AUTOMATED SCREENING AUDIOMETRY IN THE DIGITAL AGE: EXPLORING UHEAR™ AND ITS USE IN A RESOURCE-STRICKEN DEVELOPING COUNTRY

The Emerging Future of Mobile Audiometry: A Prospective Validation Study of the Mimi Hearing Test Application

OBJECTIVE

The objective of this study is to assess the accuracy of the Mimi Hearing Test (MHT) mobile application in the detection of air conduction (AC) thresholds and in screening for moderate hearing loss.

STUDY DESIGN

Prospective clinical study.

SETTING

Tertiary care center.

PATIENTS

Participants with or without a varying degree of hearing loss, aged 18 years and over, without cognitive impairment and without active otorrhea or earwax impaction at the time of the hearing assessment were included.

INTERVENTION

Subjects with a ranging severity of hearing loss underwent a conventional in-booth audiogram as well as mobile-based screening with MHT in a quiet room (45.5 dB background noise) on the same day. Both regular over-the-ear and noise-canceling headphones were tested with MHT.

MAIN OUTCOME MEASURES

Comparisons of AC thresholds between conventional audiometry and mobile-based audiometry at discrete frequencies and with pure-tone averages (PTA) were performed.

RESULTS

A total of 75 adults (mean age: 56.2 yr, 54.7% male) were recruited and 63 used for analysis. Of the thresholds measured with MHT using regular headphones, 44.0% were within 10 dB of the conventional audiogram, compared to 39.3% using noise-canceling headphones. MHT demonstrated best accuracy at high frequencies (4-8 kHz). When screening for moderate hearing loss (PTA >40 dB HL), MHT demonstrated a sensitivity and specificity of 100.0% and 80.2%, respectively.

CONCLUSIONS

MHT is reliable for identifying moderate hearing loss but lacks precision in detecting thresholds at low frequencies. Noise canceling headphones seem to improve its precision at 4,000 Hz only.

AMTASTM and user-operated smartphone research application audiometry-An evaluation study

OBJECTIVE

To evaluate two user-operated audiometry methods, the AMTASTM PC-based audiometry and a low-cost smartphone audiometry research application (R-App).

DESIGN

A repeated-measures within-subject study design was used to compare both user-operated methods to traditional manual audiometry and to evaluate test-retest reliability of each method.

STUDY SAMPLE

58 subjects were recruited in the study of which 83 ears had normal hearing thresholds and 33 ears had hearing loss (pure-tone average > 25 dB HL). Average age of participants was 44.8 years, with an age range of 11-85.

RESULTS

Standard deviation of absolute differences ranged between 3.9-6.9 dB on AMTASTM and 4.5-6.8 dB on the R-App. The highest variability was found at the 8000 Hz frequency (R-App and AMTASTM test) and 3000 Hz frequency (AMTASTM retest). Evaluation of test-retest reliability of AMTASTM and R-App showed SD of absolute differences ranging between 3.5-5.8 dB and 3.1-5.0 dB, respectively. The mean threshold difference between test and retest was within ±1.5 dB on AMTASTM and ±1 dB on the R-App.

CONCLUSION

Accuracy of AMTASTM and the R-App was within acceptable limits for audiometry and comparable to traditional manual audiometry on all tested frequencies (250-8000 Hz). Evaluation of test-retest reliability showed acceptable variation on both AMTASTM and R-App. Both user-operated methods could be reliably performed in a quiet non-soundproofed environment.

Hearing screening using the uHear™ smartphone-based app: reproducibility of results from two response modes

PURPOSE

Estimate the reproducibility of hearing screening results using the uHear™ smartphone-based app in two response modes: self-test response and test-operator.

METHODS

Reliability study conducted with 65 individuals aged ≥18 years assisted at the Speech-language and Hearing Therapy clinic of a public higher-education institution. Hearing screening was conducted by a single researcher using the uHear app and earbud headphones in a soundproof booth. Participants responded to sound stimuli in both self-test response mode and test-operator mode. The order in which these two uHear test modes were applied was altered according to the entrance of each participant in the study. The correspondence between the hearing thresholds obtained from each response mode was analyzed and their Intraclass Correlation Coefficient (ICC) was estimated.

RESULTS

A correspondence of ±5 dBHL >75% was observed between these hearing thresholds. The ICC values showed excellent agreement between the two response modes at all frequencies >40 dBHL tested.

CONCLUSION

The two hearing screening response modes using the uHear app presented high reproducibility, suggesting that the test-operator mode is a viable alternative when the self-test response mode is not recommended.

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.

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.

Tele-Audiology: Current State and Future Directions

The importance of tele-audiology has been heightened by the current COVID-19 pandemic. The present article reviews the current state of tele-audiology practice while presenting its limitations and opportunities. Specifically, this review addresses: (1) barriers to hearing healthcare, (2) tele-audiology services, and (3) tele-audiology key issues, challenges, and future directions. Accumulating evidence suggests that tele-audiology is a viable service delivery model, as remote hearing screening, diagnostic testing, intervention, and rehabilitation can each be completed reliably and effectively. The benefits of tele-audiology include improved access to care, increased follow-up rates, and reduced travel time and costs. Still, significant logistical and technical challenges remain from ensuring a secure and robust internet connection to controlling ambient noise and meeting all state and federal licensure and reimbursement regulations. Future research and development, especially advancements in artificial intelligence, will continue to increase tele-audiology acceptance, expand remote care, and ultimately improve patient satisfaction.

