Hearing Tests Based on Biologically Calibrated Mobile Devices: Comparison With Pure-Tone Audiometry

The multilingual digits-in-noise (DIN) test: development and evaluation

OBJECTIVE

To develop a methodologically uniform digits-in-noise (DIN) test in 17 different languages.

DESIGN

The DIN test was developed for Android devices as an extension to the open-access Hearing Test™ app, available on the Google Play store. It utilised professionally recorded female speech, speech-shaped noise, a digit scoring method and a variable step size. The test was adaptively optimised and evaluated as the results of tests taken online by users of the app became available.

STUDY SAMPLE

Optimisation using 35,534 ears, evaluation using 6012 ears.

RESULTS

Optimisation improved the slopes of the psychometric functions for all languages by an average of 6.8%/dB. Evaluation included calculation of normative speech reception thresholds (SRTs) and estimation of test-retest standard deviations. Normative values for SRTs ranged from -14.2 dB SNR (95% CI -14.3 to -14.0) for Chinese to -11.2 dB SNR (95% CI -11.3 to -11.1) for Japanese, with reliability estimates ranging from 0.48 dB (95% CI 0.36-0.64) for Portuguese to 0.91 dB (95% CI 0.73-1.21) for Romanian.

CONCLUSIONS

The optimisation of each language version was confirmed by the improvement in the slopes of the psychometric functions. The normative values obtained from the test evaluation were in agreement with literature data.

TRIAL REGISTRATION

Science Support Centre of Wroclaw Medical University BW-59/2020.

Prediction of Hearing Help Seeking to Design a Recommendation Module of an mHealth Hearing App: Intensive Longitudinal Study of Feature Importance Assessment

BACKGROUND

Mobile health (mHealth) solutions can improve the quality, accessibility, and equity of health services, fostering early rehabilitation. For individuals with hearing loss, mHealth apps might be designed to support the decision-making processes in auditory diagnostics and provide treatment recommendations to the user (eg, hearing aid need). For some individuals, such an mHealth app might be the first contact with a hearing diagnostic service and should motivate users with hearing loss to seek professional help in a targeted manner. However, personalizing treatment recommendations is only possible by knowing the individual's profile regarding the outcome of interest.

OBJECTIVE

This study aims to characterize individuals who are more or less prone to seeking professional help after the repeated use of an app-based hearing test. The goal was to derive relevant hearing-related traits and personality characteristics for personalized treatment recommendations for users of mHealth hearing solutions.

METHODS

In total, 185 (n=106, 57.3% female) nonaided older individuals (mean age 63.8, SD 6.6 y) with subjective hearing loss participated in a mobile study. We collected cross-sectional and longitudinal data on a comprehensive set of 83 hearing-related and psychological measures among those previously found to predict hearing help seeking. Readiness to seek help was assessed as the outcome variable at study end and after 2 months. Participants were classified into help seekers and nonseekers using several supervised machine learning algorithms (random forest, naïve Bayes, and support vector machine). The most relevant features for prediction were identified using feature importance analysis.

RESULTS

The algorithms correctly predicted action to seek help at study end in 65.9% (122/185) to 70.3% (130/185) of cases, reaching 74.8% (98/131) classification accuracy at follow-up. Among the most important features for classification beyond hearing performance were the perceived consequences of hearing loss in daily life, attitude toward hearing aids, motivation to seek help, physical health, sensory sensitivity personality trait, neuroticism, and income.

CONCLUSIONS

This study contributes to the identification of individual characteristics that predict help seeking in older individuals with self-reported hearing loss. Suggestions are made for their implementation in an individual-profiling algorithm and for deriving targeted recommendations in mHealth hearing apps.

Reliability of an Android Based Free Application for Assessment of Hearing Loss in Adults

Hearing loss is an important health care concern. Pure Tone Audiometry (PTA) is considered  Gold Standard for audiometric evaluations though, there exist a huge variance between the demand and the actual services available. As smartphones are mobile, applications are upgradable, results are reproducible, the mobile applications may offer a good screening tool, especially in remote areas. There are many smartphone-based hearing applications which are already in use. However, effectiveness of such applications needs to be validated. To evaluate the reliability of 'Hearing Test' a phone application against PTA for assessment of hearing thresholds in adults. We conducted a diagnostic study on a heterogenous group of 250 individuals irrespective of their hearing levels. The hearing thresholds for both ears were measured by PTA and phone app and then compared statistically. The agreement between the methods were statistically significant with respect to diagnosing hearing loss and the degree of hearing loss. Though, PTA remains Gold Standard for hearing evaluation but freely available,  highly reproducible & specific 'Hearing Test' application could be used as a screening tool in remote areas and may help bridging the gap between the requirement and availability of diagnostic audiometric services.

Humans need auditory experience to produce typical volitional nonverbal vocalizations

Human nonverbal vocalizations such as screams and cries often reflect their evolved functions. Although the universality of these putatively primordial vocal signals and their phylogenetic roots in animal calls suggest a strong reflexive foundation, many of the emotional vocalizations that we humans produce are under our voluntary control. This suggests that, like speech, volitional vocalizations may require auditory input to develop typically. Here, we acoustically analyzed hundreds of volitional vocalizations produced by profoundly deaf adults and typically-hearing controls. We show that deaf adults produce unconventional and homogenous vocalizations of aggression and pain that are unusually high-pitched, unarticulated, and with extremely few harsh-sounding nonlinear phenomena compared to controls. In contrast, fear vocalizations of deaf adults are relatively acoustically typical. In four lab experiments involving a range of perception tasks with 444 participants, listeners were less accurate in identifying the intended emotions of vocalizations produced by deaf vocalizers than by controls, perceived their vocalizations as less authentic, and reliably detected deafness. Vocalizations of congenitally deaf adults with zero auditory experience were most atypical, suggesting additive effects of auditory deprivation. Vocal learning in humans may thus be required not only for speech, but also to acquire the full repertoire of volitional non-linguistic vocalizations.

Self-assessment of bone conduction hearing threshold using mobile audiometry: comparison with pure tone audiometry

OBJECTIVE

The aim of the research was to evaluate the feasibility of measuring the bone conduction hearing threshold using self-administered mobile audiometry.

