CI 0.60-0.99) and 0.76 (95% CI 0.56-0.89), respectively. Smartphone-based audiometry correctly diagnosed the presence of hearing loss with high sensitivity and high specificity.ConclusionsSmartphone-based audiometry may be a dependable screening test to rule out moderate hearing impairment in the older population.

Identifying three otopathologies in humans

ObjectivesHearing-in-noise (HIN) is a primary complaint of both the hearing impaired and the hearing aid user. Both auditory nerve (AN) function and outer hair cell (OHC) function are thought to contribute to HIN, but their relative contributions are still being elucidated. OHCs play a critical role in HIN by fine tuning the motion of the basilar membrane. Further, animal studies suggest that cochlear (auditory) synaptopathy, which is the loss of synaptic contact between hair cells and the AN, may be another cause of HIN difficulty. While there is evidence that cochlear synaptopathy occurs in animal models, there is debate as to whether cochlear synaptopathy is clinically significant in humans, which may be due to disparate methods of measuring noise exposure in humans and our high variability in susceptibility to noise damage. Rather than use self-reported noise exposure to define synaptopathic groups, this paper assumes that the general population exhibits a range of noise exposures and resulting otopathologies and defines cochlear synaptopathy “operationally” as low CAP amplitude accompanied by normal DPOAE levels in persons with low pure tone averages. The first question is whether the standard audiogram detects AN dysfunction and OHC dysfunction? The second question is whether HIN performance is primarily dependent on AN function, OHC function, or both functions? DesignAdult subjects have been recruited to participate in an ongoing study and variables such as age, self-reported gender, pure tone audiometry (0.25–20 kHz), subjective perception of HIN difficulty, Quick Speech-in Noise (QuickSIN) test, 45% time compressed word recognition (WR) in 10% reverberation and WR in the presence of ipsilateral speech-weighted noise have been collected. These variables were correlated with OHC function measured by distortion-product otoacoustic emission (DPOAE) signal to-noise-ratio (SNR), and AN function measured by compound action potential (CAP) peak amplitude and ratio to summating potential measured using electrocochleography. ResultsSynaptopathy, by this operational definition, may be present in as many as 30% of individuals with normal hearing. Persons hearing within normal limits may exhibit HIN difficulties, and persons with hearing within normal limits may exhibit two distinct types of otopathologies undetected by the standard audiogram (a.k.a. hidden hearing loss) namely operational cochlear synaptopathy and OHC dysfunction. AN untuning secondary to OHC dysfunction is a third otopathology that occurs in subjects with a Mild–Moderate sensorineural hearing loss (SNHL). Clinical norms for each of these otopathologies are presented. Finally, the data show that operational cochlear synaptopathy does not correlate with HIN dysfunction. Rather, HIN performance is primarily governed by OHC function, while AN untuning also plays a lesser but statistically significant role. ConclusionsThe results of this study suggest the following: (1) persons hearing within normal limits may exhibit HIN difficulties; (2) persons hearing within normal limits may exhibit undetected otopathologies, namely AN dysfunction and OHC dysfunction; (3) AN untuning secondary to OHC dysfunction occurs in subjects with Mild–Moderate SNHL; (4) HIN performance is primarily governed by OHC function rather than AN function.

The accuracy of standard audiometric hearing level thresholds in pediatric patients

ObjectivesStandard audiograms provide decibels Hearing Level (dB HL) thresholds, which are referenced to normative values specified in decibels Sound Pressure Level in an acoustic coupler. Due to variability in external ear acoustics, the actual sound levels reaching the eardrum can vary across individuals. The real-ear to coupler difference (RECD) is a frequency-specific measurement of the difference between sound levels measured at the eardrum and in a coupler. Here, we compare the standard audiogram dB HL levels to RECD corrected hearing thresholds (dB RECHL) in children. MethodsChildren who underwent standard audiometric and RECD testing were included. The dB RECHL was established and the differences between dB HL and dB RECHL (threshold error) was calculated. A threshold error >5 dB was considered significant. ResultsA total of 166 children were included (mean age 12 years). Overall, 14% had normal hearing, 52% had conductive hearing loss and 27% had sensorineural hearing loss. Hearing threshold levels were overestimated by the standard audiogram compared to dB RECHL, at all frequencies (250–6000 Hz). In the lower frequencies and at 6000 Hz, 33–59% of patients were overestimated, with a threshold error up to 25 dB. In the mid frequencies, 33% were overestimated with a similar threshold error. ConclusionStandard audiogram thresholds overestimated hearing levels in children which may have clinical implications. This problem can be addressed by correcting thresholds with RECD. More studies are needed to assess the effect of correcting thresholds on hearing outcomes in children.