Digital Technology for Remote Hearing Assessment—Current Status and Future Directions for Consumers

Globally, more than 1.5 billion people have hearing loss. Unfortunately, most people with hearing loss reside in low- and middle-income countries (LMICs) where traditional face-to-face services rendered by trained health professionals are few and unequally dispersed. The COVID-19 pandemic has further hampered the effectiveness of traditional service delivery models to provide hearing care. Digital health technologies are strong enablers of hearing care and can support health delivery models that are more sustainable. The convergence of advancing technology and mobile connectivity is enabling new ways of providing decentralized hearing services. Recently, an abundance of digital applications that offer hearing tests directly to the public has become available. A growing body of evidence has shown the ability of several approaches to provide accurate, accessible, and remote hearing assessment to consumers. Further effort is needed to promote greater accuracy across a variety of test platforms, improve sensitivity to ear disease, and scale up hearing rehabilitation, especially in LMICs.

A Review of Adult-Onset Hearing Loss: A Primer for Neurologists

Purpose of the Review

The goal of this review is to highlight current approaches to diagnosis and treatment for adult-onset hearing loss in patients likely to present to a neurologist's office. The review will discuss primary and secondary causes of acute and chronic hearing loss, and will discuss common situations that can be managed by a neurologist as well as situations that require immediate care and referral for further management by an otolaryngologist-head and neck surgeon.

Recent Findings

Hearing screening assessments using mobile applications and tablet devices are now available and can be integrated into many clinical practice settings, including in the evaluation of hearing concerns related to various neurological pathologies. For patients presenting with a sudden worsening in hearing, bedside evaluation, including with objective measures of hearing, can inform neurologists about diagnosis and subsequent management. For patients who present with gradual worsening in hearing, particularly those related to neurologic disorders, hearing care can be an important adjunct to ongoing neurologic care. More commonly encountered, age-related hearing loss is highly prevalent among older adults and may affect overall neurological assessment, including neurocognitive testing, as well as patient-provider communication, patient satisfaction, and care outcomes. Hearing loss is increasingly recognized as a potentially modifiable risk factor for dementia. Neurologists can support the hearing health of their patients through the routine use of communication strategies and by integrating simple, low-cost technology with their current clinical practices.

Summary

Both acute and chronic hearing loss can be a symptom of many conditions managed by neurologists. Few conditions are emergent, requiring immediate referral to and treatment by an otolaryngologist-head and neck surgeon. Despite the range of hearing interventions available, including hearing aids, over-the-counter devices, and aural rehabilitation, hearing loss is a common and under-treated chronic health condition. By promptly addressing a patient's hearing concerns, neurologists can improve patients' awareness of the deficit and support the overall importance of maintaining sensory health across the life course.

Development and Pilot Testing of Smartphone-Based Hearing Test Application

BACKGROUND

Identifying and treating hearing loss can help improve communication skills, which often leads to improved quality of life. Many people do not seek medical treatment and, therefore, go undiagnosed for an extended period before realizing they have hearing loss. This study presents a self-administered, low-cost, smartphone-based hearing test application (HearTest) to quantify the pure-tone hearing thresholds of a user. The HearTest application can be used with commercially available smartphone devices and an earphone with the mentioned specification.

METHODS

Air-conduction-based pure-tone audiometry for the smartphone application was designed and implemented to detect hearing thresholds using a traditional "10 dB down and 5 dB up" approach. Employed smartphone-earphone combination was calibrated with respect to a GSI-61 audiometer and insert earphone ER-3A to maintain clinical standards with the help of subjective testing on 20 normal-hearing (NH) participants.

RESULTS

Further subjective testing on 14 participants with NH and retesting on five participants showed that HearTest achieves high-accuracy audiogram within clinically acceptable limits (≤10 dB HL mean difference) when compared with the reference clinical audiometer. Hardware challenges and limitations in air-conduction-based hearing tests through smartphones and ways to improve their accuracy and reliability are discussed.

CONCLUSION

The proposed smartphone application provides a simple, affordable, and reliable means for people to learn more about their hearing health without needing access to a formal clinical facility.

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.

Evaluation of Accuracy and Reliability of a Mobile Screening Audiometer in Normal Hearing Adults

Quantifying hearing thresholds via mobile self-assessment audiometric applications has been demonstrated repeatedly with heterogenous results regarding the accuracy. One important limitation of several of these applications has been the lack of appropriate calibration of their core technical components (sound generator and headphones). The current study aimed at evaluating accuracy and reliability of a calibrated application (app) for pure-tone screening audiometry by self-assessment on a tablet computer: Audimatch app installed on Apple iPad 4 in combination with Sennheiser HDA-280 headphones. In a repeated-measures design audiometric thresholds collected by the app were compared to those obtained by standardized automated audiometry and additionally test-retest reliability was evaluated. Sixty-eight participants aged 19–65 years with normal hearing were tested in a sound-attenuating booth. An equivalence test revealed highly similar hearing thresholds for the app compared with standardized automated audiometry. A test-retest reliability analysis within each method showed a high correlation coefficient for the app (Spearman rank correlation: rho = 0.829) and for the automated audiometer (rho = 0.792). The results imply that the self-assessment of audiometric thresholds via a calibrated mobile device represents a valid and reliable alternative for stationary assessment of hearing loss thresholds, supporting the potential usability within the area of occupational health care.