DESIGN

A single-centre, closed, cross-over trial was carried out on patients from the ENT Department. A mobile-based, self-administered, audiologist-assisted assessment of the bone conduction hearing threshold was carried out by means of the open-access, freeware app Hearing Test using two types of bone conduction headphones: professional B71 bone transducer and commercially available AfterShokz Openmove open-ear headphones.

STUDY SAMPLE

Seventy-seven ears.

RESULTS

A test-retest examination revealed the lowest standard deviation for open-ear headphones at 3.33 dB (95% CI 2.92-3.79). When compared with pure tone audiometry, the intraclass correlations of 0.95 (95% CI 0.94-0.96) and 0.90 (95% CI 0.88-0.92) were obtained for the bone transducer and for the open-ear headphones, indicating excellent and good reliability, respectively. However, the regression slope of 0.67 was found for the air-bone gap when using open ear headphones, which was significantly different from 1 (p < 0.001).

CONCLUSIONS

Open-ear headphones provide an alternative for estimating bone conduction once the air-bone gap has been adjusted by a factor of 1/0.6 7 ≅1.5. They demonstrate improved reproducibility over the bone transducer and are much easier to use with a mobile device. Trial Registration: Wroclaw Medical University, Science Support Centre, BW60/2020.

Artificial intelligence approaches for tinnitus diagnosis: leveraging high-frequency audiometry data for enhanced clinical predictions

This research investigates the application of machine learning to improve the diagnosis of tinnitus using high-frequency audiometry data. A Logistic Regression (LR) model was developed alongside an Artificial Neural Network (ANN) and various baseline classifiers to identify the most effective approach for classifying tinnitus presence. The methodology encompassed data preprocessing, feature extraction focused on point detection, and rigorous model evaluation through performance metrics including accuracy, Area Under the ROC Curve (AUC), precision, recall, and F1 scores. The main findings reveal that the LR model, supported by the ANN, significantly outperformed other machine learning models, achieving an accuracy of 94.06%, an AUC of 97.06%, and high precision and recall scores. These results demonstrate the efficacy of the LR model and ANN in accurately diagnosing tinnitus, surpassing traditional diagnostic methods that rely on subjective assessments. The implications of this research are substantial for clinical audiology, suggesting that machine learning, particularly advanced models like ANNs, can provide a more objective and quantifiable tool for tinnitus diagnosis, especially when utilizing high-frequency audiometry data not typically assessed in standard hearing tests. The study underscores the potential for machine learning to facilitate earlier and more accurate tinnitus detection, which could lead to improved patient outcomes. Future work should aim to expand the dataset diversity, explore a broader range of algorithms, and conduct clinical trials to validate the models' practical utility. The research highlights the transformative potential of machine learning, including the LR model and ANN, in audiology, paving the way for advancements in the diagnosis and treatment of tinnitus.

The Hearing Test App for Android Devices: Distinctive Features of Pure-Tone Audiometry Performed on Mobile Devices

The popularity of mobile devices, combined with advances in electronic design and internet technology, has enabled home-based hearing tests in recent years. The purpose of this article is to highlight the distinctive aspects of pure-tone audiometry performed on a mobile device by means of the Hearing Test app for Android devices. The first version of this app was released a decade ago, and since then the app has been systematically improved, which required addressing many issues common to the majority of mobile apps for hearing testing. The article discusses techniques for mobile device calibration, outlines the testing procedure and how it differs from traditional pure-tone audiometry, explores the potential for bone conduction testing, and provides considerations for interpreting mobile audiometry including test duration and background noise. The article concludes by detailing clinically relevant aspects requiring special attention during testing and interpretation of results which are of substantial value to the hundreds of thousands of active users of the Hearing Test app worldwide, as well as to users of other hearing test apps.

Mobile audiometry for hearing threshold assessment: A systematic review and meta-analysis

OBJECTIVES

Technological advancements in mobile audiometry (MA) have enabled hearing assessment using tablets and smartphones. This systematic review (PROSPERO ID: CRD42021274761) aimed to identify MA options available to health providers, assess their accuracy in measuring hearing thresholds, and explore factors that might influence their accuracy.

DESIGN AND SETTING

A systematic search of online databases including PubMed, Embase, Cochrane, Evidence Search and Dynamed was conducted on 13th December 2021, and repeated on 30th October 2022, using appropriate Medical Subject Headings (MeSH) terms. Eligible studies reported the use of MA to determine hearing thresholds and compared results to conventional pure-tone audiometry (CA). Studies investigating MA for hearing screening (i.e. reporting just pass/fail) were ineligible for inclusion. Two authors independently reviewed studies, extracted data, and assessed methodological quality and risk of bias using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool.

PARTICIPANTS

Adults and children, with and without diagnosis of hearing impairment.

MAIN OUTCOME MEASURES

A meta-analysis was performed to obtain the mean difference between thresholds measured using MA and CA in dB HL.

RESULTS

Searches returned 858 articles. After systematic review, 17 articles including 1032 participants were analysed. The most used software application was ShoeboxTM (6/17) followed by Hearing TestTM (3/17), then HearTestTM (2/17). Tablet computers were used in ten studies, smartphones in six, and a computer in one. The mean difference between MA and CA thresholds was 1.36 dB (95% CI, 0.07-2.66, p = 0.04). Significant differences between mobile audiometry (MA) and conventional audiometry (CA) thresholds were observed in thresholds measured at 500Hz, in children, when MA was conducted in a sound booth, and when MA was self-administered. However, these differences did not exceed the clinically significant threshold of 10 decibels (dB). Included studies exhibited high levels of heterogeneity, high risk of bias and low concerns about applicability.

CONCLUSIONS

MA compares favourably to CA in measuring hearing thresholds and has role in providing access to hearing assessment in situations where CA is not available or feasible. Future studies should prioritize the integration of pure-tone threshold assessment with additional tests, such as Speech Recognition and Digits-in-Noise, for a more rounded evaluation of hearing ability, assesses acceptability and feasibility, and the cost-effectiveness of MA in non-specialist settings.

A pilot study to validate AMTAS in a specialist outpatient clinic at a public restructured hospital in Singapore

Background

The prevalence of age-related hearing loss is expected to increase with the ageing population in Singapore resulting in increased demand for pure tone audiometry (PTA). One way of meeting the increased demand for PTA is the Automated Method of Testing Auditory Sensitivity (AMTAS). Nonetheless, before AMTAS may be implemented, it is important to validate its results by comparing them against those of conventional PTA for the diverse Singaporean population.

