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

A Multicenter Validity Study of Four Smartphone Hearing Test Apps in Optimized and Home Environments

OBJECTIVE

Pure tone audiometry (PTA) is the gold standard for hearing assessment. However, it requires access to specialized equipment. Smartphone audiometry applications (apps) have been developed to perform automated threshold audiometry and could allow patients to perform self-administered screening or monitoring. This study aimed to assess the validity and feasibility of patients using apps to self-assess hearing thresholds at home, with comparison to PTA.

METHODS

A multi-center, prospective randomized study was conducted amongst patients undergoing PTA in clinics. Participants were randomly allocated to one of four publicly-available apps designed to measure pure tone thresholds. Participants used an app once in optimal sound-treated conditions and a further three times at home. Ear-specific frequency-specific thresholds and pure tone average were compared using Pearson correlation coefficient. The percentage of app hearing tests with results within ±10 dB of PTA was calculated. Patient acceptability was assessed via an online survey.

RESULTS

One hundred thirty-nine participants submitted data. The results of two at-home automated smartphone apps correlated strongly/very strongly with PTA average and their frequency-specific median was within ±10 dB accuracy. Smartphone audiometry performed in sound-treated and home conditions were very strongly correlated. The apps were rated as easy/very easy to use by 90% of participants and 90% would be happy/very happy to use an app to monitor their hearing.

CONCLUSION

Judicious use of self-performed smartphone audiometry was both valid and feasible for two of four apps. It could provide frequency-specific threshold estimates at home, potentially allowing assessments of patients remotely or monitoring of fluctuating hearing loss.

LEVEL OF EVIDENCE

2 Laryngoscope, 134:2864-2870, 2024.

Breaking Sound Barriers: Exploring Tele-Audiology's Impact on Hearing Healthcare

Hearing impairment is a global issue, affecting billions of people; however, there is a gap between the population affected by hearing loss and those able to access hearing healthcare. Tele-audiology, the application of telemedicine in audiology, serves as a new form of technology which aims to provide synchronous or asynchronous hearing healthcare. In this article, we reviewed some recent studies of tele-audiology-related topics to have a glimpse of the current development, associated challenges, and future advancement. Through the utilization of tele-audiology, patients can conveniently access hearing healthcare, and thus save travel costs and time. Recent studies indicate that remote hearing screening and intervention are non-inferior to the performance of traditional clinical pathways. However, despite its potential benefits, the implementation of tele-audiology faces numerous challenges, and audiologists have varying attitudes on this technology. Overcoming obstacles such as high infrastructure costs, limited reimbursement, and the lack of quality standards calls for concerted efforts to develop effective strategies. Ethical concerns, reimbursement, and patient privacy are all crucial aspects requiring in-depth discussion. Enhancing the education and training of students and healthcare workers, along with providing relevant resources, will contribute to a more efficient, systematic hearing healthcare. Future research will aim to develop integrated models with evidence-based protocols and incorporating AI to enhance the affordability and accessibility of hearing healthcare.

Validated mobile applications in otolaryngology head and neck surgery for patient and physicians: A systematic literature review

IMPORTANCE

Mobile apps in the field of ORL-HNS, are widely used by patients and physicians, but neither necessarily developed in collaboration with healthcare professionals nor subjected to regulations by the United States Food and Drug Administration guidelines, with a resultant potential of risk for its users.

OBJECTIVE

To provide the ORL-HNS physician with an updated list of scientific peer review literature- validated mobile apps for safe use for both the clinician and the patients, for screening, diagnosis, therapy and follow up for various ORL-HNS pathologies.

EVIDENCE REVIEW

A comprehensive systematic review of the scientific literature was conducted in "PubMed," "EMBASE," and "Web of Science" without limitation of publication date up to January 1st, 2023. The included papers validated mobile apps in the ORL-HNS discipline. Each study was evaluated using the "Strengthening the Reporting of Observational Studies in Epidemiology" (STROBE) tool.

FINDINGS

From the thousands of unregulated ORL-HNS mobile apps available for download and use in the various app stores, only 17 apps were validated for safe use by the clinician and/or patient. Their information is listed.