Validity of hearing screening using hearTest smartphone-based audiometry: performance evaluation of different response modes

Objective: To investigate the validity of hearing screening with hearTest smartphone-based audiometry and to specify test duration addressing the two response modes and hearing loss criteria.Design: A diagnostic accuracy study comparing hearing screening with conventional audiometry.Study sample: Three hundred and forty individuals, aged between 5-92 years.Results: Of the 340 participants, 301 undertook all test procedures (273 adults and 28 children). Sensitivity and specificity were >90% for hearTest hearing screening to identify disabling hearing loss for both response modes with adults and children. We found similar sensitivity in identifying any level of hearing loss for both response modes in children, with specificity >80%, and for the self-test mode in adults. Low specificity was observed when identifying any level of hearing loss in adults using the test-operator mode. In adults, there was a significant difference between test duration for the test-operator and self-test modes.Conclusion: Hearing screening using hearTest smartphone-based audiometry is accurate for the identification of both disabling hearing loss and any level of hearing loss in adults and children in the self-test response mode. The test-operator mode is also an option for children; however, it does not provide good accuracy in identifying mild level of hearing loss in adults.

Evaluation of Hearing Thresholds by Using a Mobile Application in Children with Otitis Media with Effusion

Objective: Otitis media with effusion (OME) is the most common cause of hearing loss in children. Early diagnosis is important as hearing loss affects speech and language development in children. The aim of this study was to compare conventional audiometry with the Android mobile operating system application Hearing TestTM in the evaluation of hearing thresholds in children with OME and to determine the accuracy and reliability of the mobile application. Design and Study Sample: Fifty school-age children aged between 5 and 15 years with OME in at least 1 ear were included in the study. First, hearing thresholds were obtained by conventional audiometric methods and the degree of hearing loss was determined. Then, the hearing thresholds of the patients were measured using the smartphone-based Hearing TestTM application. The data were compared using Cohen’s kappa analysis. Results: OME was detected in 88 ears. There was no statistically significant correlation between the hearing threshold results obtained with the mobile phone and conventional audiometry at 500, 1,000, 2,000, and 4,000 Hz. Conclusion: The Android mobile phone application Hearing TestTM (version 1.1.3) is not an appropriate screening test to detect hearing loss in children with OME.

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.

Apps for Hearing Healthcare

This chapter provides a picture of the evolution of mobile applications (apps) for hearing health care (HHC) in terms of availability, variety, penetration, offered services, and target users. Special emphasis is given to newly developed methods that might assist audiologists and hearing professionals to get meaningful information and guidance for informed adoption of apps for themselves as well as for patients and their families. The chapter also shows how these novel methods can be used to characterize and compare a variety of apps across a wide range of services and target user groups. A representative sample of apps, assessed by using such a standardized framework, is analyzed to derive a multifaceted picture of apps for HHC. The chapter outlines and discusses emerging trends and needs in the area and highlights the open challenges as well as potential opportunities for professionals, researchers, developers, and stakeholders at large.

Accuracy of Smartphone Self-Hearing Test Applications Across Frequencies and Earphone Styles in Adults

PURPOSE

The purpose of this study is to evaluate smartphone-based self-hearing test applications (apps) for accuracy in threshold assessment and validity in screening for hearing loss across frequencies and earphone transducer styles.

METHOD

Twenty-two adult participants (10 = normal hearing; 12 = sensorineural hearing loss; n = 44 ears) underwent conventional audiometry and performed 6 self-administered hearing tests using two iPhone-based apps (App 1 = uHear [Version 2.0.2, Unitron]; App 2 = uHearingTest [Version 1.0.3, WooFu Tech, LLC.]) each with 3 different transducers (earbud earphones, supra-aural headphones, circumaural headphones). Hearing sensitivity results using the smartphone apps across frequencies and transducers were compared with conventional audiometry.

RESULTS

Differences in accuracy were revealed between the hearing test apps across frequencies and earphone styles. The uHear app using the iPhone standard EarPod earbud earphones was accurate to conventional thresholds (p > .002 with Bonferroni correction) at 1000, 2000, 4000, and 6000 Hz and found valid (81%-100% sensitivity, specificity, positive and negative predictive values) for screening mild or greater hearing loss (> 25 dB HL) at 500, 1000, 2000, 4000, and 6000 Hz. The uHearingTest app was accurate in threshold assessment and determined valid for screening mild or greater hearing loss (> 25 dB HL) using supra-aural headphones at 2000, 4000, and 8000 Hz.

CONCLUSIONS

Self-hearing test apps can be accurate in hearing threshold assessment and screening for mild or greater hearing loss (> 25 dB HL) when using appropriate transducers. To ensure accuracy, manufacturers should specify earphone model instructions to users of smartphone-based self-hearing test apps.