Methods

100 participants were recruited from the Otorhinolaryngology clinic at a public hospital. PTA was conducted for participants via the conventional method and AMTAS. The hearing thresholds obtained via the two methods were then compared. A feedback questionnaire on the use of AMTAS was also completed by all participants.

Results

Air and bone conduction threshold results from 80 participants were analysed. The absolute mean difference in air conduction thresholds obtained via the two methods ranged from 3.30 to 9.62 dB. The absolute mean difference in bone conduction thresholds obtained via the two methods ranged from 8.16 to 9.38 dB. Most participants indicated that the machine was easy to use. Other feedback collected indicated that the AMTAS testing environment was noisy and that testing was fast.

Conclusion

This study finds that despite differences in hearing thresholds obtained via AMTAS and manual PTA, these differences are within the acceptable 10 dB test-retest variation. Nonetheless, existing issues related to the AMTAS software and noise levels in the testing environment will need to be addressed before it can be used in the clinic.

Analytical methods for evaluating reliability and validity of mobile audiometry tools

Statistical approaches that could be used as standardized methodology for evaluating reliability and validity of data obtained using remote audiometry are proposed. Using data from the Nurses' Health Study II (n = 31), the approaches to evaluate the reliability and validity of hearing threshold measurements obtained by a self-administered iPhone-based hearing assessment application (Decibel Therapeutics, Inc., Boston, MA) compared with measurements obtained by clinical (soundbooth) audiometry are described. These approaches use mixed-effects models to account for multilevel correlations, intraclass correlation coefficients (ICCs) of single and averaged measurements, and regression techniques with the generalized estimating equations (GEEs) to account for between-ear correlations. Threshold measurements obtained using the iPhone application were moderately reliable. The reliability was improved substantially by averaging repeated measurements; good reliability was achieved by averaging three repeated measurements. In the linear regression analyses that assessed validity, the range of intercepts (2.3-8.4) and range of slopes (0.4-0.7) indicated that the measurements from the application were likely biased from those obtained by clinical audiometry. When evaluating alternative hearing assessment tools, it is recommended to assess reliability through mixed-effects models and use ICCs to determine the number of repeated assessments needed to achieve satisfactory reliability. When evaluating validity, GEE methods are recommended to estimate regression coefficients.

Online digital audiometry vs. conventional audiometry: a multi-centre comparative clinical study

OBJECTIVE

The primary objective of the current study was the validation of a cloud-centralized audiometry system for clinical practice.

DESIGN

A cross-sectional study design was used.

STUDY SAMPLE

A convenience sample of patients (>10 years old) booked for follow-up appointments were invited to participate. Participants completed both conventional and online digital audiometry in a standard sound treated clinic space during a single clinic visit; tests were completed in random order. Data for both ears were included. Patients were from one of three audiological practices.

RESULTS

A total of 41 participants completed both audiometric tests. Validation study results showed that the mean difference between the two audiometric test results remained within 5 dB HL for both air and bone conduction thresholds at all tested frequencies.

CONCLUSIONS

Online digital audiometry has been demonstrated as a clinically accurate method for hearing assessment.

Accuracy of smartphone-based hearing screening tests: a systematic review

PURPOSE

To verify the accuracy of smartphone apps to identify hearing loss.

RESEARCH STRATEGIES

A systematic review followed the PRISMA-DATA checklist. The search strategies were applied across four databases (Lilacs, PubMed, Scopus and Web of Science) and grey literature (Google Scholar, OpenGrey, and ProQuest Dissertations and Thesis).

SELECTION CRITERIA

The acronym PIRD was used in review. This included populations of any gender and all age groups. The Index test is the smartphone-based hearing screening test; the Reference test is the pure-tone audiometry, which is considered the gold reference for hearing diagnostics; the diagnosis was performed via validity data (sensitivity and specificity) to identify hearing loss and diagnostic studies.

DATA ANALYSIS

Two reviewers selected the studies in a two-step process. The risk of bias was assessed according to the criteria of the QUADAS-2.

RESULTS

Of 1395 articles, 104 articles were eligible for full-text reading and 17 were included. Only four met all criteria for methodological quality. All of the included studies were published in English between 2015 and 2020. The applications Digits-in noise Test (5 articles), uHear (4 articles), HearScreen (2 articles), hearTest (2 articles) and Hearing Test (2 articles) were the most studied. All this application showed sensitivity and specificity values between 75 and 100%. The other applications were EarScale, uHearing Test, Free field hearing (FFH) and Free Hearing Test.

CONCLUSION

uHear, Digit-in-Noise Test, HearTest and HearScreen have shown significant values of sensitivity and specificity and can be considered as the most accurate methods for screening of hearing impairment.

Digital Approaches to Automated and Machine Learning Assessments of Hearing: Scoping Review

BACKGROUND

Hearing loss affects 1 in 5 people worldwide and is estimated to affect 1 in 4 by 2050. Treatment relies on the accurate diagnosis of hearing loss; however, this first step is out of reach for >80% of those affected. Increasingly automated approaches are being developed for self-administered digital hearing assessments without the direct involvement of professionals.

OBJECTIVE

This study aims to provide an overview of digital approaches in automated and machine learning assessments of hearing using pure-tone audiometry and to focus on the aspects related to accuracy, reliability, and time efficiency. This review is an extension of a 2013 systematic review.

METHODS

A search across the electronic databases of PubMed, IEEE, and Web of Science was conducted to identify relevant reports from the peer-reviewed literature. Key information about each report's scope and details was collected to assess the commonalities among the approaches.

RESULTS

A total of 56 reports from 2012 to June 2021 were included. From this selection, 27 unique automated approaches were identified. Machine learning approaches require fewer trials than conventional threshold-seeking approaches, and personal digital devices make assessments more affordable and accessible. Validity can be enhanced using digital technologies for quality surveillance, including noise monitoring and detecting inconclusive results.

CONCLUSIONS

In the past 10 years, an increasing number of automated approaches have reported similar accuracy, reliability, and time efficiency as manual hearing assessments. New developments, including machine learning approaches, offer features, versatility, and cost-effectiveness beyond manual audiometry. Used within identified limitations, automated assessments using digital devices can support task-shifting, self-care, telehealth, and clinical care pathways.