CONCLUSIONS AND RELEVANCE

The limited number of validated mobile apps highlights the importance to use validated apps in clinical practice, to improve evidence-based medicine and patient safety. Physician are encouraged to use and recommend their patients to use validated mobile apps only, like any other tool in clinical practice in the evidence-based era.

Optimizing age-related hearing risk predictions: an advanced machine learning integration with HHIE-S

OBJECTIVES

The elderly are disproportionately affected by age-related hearing loss (ARHL). Despite being a well-known tool for ARHL evaluation, the Hearing Handicap Inventory for the Elderly Screening version (HHIE-S) has only traditionally been used for direct screening using self-reported outcomes. This work uses a novel integration of machine learning approaches to improve the predicted accuracy of the HHIE-S tool for ARHL in older adults.

METHODS

We employed a dataset that was gathered between 2016 and 2018 and included 1,526 senior citizens from several Taipei City Hospital branches. 80% of the data were used for training (n = 1220) and 20% were used for testing (n = 356). XGBoost, Gradient Boosting, and LightGBM were among the machine learning models that were only used and assessed on the training set. In order to prevent data leakage and overfitting, the Light Gradient Boosting Machine (LGBM) model-which had the greatest AUC of 0.83 (95% CI 0.81-0.85)-was then only used on the holdout testing data.

RESULTS

On the testing set, the LGBM model showed a strong AUC of 0.82 (95% CI 0.79-0.86), far outperforming conventional techniques. Notably, several HHIE-S items and age were found to be significant characteristics. In contrast to traditional HHIE research, which concentrates on the psychological effects of hearing loss, this study combines cutting-edge machine learning techniques-specifically, the LGBM classifier-with the HHIE-S tool. The incorporation of SHAP values enhances the interpretability of the model's predictions and provides a more comprehensive comprehension of the significance of various aspects.

CONCLUSIONS

Our methodology highlights the great potential that arises from combining machine learning with validated hearing evaluation instruments such as the HHIE-S. Healthcare practitioners can anticipate ARHL more accurately thanks to this integration, which makes it easier to intervene quickly and precisely.

App-Based Hearing Screenings in Preschool Children With Different Types of Headphones: Diagnostic Study

Background

Hearing disability in preschool children can delay or impact oral communication and social skills. Provision of hearing screening tests by standard audiometry in low- to middle-income countries is problematic due to a lack of pediatric audiologists, standard hearing equipment, and standard soundproof rooms. Therefore, an innovative hearing screening tool that is easily accessible and inexpensive such as a mobile app should be considered. Headphones have been a crucial part of hearing screenings. Audiometric headphones, which serve as the reference standard, have been used in most studies. However, since audiometric headphones are not accessible in rural areas, we hypothesized that generic headphones can also be used in hearing screenings.

Objective

This study aimed to determine the sensitivity, specificity, κ coefficiency, and time consumption of the PASS-Pro (Preschool Audiometry Screening System-Pro) app when using TDH39 headphones, Beyerdynamic DT 770 PRO headphones, and generic earmuff headphones compared to standard conditioned play audiometry.

Methods

We recruited preschool children aged 4 to 5 years to participate in this study. The children received 3 PASS-Pro screening tests using different types of headphones in a quiet room and 1 standard conditioned play audiometry in a soundproof room. All tests were administered in random order. The agreement coefficient, sensitivity, specificity, and mean test duration were determined.

Results

A total of 44 children participated in this study. For mild hearing loss screening, the κ coefficients between standard conditioned play audiometry and the PASS-Pro app using TDH39 headphones, Beyerdynamic DT 770 PRO headphones, and generic earmuff headphones were 0.195, 0.290, and 0.261 (P=.02, P=.002, and P=.004), respectively. The sensitivity for all headphones was 50% and the specificity was more than 88%. For moderate hearing loss screening, the κ coefficients were 0.206, 0.272, and 0.235 (all Ps=.001), respectively. The sensitivity for all headphones was 100% and the specificity was more than 92%. There were no statistical differences in sensitivity and specificity between the reference headphone (TDH39), Beyerdynamic DT 770 PRO headphone, and generic earmuff headphones (all Ps >.05). The PASS-Pro app used significantly less time to carry out hearing tests than conditioned play audiometry (P<.001).