Automated Audiometry: A Review of the Implementation and Evaluation Methods

Objectives

Automated audiometry provides an opportunity to do audiometry when there is no direct access to a clinical audiologist. This approach will help to use hearing services and resources efficiently. The purpose of this study was to review studies related to automated audiometry by focusing on the implementation of an audiometer, the use of transducers and evaluation methods.

Methods

This review study was conducted in 2017. The papers related to the design and implementation of automated audiometry were searched in the following databases: Science Direct, Web of Science, PubMed, and Scopus. The time frame for the papers was between January 1, 2010 and August 31, 2017. Initially, 143 papers were found, and after screening, the number of papers was reduced to 16.

Results

The findings showed that the implementation methods were categorized into the use of software (7 papers), hardware (3 papers) and smartphones/tablets (6 papers). The used transducers were a variety of earphones and bone vibrators. Different evaluation methods were used to evaluate the accuracy and the reliability of the diagnoses. However, in most studies, no significant difference was found between automated and traditional audiometry.

Conclusions

It seems that automated audiometry produces the same results compared with traditional audiometry. However, the main advantages of this method; namely, saving costs and increased accessibility to hearing services, can lead to a faster diagnosis of hearing impairment, especially in poor areas.

Tablet-based tele-audiometry: Automated hearing screening for schoolchildren

Introduction

To assess the performance of a tablet-based tele-audiometry method for automated hearing screening of schoolchildren through a comparison of the results of various hearing screening approaches.

Methods

A total of 244 children were evaluated. Tablet-based screening results were compared with gold-standard pure-tone audiometry. Acoustic immittance measurements were also conducted. To pass the tablet-based screening, the children were required to respond to at least two out of three sounds for all the frequencies in each ear. Several hearing screening methods were analysed: exclusively tablet-based (with and without 500 Hz checked) and combined tests (series and parallel). The sensitivity, specificity, positive and negative predictive values and accuracy were calculated.

Results

A total of 9.43% of children presented with mild to moderate conductive hearing loss (unilateral or bilateral). Diagnostic values varied among the different hearing screening approaches that were evaluated: sensitivities ranged from 60 to 95%, specificities ranged from 44 to 91%, positive predictive values ranged from 15 to 44%, negative predictive values ranged from 95 to 99%, accuracy values ranged from 49 to 88%, and area under curve values ranged from 0.690 to 0.883. Regarding diagnostic values, the highest results were found for the tablet-based screening method and for the series approach.

Discussion

Compared with the results obtained by conventional audiometry and considering the diagnostic values of the different hearing screening approaches, the highest diagnostic values were generally obtained using the automated hearing screening method (including 500 Hz). Thus, this application, which was developed for the tablet computer, was shown to be a valuable hearing screening tool for use with schoolchildren. Therefore, we suggest that this hearing screening protocol has the potential to improve asynchronous tele-audiology service delivery.

Screening Methods for Age-Related Hearing Loss in Older Patients with Cancer: A Review of the Literature

As people grow older, they may experience loss in hearing sensitivity. Age-related hearing loss may negatively affect the patient’s quality of life as it may lead to social isolation. In older patients with cancer, hearing loss can seriously interfere with the patient’s ability to deal properly with all aspects of their disease, and may have a cumulative effect on their already decreased quality of life. Therefore, the proper screening of those conditions is essential in order to optimise the patient’s comfort during and after treatment. This review article aims at providing a concise image of the nature of age-related hearing loss, and provides an overview of the screening methods that could be used in older patients with cancer.

eHealth and the hearing aid adult patient journey: a state-of-the-art review

The number and variety of eHealth services for adults and older adults who use hearing aids (HAs) are growing rapidly. This area holds promise to increase cost-efficiency, enable better access to care, and improve patient outcomes and satisfaction. Despite the increasing interest in this field, an up-to-date picture of recent research in the area of eHealth for adults with HAs is lacking. In this state-of-the-art review we assessed the literature from the past decade about eHealth use in the HA adult patient journey. Systematic searches were conducted in CINAHL, PubMed, Scopus, and Web of Science. A total of 34 peer-reviewed empirical records were identified from the searches and from the reference lists of searched records. Records were characterized based on: eHealth platform (i.e.: offline, Internet-based, or mobile-based), service [i.e.: education and information, screening and assessment, hearing rehabilitation, or general (tele-audiology)], and phase of the patient journey (i.e.: pre-fitting, fitting, or post-fitting). The review highlighted a growing interest in the field, as revealed by an increasing trend over the search period, from 2 records in 2009-2010 up to 17 records in 2015-2016. Internet-based platforms were the most frequently used (present in more than half of the included records), with a stable trend in the period. About one-third of the records introduced services over offline platforms, whereas mobile-based platforms were used only in 6 out of 34 records, suggesting that the clinical uptake of mobile services is still limited compared to more mature offline and Internet-based platforms. Most of the eHealth services observed were related to the areas of education and information (42.5%) and hearing rehabilitation (40.4%), whereas 10.7% were related to screening and assessment, and 6.4% to general tele-audiology services. Many services covered different phases of the patient journey, especially the fitting and post-fitting phases. Overall, this review showed that the field of eHealth in the context of HA rehabilitation in adults has grown in the recent past. Research is still needed to increase the uptake and efficacy of eHealth in clinical practice, especially in terms of technology developments, technical and clinical validation, and optimization of strategies for service delivery.