Towards the Interpretation of Sound Measurements from Smartphones Collected with Mobile Crowdsensing in the Healthcare Domain: An Experiment with Android Devices

The ubiquity of mobile devices fosters the combined use of ecological momentary assessments (EMA) and mobile crowdsensing (MCS) in the field of healthcare. This combination not only allows researchers to collect ecologically valid data, but also to use smartphone sensors to capture the context in which these data are collected. The TrackYourTinnitus (TYT) platform uses EMA to track users' individual subjective tinnitus perception and MCS to capture an objective environmental sound level while the EMA questionnaire is filled in. However, the sound level data cannot be used directly among the different smartphones used by TYT users, since uncalibrated raw values are stored. This work describes an approach towards making these values comparable. In the described setting, the evaluation of sensor measurements from different smartphone users becomes increasingly prevalent. Therefore, the shown approach can be also considered as a more general solution as it not only shows how it helped to interpret TYT sound level data, but may also stimulate other researchers, especially those who need to interpret sensor data in a similar setting. Altogether, the approach will show that measuring sound levels with mobile devices is possible in healthcare scenarios, but there are many challenges to ensuring that the measured values are interpretable.

Construction and Evaluation of a High-Frequency Hearing Loss Screening Tool for Community Residents

Early screening and detection of individuals at high risk of high-frequency hearing loss and identification of risk factors are critical to reduce the prevalence at community level. However, unlike those for individuals facing occupational auditory hazards, a limited number of hearing loss screening models have been developed for community residents. Therefore, this study used lasso regression with 10-fold cross-validation for feature selection and model construction on 38 questionnaire-based variables of 4010 subjects and applied the model to training and testing cohorts to obtain a risk score. The model achieved an area under the curve (AUC) of 0.844 in the model validation stage and individuals’ risk scores were subsequently stratified into low-, medium-, and high-risk categories. A total of 92.79% (1094/1179) of subjects in the high-risk category were confirmed to have hearing loss by audiometry test, which was 3.7 times higher than that in the low-risk group (25.18%, 457/1815). Half of the key indicators were related to modifiable contexts, and they were identified as significantly associated with the incident hearing loss. These results demonstrated that the developed model would be feasible to identify residents at high risk of hearing loss via regular community-level health examinations and detecting individualized risk factors, and eventually provide precision interventions.

Utilizing True Wireless Stereo Earbuds in Automated Pure-Tone Audiometry

True wireless stereo (TWS) earbuds have become popular and widespread in recent years, and numerous automated pure-tone audiometer applications have been developed for portable devices. However, most of these applications require specifically designed earphones to which the public may not have access. Therefore, the present study investigates the accuracy of automated pure-tone audiometry based on TWS earbuds (Honor FlyPods). The procedure for developing an automated pure-tone audiometer is reported. Calibration of the TWS earbuds was accomplished by electroacoustic measurements and establishing corrected reference equivalent threshold sound pressure levels. The developed audiometer was then compared with a clinical audiometer using 20 hearing-impaired participants. The average signed and absolute deviations between hearing thresholds measured using the two audiometers were 3.1 dB and 6.7 dB, respectively. The overall accuracy rate in determining the presence/absence of hearing loss was 81%. The results show that the proposed procedure for an automated air-conduction audiometer based on TWS earbuds is feasible, and the system gives accurate hearing level estimation using the reported calibration framework.

Validation of SHOEBOX QuickTest Hearing Loss Screening Tool in Individuals With Cognitive Impairment

Objectives: The aim of this study was to validate a novel iPad-based rapid hearing loss screening tool (SHOEBOX QuickTest) in individuals with cognitive impairment.

Design: Cross-sectional validation study.

Setting: Bruyère Research Institute, Ottawa, Canada.

Subjects and Methods: Twenty-five individuals with mild cognitive impairment (MCI) and mild dementia from the Bruyère Memory Program were included in this study. The study consisted of two components: (1) SHOEBOX QuickTest hearing screener and (2) a conventional hearing test (pure tone audiometry).

Measurements: Hearing was assessed at 1,000, 2,000, and 4,000 Hz separately for each ear. The agreement between hearing ability groupings (good vs. reduced) from conventional hearing test and SHOEBOX QuickTest was determined. Specifically, accuracy, sensitivity, specificity, as well as alignment between conventional thresholds and hearing threshold ranges.

Results: An overall accuracy of 84% was observed for SHOEBOX QuickTest, and a sensitivity and specificity of 100 and 66.7%, respectively. 72% ([95% CI], 60.0–84.1%) of conventional audiometry thresholds were within the pre-established 10 dB SHOEBOX QuickTest.

Conclusion: SHOEBOX QuickTest is a valid hearing loss screening tool for individuals with cognitive impairment. Implementing this iPad-based screening tool in memory clinics could not only aid in the timely diagnosis of hearing loss, but also assist physicians in providing a better assessment of cognitive impairment by ruling out hearing loss as a confounding variable.

Validation of a Personalized Hearing Screening Mobile Health Application for Persons with Moderate Hearing Impairment

Hearing impairment is a frequent human sensory impairment. It was estimated that over 50% of those aged >75 years experience hearing impairment in the United States. Several hearing impairment–related factors are detectable through screening; thus, further deterioration can be avoided. Early identification of hearing impairment is the key to effective management. However, hearing screening resources are scarce or inaccessible, underlining the importance of developing user-friendly mobile health care systems for universal hearing screening. Mobile health (mHealth) applications (apps) act as platforms for personalized hearing screening to evaluate an individual’s risk of developing hearing impairment. We aimed to evaluate and compare the accuracy of smartphone-based air conduction and bone conduction audiometry self-tests with that of standard air conduction and bone conduction pure-tone audiometry tests. Moreover, we evaluated the use of smartphone-based air conduction and bone conduction audiometry self-tests in conductive hearing loss diagnosis. We recruited 103 patients (206 ears) from an otology clinic. All patients were aged ≥20 years. Patients who were diagnosed with active otorrhea was excluded. Moderate hearing impairment was defined as hearing loss with mean hearing thresholds >40 dB. All patients underwent four hearing tests performed by a board-certified audiologist: a smartphone-based air conduction audiometry self-test, smartphone-based bone conduction audiometry self-test, standard air-conduction pure-tone audiometry, and standard bone conduction pure-tone audiometry. We compared and analyzed the results of the smartphone-based air conduction and bone conduction audiometry self-tests with those of the standard air conduction and bone conduction pure-tone audiometry tests. The sensitivity of the smartphone-based air conduction audiometry self-test was 0.80 (95% confidence interval CI = 0.71–0.88) and its specificity was 0.84 (95% CI = 0.76–0.90), respectively. The sensitivity of the smartphone-based bone conduction audiometry self-test was 0.64 (95% CI = 0.53–0.75) and its specificity was 0.71 (95% CI = 0.62–0.78). Among all the ears, 24 were diagnosed with conductive hearing loss. The smartphone-based audiometry self-tests correctly diagnosed conductive hearing loss in 17 of those ears. The personalized smartphone-based audiometry self-tests correctly diagnosed hearing loss with high sensitivity and high specificity, and they can be a reliable screening test to rule out moderate hearing impairment among the population. It provided patients with moderate hearing impairment with personalized strategies for symptomatic control and facilitated individual case management for medical practitioners.