Correlation between recovery time of extended high-frequency audiometry and duration of inflammation in patients with acute otitis media.

To explore the rule of extended high-frequency (EHF) audiometry recovery in patients with acute otitis media. From January 2016 to July 2019, patients with acute otitis media in the outpatient department of otology were studied. The diagnosis was made according to the otoscopy and acoustic impedance tests, and antibiotics and other treatment programs were given. The patients were followed up to compare the effects of different recovery time on extended high-frequency audiometry in patients with acute otitis media. 146 patients with acute otitis media (69 in the left ear and 77 in the right ear) were selected for observation and follow-up. The patients were divided into three groups according to the time from the onset to the disappearance of hyperacusis and earache symptoms: ≤ 5days group (26 patients, 17.8%), 6-10days group (74 patients, 50.7%), and > 10days group (46 patients, 31.5%). The threshold of EHF in the study group was significantly higher than that in the control group in the early stage. According to the study design for follow-up, we found that with the prolongation of the duration of acute otitis media, the extended high frequency of different groups had different changes. Our results show that the recovery time of EHF in patients with acute otitis media was later than that of the standard audiogram and was closely related to the course of the disease. This is of great significance for discovering the hidden hearing loss of the patients and taking the treatment plan as soon as possible.

Speech recognition with hearing aids for 10 standard audiograms

BackgroundImprovement of speech perception in quiet is an important goal of hearing aid provision. In practice, results are highly variable. The aim of this study was to investigate the relationship between type and extent of hearing loss (audiogram type), maximum word recognition score, and aided speech perception.Materials and methodsPure tone and speech audiometric data of 740 ears in 370 patients were reviewed. All subjects visited our hearing center for hearing aid evaluation between 2012 and 2017. The maximum word recognition score (WRSmax) and the monosyllabic speech recognition score with hearing aids, WRS65(HA) were analyzed for 10 different standard audiogram types.ResultsThe WRS65(HA) with hearing aids for different degrees of hearing loss is, within error boundaries, comparable to previous investigations and shows a difference of 10–20 percentage points to the WRSmax. This difference tends to be larger for flat and moderately sloping audiograms compared to steep-sloping audiograms. The ratio WRS65(HA)/WRSmax can be interpreted as an efficiency factor for hearing aid provision, since it relates speech recognition with hearing aids to the maximally achievable information carrying capacity of the hearing impaired.ConclusionThe expectation regarding hearing aid provision has to be adjusted according to maximum word recognition score, the derived quality measures, degree of hearing loss, and audiogram type.

Speech recognition with hearing aids for 10standard audiograms

Improvement of speech perception in quiet is an important goal of hearing aid provision. In practice, results are highly variable. The aim of this study was to investigate the relationship between type and extent of hearing loss (audiogram type), maximum word recognition score, and aided speech perception. Pure tone and speech audiometric data of 740ears in 370patients were reviewed. All subjects visited our hearing center for hearing aid evaluation between 2012 and 2017. The maximum word recognition score (WRSmax) and the monosyllabic speech recognition score with hearing aids, WRS65(HA) were analyzed for 10different standard audiogram types. The WRS65(HA) with hearing aids for different degrees of hearing loss is, within error boundaries, comparable to previous investigations and shows adifference of 10-20percentage points to the WRSmax. This difference tends to be larger for flat and moderately sloping audiograms compared to steep-sloping audiograms. The ratio WRS65(HA)/WRSmax can be interpreted as an efficiency factor for hearing aid provision, since it relates speech recognition with hearing aids to the maximally achievable information carrying capacity of the hearing impaired. The expectation regarding hearing aid provision has to be adjusted according to maximum word recognition score, the derived quality measures, degree of hearing loss, and audiogram type.

Online Machine Learning Audiometry.