Conclusions

The PASS-Pro app, used with generic headphones, is effective for conducting hearing screening tests in preschool children with high sensitivity and specificity.

Evaluating the hearing screening effectiveness of active noise cancellation technology among young adults: A pilot study

BACKGROUND

The population of young adults who are hearing impaired increases yearly, and a device that enables convenient hearing screening could help monitor their hearing. However, background noise is a critical issue that limits the capabilities of such a device. Therefore, this study evaluated the effectiveness of commercial active noise cancellation (ANC) headphones for hearing screening applications in the presence of background noise. In particular, six confounders were used for a comprehensive evaluation.

METHODS

We enrolled 12 young adults (a total of 23 ears with normal hearing) to participate in this study. A cross-sectional self-controlled study was conducted to explore the effectiveness of hearing screening in the presence of background noise, with a total of 240 test conditions (=3 ANC models × 2 ANC function statuses × 2 noise types × 5 noise levels × 4 frequencies) for each test ear. Subsequently, a linear regression model was used to prove the effectiveness of ANC headphones for hearing screening applications in the presence of background noise with six confounders.

RESULTS

The experimental results showed that, on average, the ANC function of headphones can improve the effectiveness of hearing screening tasks in the presence of background noise. Specifically, the statistical analysis showed that the ANC function enabled a significant 10% improvement ( p < 0.001) compared with no ANC function.

CONCLUSION

This study confirmed the effectiveness of ANC headphones for young adult hearing screening applications in the presence of background noise. Furthermore, the statistical results confirmed that as confounding variables, noise type, noise level, hearing screening frequency, ANC headphone model, and sex all affect the effectiveness of the ANC function. These findings suggest that ANC is a potential means of helping users obtain high-accuracy hearing screening results in the presence of background noise. Moreover, we present possible directions of development for ANC headphones in future studies.

Long-term Follow-up of Patients With Hernia Using the Hernia-Specific Quality-of-Life Mobile App: Feasibility Questionnaire Study

BACKGROUND

Hernia repair is one of the most common surgical procedures; however, the long-term outcomes are seldom reported due to incomplete follow-up.

OBJECTIVE

The aim of this study was to examine the use of a mobile app for the long-term follow-up of hernia recurrence, complication, and quality-of-life perception.

METHODS

A cloud-based corroborative system drove a mobile app with the HERQL (Hernia-Specific Quality-of-Life) questionnaire built in. Patients who underwent hernia repair were identified from medical records, and an invitation to participate in this study was sent through the post.

RESULTS

The response rate was 11.89% (311/2615) during the 1-year study period, whereas the recurrence rate was 1.0% (3/311). Causal relationships between symptomatic and functional domains of the HERQL questionnaire were indicated by satisfactory model fit indices and significant regression coefficients derived from structural equational modeling. Regarding patients' last hernia surgeries, 88.7% (276/311) of the patients reported them to be satisfactory or very satisfactory, 68.5% (213/311) of patients reported no discomfort, and 61.1% (190/311) of patients never experienced mesh foreign body sensation. Subgroup analysis for the most commonly used mesh repairs found that mesh plug repair inevitably resulted in worse symptoms and quality-of-life perception from the group with groin hernias.

CONCLUSIONS

The mobile app has the potential to enhance the quality of care for patients with hernia and facilitate outcomes research with more complete follow-up.

Objective Signal Analysis for Investigating Feasibility of Active Noise Cancellation in Hearing Screening

With the development of active noise cancellation (ANC) technology, ANC has been used to mitigate the effects of environmental noise on audiometric results. However, objective evaluation methods supporting the accuracy of audiometry for ANC exposure to different levels of noise have not been reported. Accordingly, the audio characteristics of three different ANC headphone models were quantified under different noise conditions and the feasibility of ANC in noisy environments was investigated. Steady (pink noise) and non-steady noise (cafeteria babble noise) were used to simulate noisy environments. We compared the integrity of pure-tone signals obtained from three different ANC headphone models after processing under different noise scenarios and analyzed the degree of ANC signal correlation based on the Pearson correlation coefficient compared to pure-tone signals in quiet. The objective signal correlation results were compared with audiometric screening results to confirm the correspondence. Results revealed that ANC helped mitigate the effects of environmental noise on the measured signal and the combined ANC headset model retained the highest signal integrity. The degree of signal correlation was used as a confidence indicator for the accuracy of hearing screening in noise results. It was found that the ANC technique can be further improved for more complex noisy environments.