Telehealth Audiology and Virtual Hearing Screenings: A Case Report

Clinic closures across the United States in response to the coronavirus disease 2019 (COVID-19) pandemic meant that many audiology services were reduced to phone calls, video visits, and modified services (e.g., curbside, mail-ins, drop offs). Audiologists and other providers needed a way to manage hearing- and ear-related complaints via telehealth. A simple pure tone air conduction threshold test performed at home was used to determine which patients needed to come into the clinic for an in-person appointment. This case will review a 56-year-old male who was being treated for an idiopathic sudden sensorineural hearing loss prior to clinic closure. He had on file a comprehensive audiogram at first onset of symptoms and was treated with oral steroids. Virtual hearing testing was then utilized for a variety of other patients from teenagers to adults to triage hearing- and ear-related complaints while clinics were closed for in-person visits.

Optimization of the Speech Test Material in a Group of Hearing Impaired Subjects: A Feasibility Study for Multilingual Digit Triplet Test Development

Background: The development of the global digit-in-noise test requires optimization of each language version on a group of normal-hearing native-speakers. An alternative solution may be an adaptive optimization during ongoing tests in a group of subjects with unknown hearing impairments. The objective of the research was to compare the optimization results between these groups. Methods: Digit triplets consisting of three pseudo-randomly selected digits were presented in speech-shaped noise at various signal-to-noise ratios (SNRs), according to the protocol of the final speech test. Digit-specific and position-specific speech reception thresholds (SRTs) were determined and compared between groups. Results: The study sample consisted of 82 subjects, 26 normal-hearing subjects and 56 patients with diverse hearing disorders. Statistically significant differences in digit-specific SRTs between the control and the investigated group were obtained for three digits in continuous noise (digits 0, 4, 6; p-value of 0.04, 0.03, 0.05) and two in modulated noise (digits 1 and 6; p-value of 0.05 and 0.01). An analysis including only ears with SRTs within the range of the normal hearing control group showed no statistically significant differences between digits. Conclusion: Optimization of speech material can be carried out in a group of subjects with unknown hearing impairments, provided the ears with scores outside normal range are rejected.

SARS-CoV-2 and hearing: An audiometric analysis of COVID-19 hospitalized patients

PURPOSE

COVID-19 associated hearing loss is still an ongoing matter of debate. No original studies exist on audiological effects of SARS-CoV-2 infection in hospitalized patients. The main objective was to determine whether SARS-CoV-2 may affect auditory function in clinically ill COVID-19 patients.

MATERIALS AND METHODS

COVID-19 patients with moderate-severe disease and without prior history of hearing abnormalities were enrolled from a tertiary referral center, and matched with controls. Participants performed an audiometric evaluation, and thresholds were compared.

RESULTS

120 ears from 60 patients were enrolled. Patients with COVID-19 showed worse mean auditory thresholds starting from 1000 Hz through higher frequencies, when compared to controls (1000 Hz: 18.52 ± 5.49 dB HL in controls vs 25.36 ± 6.79 dB HL in COVID-19, p < 0.001; 2000Hz: 17.50 ± 5.57 dB HL in controls vs 21.96 ± 7.05 dB HL in COVID-19, p = 0.010; 3000Hz: 17.97 ± 8.07 dB HL in controls vs 25 ± 9.38 dB HL in COVID-19, p = 0.003; 4000 Hz: 20.16 ± 10.12 dB HL in controls vs 29.55 ± 11.26 dB HL in COVID-19, p = 0.001; 8000 Hz: 31.09 ± 12.75 dB HL in controls vs 40.71 ± 19.40 dB HL in COVID-19, p = 0.030; Pure Tone Average: 20.42 ± 4.29 dB HL in controls vs 24.85 ± 5.62 dB HL in COVID-19, p = 0.001). Statistical significance persisted after adjusting for confounders such as age, gender and various comorbidities (p < 0.05).

CONCLUSIONS

SARS-CoV-2 may affect hearing in COVID-19 patients with moderate-severe disease. Results are in line with the previous suggested effects of COVID-19 on auditory system. This study is expected to encourage further research on this topic.

[Application areas of medical apps in otolaryngology]

The use of medical apps is becoming increasingly important as it offers new solutions in healthcare. Steadily growing computing and storage capacities in combination with high-precision sensors make smartphones effective tools for medical diagnostics and treatment. The use of this technology offers immense advantages, such as direct availability or independence from opening times. However, it also harbors risks such as unfiltered data storage and transmission. The consulting physician should exercise great care when selecting and recommending apps, particularly since only a few have been certified as medical devices to date. There is a steadily growing range of products on the market for otorhinolaryngology. The scientific evidence and quality of the apps vary widely, but tools exist for their validation by physicians and patients. The present training course is intended to help increase knowledge in this new, rapidly developing area.

[Mobile solutions in hearing assessment]

PURPOSE OF THE STUDY

To evaluate the effectiveness of the application of the web application "Automated system of primary hearing assessment" created by us for the diagnosis of hearing impairment in different age groups.

MATERIAL AND METHODS

With the help of this web application, 712 patients were examined in 3 age groups: group 1 - patients aged 18 to 44 years, 196 people (average age 25.6±2.7 years), group 2 - patients aged 45 to 59 years, 265 people (mean age 46.3±3.6 years), 3rd group - patients 60 years old and older, 251 people (mean age 75.4±1.1 years).