A confluence of recent developments in cloud computing, real-time web audio and machine learning psychometric function estimation has made wide dissemination of sophisticated turn-key audiometric assessments possible. The authors have combined these capabilities into an online (i.e., web-based) pure-tone audiogram estimator intended to empower researchers and clinicians with advanced hearing tests without the need for custom programming or special hardware. The objective of this study was to assess the accuracy and reliability of this new online machine learning audiogram method relative to a commonly used hearing threshold estimation technique also implemented online for the first time in the same platform. The authors performed air conduction pure-tone audiometry on 21 participants between the ages of 19 and 79 years (mean 41, SD 21) exhibiting a wide range of hearing abilities. For each ear, two repetitions of online machine learning audiogram estimation and two repetitions of online modified Hughson-Westlake ascending-descending audiogram estimation were acquired by an audiologist using the online software tools. The estimated hearing thresholds of these two techniques were compared at standard audiogram frequencies (i.e., 0.25, 0.5, 1, 2, 4, 8 kHz). The two threshold estimation methods delivered very similar threshold estimates at standard audiogram frequencies. Specifically, the mean absolute difference between threshold estimates was 3.24 ± 5.15 dB. The mean absolute differences between repeated measurements of the online machine learning procedure and between repeated measurements of the Hughson-Westlake procedure were 2.85 ± 6.57 dB and 1.88 ± 3.56 dB, respectively. The machine learning method generated estimates of both threshold and spread (i.e., the inverse of psychometric slope) continuously across the entire frequency range tested from fewer samples on average than the modified Hughson-Westlake procedure required to estimate six discrete thresholds. Online machine learning audiogram estimation in its current form provides all the information of conventional threshold audiometry with similar accuracy and reliability in less time. More importantly, however, this method provides additional audiogram details not provided by other methods. This standardized platform can be readily extended to bone conduction, masking, spectrotemporal modulation, speech perception, etc., unifying audiometric testing into a single comprehensive procedure efficient enough to become part of the standard audiologic workup.

Standard Audiograms for Koreans Derived through Hierarchical Clustering Using Data from the Korean National Health and Nutrition Examination Survey 2009\u20132012

Assessments of standardized region/population-specific audiological characteristics are needed for provision of effective rehabilitative services through reducing costs associated with hearing aids. This study aims to propose a set of standard audiograms representing the Korean population that were derived by analyzing data from the 2009–2012 Korea National Health and Nutrition Examination Survey (KNHANES), a nationwide epidemiologic study conducted by Korean government organizations. Standard audiograms were derived by applying a hierarchical clustering method from recorded audiologic data that were obtained independently at 6 frequencies for each ear: 0.5, 1.0, 2.0, 3.0, 4.0, and 6.0 kHz (in dB HL). To derive the optimal number of clusters of the desired standard audiograms, cubic clustering criterion, pseudo-F-, and pseudo-t2-statistics were calculated. These analyses resulted in 29 clusters representing a standard audiogram of the South Korean population. Eighteen of the clusters represented normal hearing audiograms (73.11%), while 11 represented hearing-impaired (HI) standard audiograms (27.89%). Of the 11 HI audiograms, 7 were defined as flat-type (17.81%), while the remaining 4 were defined as sloping-type (9.08%). In conclusion, 29 audiograms representing standard audiograms for the Korean population have been derived using KNHANES data. Improved understanding of the characteristics of each cluster may be helpful for development of more personalized, fixed-setting hearing aids.

Association of Behavior With Noise-Induced Hearing Loss Among Attendees of an Outdoor Music Festival