Mobile Hearing Testing Applications and the Diagnosis of Sudden Sensorineural Hearing Loss: A Cautionary Tale

OBJECTIVE

Mobile hearing applications (apps) are available for hearing testing, personal sound amplification, as well as hearing aid modulation. Hearing testing apps are gaining popularity, especially in resource-limited settings. The reliability of mobile hearing testing apps, however, is not well characterized.

PATIENTS/INTERVENTIONS

A case study of a single patient with a complaint of sudden hearing loss presenting to a tertiary-care hospital.

MAIN OUTCOME MEASURE

Comparison of a mobile hearing testing app results with standard audiogram.

RESULTS

A commercially available mobile hearing testing app was used after hours to determine if a patient's hearing complaints were consistent with sudden sensorineural hearing loss. The hearing app produced a rudimentary audiogram that was consistent with unilateral SSNHL. Given contraindications to oral treatment, preparations for possible intratympanic dexamethasone after a full audiometric evaluation were completed. Confirmatory audiogram the following day demonstrated normal hearing without evidence of hearing loss. Steroid treatment was aborted and appropriate counseling provided.

CONCLUSION

While mobile hearing testing apps offer improved access to hearing screening in resource-limited settings, caution must be exercised when interpreting data and making clinical decisions based upon results. The role of professional audiologists remains critical. Further testing and validation of specific apps is required.

Is there a clinical application for tablet-based automated audiometry in children?

INTRODUCTION

Recent research supports the clinical use of automated audiometry for pediatric hearing screenings. However, very few studies have tested whether tablet-based automated audiometry can offer a valid alternative to traditional manual audiometry for estimation of hearing thresholds in children. This study examined the validity and efficiency of automated audiometry in school-aged children.

METHODS

Hearing thresholds for 0.5, 1, 2, 4, 6, and 8 kHz were collected in 32 children ages 6-12 years using standard audiometry and tablet-based automated audiometry in a soundproof booth. Test administration time, test preference, and medical history were also collected.

RESULTS

Results exhibited that the majority (67%) of threshold differences between automated and standard were within the clinically acceptable range (10 dB). The threshold difference between the two tests showed that automated audiometry thresholds were higher by 12 dB in 6-year-olds, 7 dB in 7- to 9-year-olds, and 3 dB in 10- to 12-year-olds. In addition, test administration times were similar, such that standard audiometry took an average of 12.3 min and automated audiometry took 11.9 min.

CONCLUSIONS

These results support the use of tablet-based automated audiometry in children from ages 7-12 years. However, the results suggest that the clinical use of at least some types of tablet-based automated audiometry may not be feasible in children 6 years of age.

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

BACKGROUND

Hearing screening tests based on pure-tone audiometry may be conducted on mobile devices, provided that the devices are specially calibrated for the purpose. Calibration consists of determining the reference sound level and can be performed in relation to the hearing threshold of normal-hearing persons. In the case of devices provided by the manufacturer, together with bundled headphones, the reference sound level can be calculated once for all devices of the same model.

OBJECTIVE

This study aimed to compare the hearing threshold measured by a mobile device that was calibrated using a model-specific, biologically determined reference sound level with the hearing threshold obtained in pure-tone audiometry.

METHODS

Trial participants were recruited offline using face-to-face prompting from among Otolaryngology Clinic patients, who own Android-based mobile devices with bundled headphones. The hearing threshold was obtained on a mobile device by means of an open access app, Hearing Test, with incorporated model-specific reference sound levels. These reference sound levels were previously determined in uncontrolled conditions in relation to the hearing threshold of normal-hearing persons. An audiologist-assisted self-measurement was conducted by the participants in a sound booth, and it involved determining the lowest audible sound generated by the device within the frequency range of 250 Hz to 8 kHz. The results were compared with pure-tone audiometry.

RESULTS

A total of 70 subjects, 34 men and 36 women, aged 18-71 years (mean 36, standard deviation [SD] 11) participated in the trial. The hearing threshold obtained on mobile devices was significantly different from the one determined by pure-tone audiometry with a mean difference of 2.6 dB (95% CI 2.0-3.1) and SD of 8.3 dB (95% CI 7.9-8.7). The number of differences not greater than 10 dB reached 89% (95% CI 88-91), whereas the mean absolute difference was obtained at 6.5 dB (95% CI 6.2-6.9). Sensitivity and specificity for a mobile-based screening method were calculated at 98% (95% CI 93-100.0) and 79% (95% CI 71-87), respectively.

CONCLUSIONS

The method of hearing self-test carried out on mobile devices with bundled headphones demonstrates high compatibility with pure-tone audiometry, which confirms its potential application in hearing monitoring, screening tests, or epidemiological examinations on a large scale.

Evaluation of the Hearing Test Pro Application as a Screening Tool for Hearing Loss Assessment

Background:

Disabling hearing loss is considered a significant health problem globally with high incidence in developing countries. In Africa, different studies have shown that one in five Africans uses smartphones. This dispositive can be used to screen hearing loss.