RESULTS

It was revealed that 61.8% of patients had risk factors for the development of hearing loss. In the 1st age group, one risk factor for hearing loss prevailed, in the 2nd and 3rd groups, up to 5-9 factors were simultaneously combined. Clinically significant hearing loss was found in 24.3% of patients. Hearing studies at frequencies of 10 and 12 kHz revealed latent hearing loss in 31.3% of patients, 57% of them had risk factors for the development of hearing loss. Comparative analysis in the groups showed that hearing impairment at high frequencies was found in 47.4% of patients in older age groups and in 15.8% of young people. The possibility of performing otoscopy images made it possible to identify changes in the tympanic membrane in 17.1% of patients, to give a correct conclusion about the state of their hearing and to propose an algorithm for further examination. It was found that the sensitivity of the study in the web application was 98%, the specificity - 99.9%.

FINDINGS

The use of the web application allows assessing the risk factors for the development of hearing loss, identifying patients with latent hearing loss, objectifying the study with otoscopy images, and remotely obtaining a conclusion about the state of hearing from a specialist doctor.

Smartphone-Based Applications to Detect Hearing Loss: A Review of Current Technology

BACKGROUND/OBJECTIVES

Age-related hearing loss (ARHL) is a widely prevalent yet manageable condition that has been linked to neurocognitive and psychiatric comorbidities. Multiple barriers hinder older individuals from being diagnosed with ARHL through pure-tone audiometry. This is especially true during the COVID-19 pandemic, which has resulted in the closure of many outpatient audiology and otolaryngology offices. Smartphone-based hearing assessment apps may overcome these challenges by enabling patients to remotely self-administer their own hearing examination. The objective of this review is to provide an up-to-date overview of current mobile health applications (apps) that claim to assess hearing.

DESIGN

Narrative review.

MEASUREMENTS

The Apple App Store and Google Play Store were queried for apps that claim to assess hearing. Relevant apps were downloaded and used to conduct a mock hearing assessment. Names of included apps were searched on four literature databases (PubMed/MEDLINE, EMBASE, Cochrane Library, and CINAHL) to determine which apps had been validated against gold standard methods.

RESULTS

App store searches identified 44 unique apps. Apps differed with respect to the type of test offered (e.g., hearing threshold test), cost, strategies to reduce ambient noise, test output (quantitative vs qualitative results), and options to export results. Validation studies were identified for seven apps.

CONCLUSION

Given their low cost and relative accessibility, smartphone-based hearing apps may facilitate screening for ARHL, particularly in the setting of limitations on in-person medical care due to COVID-19. However, app features vary widely, few apps have been validated, and user-centered designs for older adults are largely lacking. Further research and validation efforts are necessary to determine whether smartphone-based hearing assessments are a feasible and accurate screening tool for ARHL. Key Points Age-related hearing loss is a prevalent yet undertreated condition among older adults. Why Does this Paper Matter?     Smartphone-based hearing test apps may facilitate remote screening for hearing loss, but limitations surrounding app validation, usability, equipment calibration, and data security should be addressed.

Contemporary Review of Smartphone Apps for Tinnitus Management and Treatment

Tinnitus is a complex and heterogeneous psycho-physiological disorder responsible for causing a phantom ringing or buzzing sound albeit the absence of an external sound source. It has a direct influence on affecting the quality of life of its sufferers. Despite being around for a while, there has not been a cure for tinnitus, and the usual course of action for its treatment involves use of tinnitus retaining and sound therapy, or Cognitive Behavioral Therapy (CBT). One positive aspect about these therapies is that they can be administered face-to-face as well as delivered via internet or smartphone. Smartphones are especially helpful as they are highly personalized devices, and offer a well-established ecosystem of apps, accessible via respective marketplaces of differing mobile platforms. Note that current therapeutic treatments such as CBT have shown to be effective in suppressing the tinnitus symptoms when administered face-to-face, their effectiveness when being delivered using smartphones is not known so far. A quick search on the prominent market places of popular mobile platforms (Android and iOS) yielded roughly 250 smartphone apps offering tinnitus-related therapies and tinnitus management. As this number is expected to steadily increase due to high interest in smartphone app development, a contemporary review of such apps is crucial. In this paper, we aim to review scientific studies validating the smartphone apps, particularly to test their effectiveness in tinnitus management and treatment. We use the PRISMA guidelines for identification of studies on major scientific literature sources and delineate the outcomes of identified studies.

A Smartphone-Based Approach to Screening for Sudden Sensorineural Hearing Loss: Cross-Sectional Validity Study

Background

Sudden sensorineural hearing loss (SSNHL) is an otologic emergency that warrants urgent management. Pure-tone audiometry remains the gold standard for definitively diagnosing SSNHL. However, in clinical settings such as primary care practices and urgent care facilities, conventional pure-tone audiometry is often unavailable.

Objective

This study aimed to determine the correlation between hearing outcomes measured by conventional pure-tone audiometry and those measured by the proposed smartphone-based Ear Scale app and determine the diagnostic validity of the hearing scale differences between the two ears as obtained by the Ear Scale app for SSNHL.

Methods

This cross-sectional study included a cohort of 88 participants with possible SSNHL who were referred to an otolaryngology clinic or emergency department at a tertiary medical center in Taipei, Taiwan, between January 2018 and June 2019. All participants underwent hearing assessments with conventional pure-tone audiometry and the proposed smartphone-based Ear Scale app consecutively. The gold standard for diagnosing SSNHL was defined as the pure-tone average (PTA) difference between the two ears being ≥30 dB HL. The hearing results measured by the Ear Scale app were presented as 20 stratified hearing scales. The hearing scale difference between the two ears was estimated to detect SSNHL.

Results

The study sample comprised 88 adults with a mean age of 46 years, and 50% (44/88) were females. PTA measured by conventional pure-tone audiometry was strongly correlated with the hearing scale assessed by the Ear Scale app, with a Pearson correlation coefficient of .88 (95% CI .82-.92). The sensitivity of the 5–hearing scale difference (25 dB HL difference) between the impaired ear and the contralateral ear in diagnosing SSNHL was 95.5% (95% CI 87.5%-99.1%), with a specificity of 66.7% (95% CI 43.0%-85.4%).