A device and an app for the diagnosis and self-management of tinnitus

Tinnitus is an annoying ringing in the ears, in varying shades and intensities. Tinnitus can affect a person’s overall health and social well-being (e.g., sleep problems, trouble concentrating, anxiety, depression and inability to work). The diagnostic procedure of tinnitus usually consists of three steps: an audiological examination, psychoacoustic measurement, and a disability evaluation. All steps are performed by physicians, who use specialised hardware/software and administer questionnaires. This paper presents a system, to be used by patients, for the diagnosis and self-management of tinnitus. The system is made up of an app and a device. The app is responsible for executing – through the device – a part of the required audiological and psychoacoustic examinations, as well as administering questionnaires that evaluate disability. The paper reviews the quality of the automated audiometric reporting and the user experience provided by the app. Descriptive and inferential statistics were used to support the findings. The results show that automated reporting is comparable with that of physicians and that user experience was improved by re-designing and re-developing the acufenometry of the app. As for the user experience, two experts in Human-Computer Interaction evaluated the first version of the app: their agreement was good (Cohen’s K = 0.639) and the average rating of the app was 1.43/2. Also patients evaluated the app in its initial version: the satisfactory tasks (audiometry and questionnaires) were rated as 4.31/5 and 4.65/5. The unsatisfactory task (acufenometry) was improved and the average rating increased from 2.86/5 to 3.96/5 (p = 0.0005). Finally, the general usability of the app was increased from the initial value of 73.6/100 to 85.4/100 (p = 0.0003). The strengths of the project are twofold. Firstly, the automated reporting feature, which – to the best of our knowledge – is the first attempt in this area. Secondly, the overall app usability, which was evaluated and improved during its development. In summary, the conclusion drawn from the conducted project is that the system works as expected, and despite some weaknesses, also the replication of the device would not be expensive, and it can be used in different scenarios.

COVID-19 and the resurgence of telehealth in otolaryngology

The objective of this review is to examine the impact of the ongoing Coronavirus disease 2019 (COVID-19) pandemic on the use of telehealth in Otolaryngology. The use of telemedicine rose dramatically during the pandemic to meet the need for continued patient care while allowing for physical separation of providers and patients. Telemedicine has been used to evaluate patients with a variety of pathologies including dysphonia, vertigo, and anosmia. Innovative use of at-home exams, such as video-otoscopy has aided providers in overcoming challenges associated with a highly specialized physical exam. The use of telemedicine in Otolaryngology will likely remain essential in the post-pandemic era and has promising results for improving clinical efficiency.

Diagnostic Validity of Self-Reported Hearing Loss in Elderly Taiwanese Individuals: Diagnostic Performance of a Hearing Self-Assessment Questionnaire on Audiometry

Key Points: Question: Can the traditional Chinese version of the hearing handicap inventory for elderly screening (HHIE-S) checklist screen for age-related hearing loss (ARHL) in elderly individuals? Findings: In this cross-sectional study of 1696 Taiwanese patients who underwent annual government-funded geriatric health checkups, the Chinese version of the HHIE-S had a sensitivity of 76.9% and a specificity of 79.8% with a cutoff score greater than 6 for identifying patients with disabled hearing loss (defined as a PTA > 40 dB). Meaning: The traditional Chinese version of the HHIE-S is an effective test to detect ARHL and can improve the feasibility of large-scale hearing screening among elderly individuals. Purpose: The traditional Chinese version of the hearing handicap inventory for elderly screening (TC-HHIE-S) was translated from English and is intended for use with people whose native language is traditional Chinese, but its effectiveness and diagnostic performance are still unclear. The purpose of this study was to evaluate the validity and reliability of the traditional Chinese version of the HHIE-S for screening for age-related hearing loss (ARHL). Methods: A total of 1696 elderly people underwent the government’s annual geriatric medical examination at community hospitals. In this cross-sectional study, we recorded average conducted pure-tone averages (PTA) (0.5 kHz, 1 kHz, 2 kHz, 4 kHz), age, sex, and HHIE-S data. Receiver operating characteristic (ROC) curve analysis was used to identify the best critical point for detecting hearing impairment, and the validity of the structure was verified by the agreement between the TC-HHIE-S and PTA results. Results: The HHIE-S scores were correlated with the better-ear pure-tone threshold averages (PTAs) at 0.5–4 kHz (correlation coefficient r = 0.45). The internal consistency of the total HHIE-S score was excellent (Cronbach’s alpha = 0.901), and the test-retest reliability was also excellent (Spearman’s correlation coefficient = 0.60, intraclass correlation coefficient = 0.75). In detecting disabled hearing loss (i.e., PTA at 0.5–4 kHz > 40 dB), the HHIE-S cutoff score of > 6 had a sensitivity of 76.9% and a specificity of 79.8%. Conclusions: The traditional Chinese version of the HHIE-S is a valid, reliable, and efficient tool for large-scale screening for ARHL.