Aim:

The study aims to appraise the effectiveness of Hearing Test Pro, an Android-based application, as a screening tool for hearing loss.

Methods:

This is a prospective study developed in the Federal Teaching Hospital, Ido-Ekiti, Ekiti State, Nigeria, between September and December 2018. The study was approved by the institutional ethics committee. Consent of adult android users was conveniently obtained for the study. A regular audiometric test with Amplivox 260 was done after otoscopy (to exclude other ear pathology). The results were compared with the test developed by an android Hearing Test Pro app. A threshold of >40 decibels was used to determine any evidence of hearing loss at the specific frequency of 250–8000 Hz. P < 0.05 was considered statistically significant.

Results:

Three hundred and sixty ears of 180 patients were evaluated, of which 100 were male and 80 were female. The male-to-female ratio was 1.25:1. At lower frequency, a statistical difference between classical pure-tone thresholds recorded with the audiometer and the android phone was documented. However, this difference was not noted at higher frequencies.

Conclusion:

The Hearing Test Pro app effectively distinguishes between high-frequency hearing loss and thus can be useful as part of the hearing loss screening programs.

Utilising an innovative digital software to grade pre-clinical crown preparation exercise

BACKGROUND

Accurate assessment of dental students' pre-clinical work is the most critical component of the dental education process. Thus, this study came to investigate the effectiveness of using technology in students' pre-clinical work evaluation; by comparing grades generated from a digital assessment software of a prepared tooth and a traditional visual inspection carried out by four calibrated faculty members.

METHODS

Ninety-six teeth were prepared for a ceramo-metal crown by fourth year dental students. The four examiners and the digital grading software evaluated independently each preparation once. A random sample of 20 preparations were graded twice to assess intra-rater reliability. Inter-class correlation (ICC) was used to measure agreement among the four examiners, and between the examiners and the digital grading software. Paired student t-test was used to assess the accuracy of grades generated from visual inspection when compared to the digital grading system.

RESULTS

Intra-rater reliability for examiners 1 and 2 were 0.73 and 0.78 and for the digital grading system was 0.99. The inter-rater reliability among the four examiners was very good, ICC of 0.76. However, the agreement between scores produced by the examiners and the digital system were mostly in the low to moderate range. The paired t-test demonstrated statistically significant differences between each examiner and the digital grading by 6-25 grades.

CONCLUSIONS

This study demonstrates that the digital grading system used in this study can reliably scan and compare students' tooth preparations to a known gold standard. Results of this study suggests that using digital grading will preclude the variability and the subjectivity that usually result from the traditional visual inspection grading.

The ALFA4Hearing Model (At-a-Glance Labeling for Features of Apps for Hearing Health Care) to Characterize Mobile Apps for Hearing Health Care

PURPOSE

The aim of the study was to analyze, by using the ALFA4Hearing model (At-a-Glance Labeling for Features of Apps for Hearing Health Care), a sample of apps over a wide range of services in the hearing health care (HHC) domain in order to take a first picture of the current scenario of apps for HHC.

METHOD

We tested 120 apps, and we characterized them by using the ALFA4Hearing model, which includes 29 features in 5 components (Promoters, Services, Implementation, Users, and Descriptive Information). We analyzed (a) the distribution of the 29 features in the sample, (b) the relationship between the Implementation features and the Services provided by the apps, and (c) the distribution of the 29 features in apps for professional use.

RESULTS

The analysis of our sample of apps by means of the ALFA4Hearing model highlighted interesting trends and emerging challenges. Also, results suggested many potential opportunities for research and clinical practice, such as greater involvement of stakeholders, improved evidence base, higher technical quality, and usability.

CONCLUSIONS

The ALFA4Hearing model is able to represent, at a glance, a large amount of information about apps for HHC, highlighting trends and challenges. It might be useful to HHC professionals as a basis for app characterization and informed decision making.

Validated Smartphone-Based Apps for Ear and Hearing Assessments: A Review

BACKGROUND

An estimated 360 million people have a disabling hearing impairment globally, the vast majority of whom live in low- and middle-income countries (LMICs). Early identification through screening is important to negate the negative effects of untreated hearing impairment. Substantial barriers exist in screening for hearing impairment in LMICs, such as the requirement for skilled hearing health care professionals and prohibitively expensive specialist equipment to measure hearing. These challenges may be overcome through utilization of increasingly available smartphone app technologies for ear and hearing assessments that are easy to use by unskilled professionals.

OBJECTIVE

Our objective was to identify and compare available apps for ear and hearing assessments and consider the incorporation of such apps into hearing screening programs.

METHODS

In July 2015, the commercial app stores Google Play and Apple App Store were searched to identify apps for ear and hearing assessments. Thereafter, six databases (EMBASE, MEDLINE, Global Health, Web of Science, CINAHL, and mHealth Evidence) were searched to assess which of the apps identified in the commercial review had been validated against gold standard measures. A comparison was made between validated apps.

RESULTS

App store search queries returned 30 apps that could be used for ear and hearing assessments, the majority of which are for performing audiometry. The literature search identified 11 eligible validity studies that examined 6 different apps. uHear, an app for self-administered audiometry, was validated in the highest number of peer reviewed studies against gold standard pure tone audiometry (n=5). However, the accuracy of uHear varied across these studies.