Conclusions

Our findings suggest that the proposed smartphone-based Ear Scale app can be useful in the evaluation of SSNHL in clinical settings where conventional pure-tone audiometry is not available.

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

Background

Hearing 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.

Objective

We 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.

Methods

In 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.

Results

The 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.

Conclusions

Smartphone-based audiometry may be a dependable screening test to rule out moderate hearing impairment in the older population.

Personal Music Players Use and Other Noise Hazards among Children 11 to 12 Years Old

Exposure to loud music-due to widespread personal music players (PMPs) and noisy leisure activities-are major risk factors for noise induced hearing loss (NIHL) in adolescents. However, there is little evidence of the impact of noise on the hearing of younger children. This study aimed to explore an association between PMP use and hearing, and to identify other sources of noise among children. The study sample consisted of 1032 children aged 11-12 years old. Hearing thresholds were determined from 0.5 to 8 kHz. PMP use and other noise exposures were evaluated using a survey. We found that 82% of the children had a PMP, and 78% were exposed to noise when playing computer games. An audiometric notch was documented in 1.3% of the children. Only 11.5% of the children ever used hearing protection while engaged in noisy activities. We found no convincing evidence of an association between PMP use and hearing thresholds, although our results suggest that tinnitus may be an early sign of NIHL in young children. The study shows a need to provide children, their parents, and educators with knowledge of how to take care of hearing, including how to avoid and minimize noise exposure.

The Role of Patient-Site Facilitators in Teleaudiology: A Scoping Review

Purpose Teleaudiology helps improve access to hearing health care by overcoming the geographic gap between providers and patients. In many teleaudiology encounters, a facilitator is needed at the patient site to help with hands-on aspects of procedures. The aim of this study was to review the scope and nature of research around patient-site facilitators in teleaudiology. We focused on identifying the facilitators' background, training, and responsibilities. Method To conduct this scoping review, we searched PubMed, CINAHL, and Embase. To be included, studies needed to address teleaudiology; be experimental/quasi-experimental, correlational/predictive, or descriptive; be published in English; and include the use of a facilitator at the patient location. Results A total of 82 studies met the inclusion criteria. The available literature described a number of different individuals in the role of the patient-site facilitator, including audiologists, students, and local aides. Fifty-seven unique tasks were identified, including orienting the client to the space, assisting with technology, and assisting with audiology procedures. The largest number of studies (n = 42) did not describe the facilitators' training. When reported, the facilitators' training was heterogenous in terms of who delivered the training, the length of the training, and the training content. Conclusions Across studies, the range of duties performed by patient-site facilitators indicates they may have an important role in teleaudiology. However, details are still needed surrounding their background, responsibilities, and training. Future research is warranted exploring the role of the patient-site facilitator, including their impact on teleaudiology service delivery. Supplemental Material https://doi.org/10.23641/asha.12475796.

Smartphone and Mobile Health Apps for Tinnitus: Systematic Identification, Analysis, and Assessment

Background

Modern smartphones contain sophisticated high-end hardware features, offering high computational capabilities at extremely manageable costs and have undoubtedly become an integral part in users' daily life. Additionally, smartphones offer a well-established ecosystem that is easily discoverable and accessible via the marketplaces of differing mobile platforms, thus encouraging the development of many smartphone apps. Such apps are not exclusively used for entertainment purposes but are also commonplace in health care and medical use. A variety of those health and medical apps exist within the context of tinnitus, a phantom sound perception in the absence of any physical external source.

Objective

In this paper, we shed light on existing smartphone apps addressing tinnitus by providing an up-to-date overview.

Methods

Based on PRISMA guidelines, we systematically searched and identified existing smartphone apps on the most prominent app markets, namely Google Play Store and Apple App Store. In addition, we applied the Mobile App Rating Scale (MARS) to evaluate and assess the apps in terms of their general quality and in-depth user experience.

Results

Our systematic search and screening of smartphone apps yielded a total of 34 apps (34 Android apps, 26 iOS apps). The mean MARS scores (out of 5) ranged between 2.65-4.60. The Tinnitus Peace smartphone app had the lowest score (mean 2.65, SD 0.20), and Sanvello—Stress and Anxiety Help had the highest MARS score (mean 4.60, SD 0.10). The interrater agreement was substantial (Fleiss κ=0.74), the internal consistency was excellent (Cronbach α=.95), and the interrater reliability was found to be both high and excellent—Guttman λ6=0.94 and intraclass correlation, ICC(2,k) 0.94 (95% CI 0.91-0.97), respectively.

Conclusions

This work demonstrated that there exists a plethora of smartphone apps for tinnitus. All of the apps received MARS scores higher than 2, suggesting that they all have some technical functional value. However, nearly all identified apps were lacking in terms of scientific evidence, suggesting the need for stringent clinical validation of smartphone apps in future. To the best of our knowledge, this work is the first to systematically identify and evaluate smartphone apps within the context of tinnitus.

Worldwide Prevalence of Hearing Loss Among Smartphone Users: Cross-Sectional Study Using a Mobile-Based App

Background

In addition to the aging process, risk factors for hearing loss in adults include, among others, exposure to noise, use of ototoxic drugs, genetics, and limited access to medical care. Differences in exposure to these factors are bound to be reflected in the prevalence of hearing loss. Assessment of hearing loss can easily be carried out on a large scale and at low cost using mobile apps.

Objective

This study aimed to conduct a worldwide assessment of the differences in hearing loss prevalence between countries in a group of mobile device users.

Methods

Hearing tests were conducted using the open-access Android-based mobile app Hearing Test. The app is available free of charge in the Google Play store, provided that consent to the use of the results for scientific purposes is given. This study included hearing tests carried out on device models supported by the app with bundled headphones in the set. Calibration factors for supported models were determined using the biological method. The tests consisted of self-determining the quietest audible tone in the frequency range from 250 Hz to 8 kHz by adjusting its intensity using the buttons. The ambient noise level was optionally monitored using a built-in microphone. Following the test, the user could compare his hearing threshold against age norms by providing his or her age. The user's location was identified based on the phone’s IP address.

