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Self-Test Web-Based Pure-Tone Audiometry: Validity Evaluation and Measurement Error Analysis

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

Online hearing tests conducted in home settings on a personal computer (PC) require prior calibration. Biological calibration consists of approximating the reference sound level via the hearing threshold of a person with normal hearing. The objective of this study was to identify the error of the proposed methods of biological calibration, their duration, and the subjective difficulty in conducting these tests via PC. Seven methods have been proposed for measuring the calibration coefficients. All measurements were performed in reference to the hearing threshold of a normal-hearing person. Three methods were proposed for determining the reference sound level on the basis of these calibration coefficients. Methods were compared for the estimated error, duration, and difficulty of the calibration. Web-based self-assessed measurements of the calibration coefficients were carried out in 3 series: (1) at a otolaryngology clinic, (2) at the participant’s home, and (3) again at the clinic. Additionally, in series 1 and 3, pure-tone audiometry was conducted and series 3 was followed by an offline questionnaire concerning the difficulty of the calibration. Participants were recruited offline from coworkers of the Department and Clinic of Otolaryngology, Wroclaw Medical University, Poland. All 25 participants, aged 22-35 years (median 27) completed all tests and filled in the questionnaire. The smallest standard deviation of the calibration coefficient in the test-retest measurement was obtained at the level of 3.87 dB (95% CI 3.52-4.29) for the modulated signal presented in accordance with the rules of Bekesy’s audiometry. The method is characterized by moderate duration time and a relatively simple procedure. The simplest and shortest method was the method of self-adjustment of the sound volume to the barely audible level. In the test-retest measurement, the deviation of this method equaled 4.97 dB (95% CI 4.53-5.51). Among methods determining the reference sound level, the levels determined independently for each frequency revealed the smallest error. The estimated standard deviations of the difference in the hearing threshold between the examination conducted on a biologically calibrated PC and pure-tone audiometry varied from 7.27 dB (95% CI 6.71-7.93) to 10.38 dB (95% CI 9.11-12.03), depending on the calibration method. In this study, an analysis of biological calibration was performed and the presented results included calibration error, calibration time, and calibration difficulty. These values determine potential applications of Web-based hearing tests conducted in home settings and are decisive factors when selecting the calibration method. If there are no substantial time limitations, it is advisable to use Bekesy method and determine the reference sound level independently at each frequency because this approach is characterized by the lowest error.

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.

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.