To date, factors associated with noise-induced hearing loss at music festivals have not yet been analyzed in a single comprehensive data set. In addition, little is known about the hearing loss-associated behavior of music festival attendees. To assess which factors are associated with the occurrence of a temporary threshold shift (TTS) after music exposure and to investigate the behavior of music festival attendees. This prospective post hoc analysis gathered data from a randomized, single-blind clinical trial conducted on September 5, 2015, at an outdoor music festival in Amsterdam, the Netherlands. Adult volunteers with normal hearing were recruited via social media from August 26 through September 3, 2015. Intention to use earplugs was an exclusion criterion. Of 86 volunteers assessed, 51 were included. This post hoc analysis was performed from October 3, 2016, through February 27, 2017. Music festival visit for 4.5 hours. The primary outcome was a TTS on a standard audiogram for the frequencies 3.0- and 4.0-kHz. Multivariable linear regression was performed to determine which factors are associated with a TTS. A questionnaire on behavior, hearing, and tinnitus was distributed to the participants before and after the festival visit. A total of 51 participants were included (18 men [35%] and 33 women [65%]) with a mean (SD) age of 27 (6) years. Mean (SD) threshold change across 3.0 and 4.0 kHz was 5.4 (5.7) dB for the right ear and 4.0 (6.1) dB for the left ear. Earplug use (absolute difference in the left ear, -6.0 dB [95% CI, -8.7 to -3.2 dB]; in the right ear, -6.4 dB [95% CI, -8.8 to -4.1 dB]), quantity of alcohol use (absolute difference per unit in the left ear, 1.1 dB [95% CI, 0.5 to 1.7 dB]; in the right ear, 0.7 dB [95% CI, 0.1 to 1.4 dB]), drug use (absolute difference in the right ear, 6.0 dB [95% CI, 0.9 to 11.1 dB]), and male sex (absolute difference in the right ear, 4.1 dB [95% CI, 0.3 to 5.9 dB]) were independently associated with hearing loss, with earplug use being the most important factor. Unprotected participants reported significantly worse subjective hearing performance and tinnitus after the festival visit than did participants using earplugs (Cramer V, 0.62 [95% CI, 0.47-0.79] and 0.39 [95% CI, 0.16-0.62], respectively). In the earplug group, the perceived loudness (r = -0.72; 95% CI, -1.00 to -0.43) and appreciation (r = 0.53; 95% CI, 0.29 to 0.78) of music and speech perception (r = 0.21; 95% CI, 0.09 to 0.35) were correlated with the duration of earplug use. The present study identified nonuse of earplugs, use of alcohol and drugs, and male sex as associated with a TTS at an outdoor music festival. Physicians should consider these factors to raise awareness about the combined risk of attending music festivals without using earplugs while consuming alcohol and/or drugs. The intention to use earplugs was correlated with the loudness and appreciation of music with earplugs, which may advocate for the use of personalized earplugs. trialregister.nl Identifier: NTR5401.

Electroacoustic assessment of wireless remote microphone systems.

Wireless remote microphones (RMs) transmit the desired acoustic signal to the hearing aid (HA) and facilitate enhanced listening in challenging environments. Fitting and verification of RMs, and benchmarking the relative performance of different RM devices in varied acoustic environments are of significant interest to Audiologists and RM developers. This paper investigates the application of instrumental speech intelligibility and quality metrics for characterizing the RM performance in two acoustic environments with varying amounts of background noise and reverberation. In both environments, two head and torso simulators (HATS) were placed 2 m apart, where one HATS served as the talker and the other served as the listener. Four RM systems were interfaced separately with a HA programmed to match the prescriptive targets for the N4 standard audiogram and placed on the listener HATS. The HA output in varied acoustic conditions was recorded and analyzed offline through computational models predicting speech intelligibility and quality. Results showed performance differences among the four RMs in the presence of noise and/or reverberation, with one RM exhibiting significantly better performance. Clinical implications and applications of these results are discussed.

Application-Based Hearing Screening in the Elderly Population.

The effects of age-related hearing loss are severe. Early detection is essential for maximum benefit. However, most hearing-impaired adults delay obtaining treatment. Diagnostic hearing testing at an appropriate facility is impractical, and new methods for screening audiometry aim to provide easy access for patients and reliable outcomes. The purpose of this study was to examine the accuracy of application-based hearing screening in an elderly population. The uHear application was downloaded to an iPad. Application-based hearing screening was performed in a non-soundproofed quiet room, and subsequently all participants underwent full diagnostic audiometry in a soundproof booth. Sixty patients were recruited and completed both tests. Significant differences were observed between the hearing results obtained with the application and the standard audiogram at all frequencies and in both ears. Following subtraction of a constant factor of 25 dB from the application-based results in order to compensate for ambient noise, no significant differences in pure tone average were found between the 2 methods. The uHear application is inaccurate in assessing hearing thresholds for screening in the elderly. However, when site-specifically corrected, the uHear application may be used as a screening tool for hearing loss in an elderly population.

How can the audiogram be more useful?

The Canadian Hearing and Auditory Research Translation (CHART) group is a newly formed taskforce to develop collaborative research initiatives. Initial discussions centered on diagnostic improvements for middle ear disease, auditory neuropathy spectrum disorder, tinnitus and presbycusis. Central to these discussions was the widely held view that the standard audiogram and its interpretation is inadequate to for describing many forms of hearing problems that we now recognize. This letter is designed to create awareness and to seek feedback from hearing healthcare professionals on their experience regarding the adequacy (or otherwise) of the audiogram in its present form.