Results

From November 23, 2016 to November 22, 2019, 733,716 hearing tests were conducted on 236,716 mobile devices across 212 countries. After rejecting the tests that were incomplete, performed with disconnected headphones, not meeting the time criterion, repeated by the same user, or carried out regularly on one device, 116,733 of 733,716 tests (15.9%) were qualified for further analysis. The prevalence of hearing loss, defined as the average threshold at frequencies 0.5 kHz, 1 kHz, 2 kHz, and 4 kHz above 25 dB HL in the better ear, was calculated at 15.6% (95% CI 15.4-15.8). Statistically significant differences were found between countries (P<.001), with the highest prevalences for Bangladesh, Pakistan, and India (>28%) and the lowest prevalences for Taiwan, Finland, and South Korea (<11%).

Conclusions

Hearing thresholds measured by means of mobile devices were congruent with the literature data on worldwide hearing loss prevalence. Uniform recruitment criteria simplify the comparison of the hearing loss prevalence across countries. Hearing testing on mobile devices may be a valid tool in epidemiological studies carried out on a large scale.

Mobile Applications in Otolaryngology: A Systematic Review of the Literature, Apple App Store and the Google Play Store

OBJECTIVES

Although the last few years have seen an increased number of smartphone applications (apps) disseminated in the field of Otolaryngology (ORL), these apps vary widely in quality. The aim of this paper, therefore, is to systematically review ORL apps directed towards patients in mobile app stores and the current literature.

METHODS

The Google Play Store, Apple App Store and PubMed were searched for ORL apps for patients using various keywords pertaining to different ORL subspecialties. Apps not relevant to the scope of this research and/or duplicates, educational apps, apps promoting a business, apps requiring specific separate hardware, and apps in non-English were excluded. In PubMed, keywords pertaining to the subspecialties were combined with "mobile app" in a search query; literature reviews, editorials, case reports, conference papers, duplicate articles, and articles irrelevant to ORL apps were excluded. The quality of apps with the highest number of reviews was assessed using the "Mobile App Rating Scale" (MARS), while the quality of the articles was rated using "The Strengthening the Reporting of Observational Studies in Epidemiology" (STROBE) Statement.

RESULTS

After searching the app stores, 1074 apps were included and grouped according to their ORL subspecialties. The overall MARS score of the ten most popular apps in each category was 3.65 out of 5. A total of 636 articles were identified in the literature, and 193 were included. The mean adherence percentage of the articles to the STROBE checklist was of 84.37%.

CONCLUSIONS

Although the apps currently available need further development, their application in ORL appears promising. Further dialogue between physicians and patients, as well as formal support from professional and scientific associations, should be encouraged.

Results of hearing screening of school-age children in Bishkek, Kyrgyzstan

Aim:

To gauge the prevalence of hearing loss in school children in Bishkek, Kyrgyzstan, and refer pupils with positive results for further diagnostic testing.

Background:

According to WHO data, hearing disorders are common in school-age children. Screening for hearing loss is an important preventative tool, helping to avoid further complications. Expenditure that supports early child development can reduce future outlay on health care and social services; it can eliminate disability problems, education deficits, and social maladaptation in later adult life.

Methods:

Pure-tone air-conduction hearing thresholds were obtained at 0.5–8 kHz. The results of the hearing screening examination were regarded as positive if pure-tone thresholds were higher than 20 dB HL in one or both ears at one or more of the test frequencies. Data were also obtained from follow-up visits of children who failed the initial screening.

Findings:

This study included 452 children aged 7–13 years old. Based on audiograms, screening showed that 123 (27.2%) of the children had hearing impairment. The study has important implications for clinical practice and health policy. There is a need for systematic monitoring of hearing status among children of this age, and parents and educators need to be made aware of the significance of hearing loss.

Smartphone Apps in the Context of Tinnitus: Systematic Review

Smartphones containing sophisticated high-end hardware and offering high computational capabilities at extremely manageable costs have become mainstream and an integral part of users' lives. Widespread adoption of smartphone devices has encouraged the development of many smartphone applications, resulting in a well-established ecosystem, which is easily discoverable and accessible via respective marketplaces of differing mobile platforms. These smartphone applications are no longer exclusively limited to entertainment purposes but are increasingly established in the scientific and medical field. In the context of tinnitus, the ringing in the ear, these smartphone apps range from relief, management, self-help, all the way to interfacing external sensors to better understand the phenomenon. In this paper, we aim to bring forth the smartphone applications in and around tinnitus. Based on the PRISMA guidelines, we systematically analyze and investigate the current state of smartphone apps, that are directly applied in the context of tinnitus. In particular, we explore Google Scholar, CiteSeerX, Microsoft Academics, Semantic Scholar for the identification of scientific contributions. Additionally, we search and explore Google's Play and Apple's App Stores to identify relevant smartphone apps and their respective properties. This review work gives (1) an up-to-date overview of existing apps, and (2) lists and discusses scientific literature pertaining to the smartphone apps used within the context of tinnitus.

A Mobile Phone-Based Approach for Hearing Screening of School-Age Children: Cross-Sectional Validation Study

Background

Pure-tone screening (PTS) is considered as the gold standard for hearing screening programs in school-age children. Mobile devices, such as mobile phones, have the potential for audiometric testing.

Objective

This study aimed to demonstrate a new approach to rapidly screen hearing status and provide stratified test values, using a smartphone-based hearing screening app, for each screened ear of school-age children.

Method

This was a prospective cohort study design. The proposed smartphone-based screening method and a standard sound-treated booth with PTS were used to assess 85 school-age children (170 ears). Sound-treated PTS involved applying 4 test tones to each tested ear: 500 Hz at 25 dB and 1000 Hz, 2000 Hz, and 4000 Hz at 20 dB. The results were classified as pass (normal hearing in the ear) or fail (possible hearing impairment). The proposed smartphone-based screening employs 20 stratified hearing scales. Thresholds were compared with those of pure-tone average (PTA).

Results

A total of 85 subjects (170 ears), including 38 males and 47 females, aged between 11 and 12 years with a mean (SD) of 11 (0.5) years, participated in the trial. Both screening methods produced comparable pass and fail results (pass in 168 ears and fail in 2 ears). The smartphone-based screening detected moderate or worse hearing loss (average PTA>25 dB) accurately. Both the sensitivity and specificity of the smartphone-based screening method were calculated at 100%.

Conclusions

The results of the proposed smartphone-based self-hearing test demonstrated high concordance with conventional PTS in a sound-treated booth. Our results suggested the potential use of the proposed smartphone-based hearing screening in a school-age population.