CONCLUSIONS

Very few of the available apps have been validated in peer-reviewed studies. Of the apps that have been validated, further independent research is required to fully understand their accuracy at detecting ear and hearing conditions.

Hearing Tests on Mobile Devices: Evaluation of the Reference Sound Level by Means of Biological Calibration

Background

Hearing tests carried out in home setting by means of mobile devices require previous calibration of the reference sound level. Mobile devices with bundled headphones create a possibility of applying the predefined level for a particular model as an alternative to calibrating each device separately.

Objective

The objective of this study was to determine the reference sound level for sets composed of a mobile device and bundled headphones.

Methods

Reference sound levels for Android-based mobile devices were determined using an open access mobile phone app by means of biological calibration, that is, in relation to the normal-hearing threshold. The examinations were conducted in 2 groups: an uncontrolled and a controlled one. In the uncontrolled group, the fully automated self-measurements were carried out in home conditions by 18- to 35-year-old subjects, without prior hearing problems, recruited online. Calibration was conducted as a preliminary step in preparation for further examination. In the controlled group, audiologist-assisted examinations were performed in a sound booth, on normal-hearing subjects verified through pure-tone audiometry, recruited offline from among the workers and patients of the clinic. In both the groups, the reference sound levels were determined on a subject’s mobile device using the Bekesy audiometry. The reference sound levels were compared between the groups. Intramodel and intermodel analyses were carried out as well.

Results

In the uncontrolled group, 8988 calibrations were conducted on 8620 different devices representing 2040 models. In the controlled group, 158 calibrations (test and retest) were conducted on 79 devices representing 50 models. Result analysis was performed for 10 most frequently used models in both the groups. The difference in reference sound levels between uncontrolled and controlled groups was 1.50 dB (SD 4.42). The mean SD of the reference sound level determined for devices within the same model was 4.03 dB (95% CI 3.93-4.11). Statistically significant differences were found across models.

Conclusions

Reference sound levels determined in the uncontrolled group are comparable to the values obtained in the controlled group. This validates the use of biological calibration in the uncontrolled group for determining the predefined reference sound level for new devices. Moreover, due to a relatively small deviation of the reference sound level for devices of the same model, it is feasible to conduct hearing screening on devices calibrated with the predefined reference sound level.

The Accuracy of IOS Device-based uHear as a Screening Tool for Hearing Loss: A Preliminary Study From the Middle East

OBJECTIVES

To determine and explore the potential use of uHear as a screening test for determining hearing disability by evaluating its accuracy in a clinical setting and a soundproof booth when compared to the gold standard conventional audiometry.  .

METHODS

Seventy Sultan Qaboos University students above the age of 17 years who had normal hearing were recruited for the study. They underwent a hearing test using conventional audiometry in a soundproof room, a self-administered uHear evaluation in a side room resembling a clinic setting, and a self-administered uHear test in a soundproof booth. The mean pure tone average (PTA) of thresholds at 500, 1000, 2000 and 4000 Hz for all the three test modalities was calculated, compared, and analyzed statistically.  .

RESULTS

There were 36 male and 34 female students in the study. The PTA with conventional audiometry ranged from 1 to 21 dB across left and right ears. The PTA using uHear in the side room for the same participants was 25 dB in the right ear and 28 dB in the left ear (3-54 dB across all ears). The PTA for uHear in the soundproof booth was 18 dB and 17 dB (1-43 dB) in the right and left ears, respectively. Twenty-three percent of participants were reported to have a mild hearing impairment (PTA > 25 dB) using the soundproof uHear test, and this number was 64% for the same test in the side room. For the same group, only 3% of participants were reported to have a moderate hearing impairment (PTA > 40 dB) using the uHear test in a soundproof booth, and 13% in the side room.  .

CONCLUSION

uHear in any setting lacks specificity in the range of normal hearing and is highly unreliable in giving the exact hearing threshold in clinical settings. However, there is a potential for the use of uHear if it is used to rule out moderate hearing loss, even in a clinical setting, as exemplified by our study. This method needs standardization through further research.

The use of telehealth services to facilitate audiological management for children: A scoping review and content analysis

Approximately 32 million children globally present with disabling hearing loss. Despite evidence describing the negative consequences of hearing loss, there is still a lack of hearing screening programmes in South Africa. Audiologists have been exploring the use of information and communication technologies (tele-audiology) to provide services to children and it is currently being evaluated to determine its feasibility.

Aims

We aim to describe tele-audiology services conducted to facilitate audiological management for children in both the rural and urban context and to determine the strengths, challenges and clinical implications of such services.

Methods

A scoping review was conducted by searching for peer-reviewed publications from five databases. Inclusion criteria and search strategies were outlined.