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 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.

Diagnostic Accuracy of Smartphone-Based Audiometry for Hearing Loss Detection: Meta-analysis

Background

Hearing loss is one of the most common disabilities worldwide and affects both individual and public health. Pure tone audiometry (PTA) is the gold standard for hearing assessment, but it is often not available in many settings, given its high cost and demand for human resources. Smartphone-based audiometry may be equally effective and can improve access to adequate hearing evaluations.

Objective

The aim of this systematic review is to synthesize the current evidence of the role of smartphone-based audiometry in hearing assessments and further explore the factors that influence its diagnostic accuracy.

Methods

Five databases—PubMed, Embase, Cochrane Library, Web of Science, and Scopus—were queried to identify original studies that examined the diagnostic accuracy of hearing loss measurement using smartphone-based devices with conventional PTA as a reference test. A bivariate random-effects meta-analysis was performed to estimate the pooled sensitivity and specificity. The factors associated with diagnostic accuracy were identified using a bivariate meta-regression model. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool.

Results

In all, 25 studies with a total of 4470 patients were included in the meta-analysis. The overall sensitivity, specificity, and area under the receiver operating characteristic curve for smartphone-based audiometry were 89% (95% CI 83%-93%), 93% (95% CI 87%-97%), and 0.96 (95% CI 0.93-0.97), respectively; the corresponding values for the smartphone-based speech recognition test were 91% (95% CI 86%-94%), 88% (95% CI 75%-94%), and 0.93 (95% CI 0.90-0.95), respectively. Meta-regression analysis revealed that patient age, equipment used, and the presence of soundproof booths were significantly related to diagnostic accuracy.

Conclusions

We have presented comprehensive evidence regarding the effectiveness of smartphone-based tests in diagnosing hearing loss. Smartphone-based audiometry may serve as an accurate and accessible approach to hearing evaluations, especially in settings where conventional PTA is unavailable.

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.

Effect of Realistic Test Conditions on Spectral and Temporal Processing in Normal-Hearing Listeners

Purpose To measure the effect of testing conditions (in the soundproof booth vs. quiet room), test order, and number of test sessions on spectral and temporal processing in normal-hearing (NH) listeners. Method Thirty-two adult NH listeners participated in the three experiments. For all three experiments, the stimuli were presented to the left ear at the subjects' most comfortable level through headphones. All tests were administered in an adaptive three-alternative forced-choice paradigm. Experiment 1 was designed to compare the effect of soundproof booth and quiet room test conditions on amplitude modulation detection threshold and modulation frequency discrimination threshold with each of the five modulation frequencies. Experiment 2 was designed to compare the effect of two test orders on the frequency discrimination thresholds under the quiet room test conditions. The thresholds were first measured in the ascending and descending order of four pure tones, and then with counterbalanced order. For Experiment 3, the amplitude discrimination threshold under the quiet room testing condition was assessed 3 times to determine the effect of the number of test sessions. Then the thresholds were compared over the sessions. Results Results showed no significant effect of test environment. The test order is an important variable for frequency discrimination, particularly between piano tunes and pure tones. Results also show no significant difference across test sessions. Conclusions These results suggest that a controlled test environment may not be required in spectral and temporal assessment for NH listeners. Under the quiet test environment, a single outcome measure is sufficient, but test orders should be counterbalanced.

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.

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.

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.