Results

Of the 23 studies that met the inclusion criteria, reliability of automated testing was comparable to conventional testing; however, these studies were based primarily on screening programmes. Eight (35%) of the 23 papers were concordance studies evaluating feasibility and validity of tele-audiology systems when compared with conventional testing, while one study (4%) evaluated a tele-audiology service. A further four studies (17%) evaluated the feasibility of introducing telehealth methods to evaluate middle ear pathology. Tele-auditory brainstem response was investigated in three studies (13%) and another five (22%) used smartphone and/or iPad technology to screen hearing. Only two studies (9%) evaluated the feasibility of providing intervention through telehealth methods. All included studies demonstrated improved access to and coverage of rural areas. Services such as video otoscopy and synchronous (online) hearing testing in remote areas were successfully implemented. Challenges included lack of diagnostic studies, inadequate training of staff and the need to standardize protocols and procedures in order to ensure that tele-audiology services are provided in a standardized and valid manner.

Conclusion

Tele-audiology services are feasible and can be useful in identifying auditory pathology for children in rural and remote areas.

Mobile Technology for the Practice of Pathology

Recently, several technological advances have been introduced to mobile phones leading some people to refer to them as "smartphones." These changes have led to widespread consumer adoption. A similar adoption has occurred within the medical field and this revolution is changing the practice of medicine, including pathology. Several mobile applications have been published for dermatology, orthopedics, ophthalmology, neurosurgery, and clinical pathology. The applications are wide ranging, including mobile technology to increase patient engagement, self-monitoring by patients, clinical algorithm calculation, facilitation between experts to resource-poor environments. These advances have been received with mixed reviews. For anatomic pathology, mobile technology applications can be broken into 4 broad categories: (a) educational uses, (b) microscope with mobile phone, (c) mobile phone as microscope/acquisition device, and (d) miscellaneous. Using a mobile phone as an acquisition device paired with a microscope seems to be the most interesting current application because of the need for expert consultation with resource-poor environments. However, several emerging uses for mobile technology may become more prominent as the technology matures including image analysis, alternative light sources, and increased opportunities for clinician and patient engagement. The flexibility represented by mobile technology represents a burgeoning field in pathology informatics.

Self-administered hearing loss screening using an interactive, tablet play audiometer with ear bud headphones

BACKGROUND AND OBJECTIVE

The timely diagnosis and treatment of acquired hearing loss in the pediatric population has significant implications for a child's development. Audiological assessment in children, however, carries both technological and logistical challenges. Typically, specialized methods (such as play audiometry) are required to maintain the child's attention and can be resource intensive. These challenges were previously addressed by a novel, calibrated, interactive play audiometer for Apple(®) iOS(®) called "ShoeBOX Audiometry". This device has potential applications for deployment in environments where traditional clinical audiometry is either unavailable or impractical. The objective of this study was to assess the screening capability of the tablet audiometer in an uncontrolled environment using consumer ear-bud headphones.

METHODS

Consecutive patients presenting to the Audiology Clinic at the Children's Hospital of Eastern Ontario (ages 4 and older) were recruited. Participants' hearing was evaluted using the tablet audiometer calibrated to Apple(®) In-Ear headphones. The warble tone thresholds obtained were compared to gold standard measurements taken with a traditional clinical audiometer inside a soundbooth.

RESULTS

80 patients were enrolled. The majority of participants were capable of completing an audiologic assessment using the tablet computer. Due to ambient noise levels outside a soundbooth, thresholds obtained at 500Hz were not consistent with traditional audiometry. Excluding 500Hz threholds, the tablet audiometer demonstrated strong negative predictive value (89.7%) as well as strong sensitivity (91.2%) for hearing loss.

CONCLUSION

Thresholds obtained in an uncontrolled setting are not reflective of diagnostic thresholds due to the uncalibrated nature of the headphones and variability of the setting without a booth. Nevertheless, the tablet audiometer proved to be both a valid and sensitive instrument for unsupervised screening of warble-tone thresholds in children.

Technology for hearing loss--as We Know it, and as We Dream it

PURPOSE

Worldwide demand for accessible hearing health technology continues to increase while the numbers of hearing healthcare specialists are grossly inadequate to meet this demand. Proliferation of innovative technology and the advent of greater access to global connectivity are providing an opportunity to identify and harness new resources that may change current audiological service delivery methods to maximize access, efficiency and impact.

METHODS

By searching through the most current literature and engaging in discussions with industry experts, it is possible to identify avenues that could increase services to those who have hearing loss with innovative healthcare technology. This article aims to review the current state as well as future trends of hearing health technology by addressing: Technology as We Know it; and Technology as We Dream it.

RESULTS

Some of the newer technologies we have recently witnessed include: micro processors; personalized computing devices (e.g. smartphones); web-based applications; an expanding clinical repertoire with integrated test equipment; and globalization of telecommunications that opens the door to telehealth; and self-fitting of hearing aids. Yet, innovation continues scaffolding on recent successes with innovations for hearing healthcare expected to increase into the future.

CONCLUSION

As technology and connectivity continue to evolve so should the practice of audiology adapt to the global needs by capitalizing on these advances to optimize service delivery access and sustainability.

IMPLICATIONS FOR REHABILITATION

Capital investment in equipment will be dramatically reduced with smaller, lighter, less costly and more portable equipment. Individuals who live in remote regions with little or no hearing healthcare access can undergo valid assessments by a professional via telehealth. Web-based applications allow clinicians to expand their repertoire and reach of services.