Mobile Audiometry for Use in Ototoxicity Monitoring Programs: A Scoping Review

Pierre W. C. Yim; Zee Hui Lim

doi:10.7874/jao.2024.00815

J Audiol Otol > Volume 29(3); 2025 > Article

Yim and Lim: Mobile Audiometry for Use in Ototoxicity Monitoring Programs: A Scoping Review

Review

Journal of Audiology and Otology 2025;29(3):166-180.

Published online: July 18, 2025

DOI: https://doi.org/10.7874/jao.2024.00815

Mobile Audiometry for Use in Ototoxicity Monitoring Programs: A Scoping Review

Pierre W. C. Yim¹

, Zee Hui Lim²

¹Duke-NUS Medical School, Singapore

²Department of Otolaryngology-Head & Neck Surgery, National University Hospital, Singapore

Address for correspondence (Current affiliation) Pierre W. C. Yim, MD Department of Medicine, National University Hospital, 5 Lower Kent Ridge Road, Singapore 119074 Tel +65 67727728 E-mail pierreyim@gmail.com

Received December 29, 2024 Revised April 27, 2025 Accepted May 17, 2025

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Ototoxicity monitoring programs (OMPs) for cisplatin-induced hearing loss have not been widely adopted in clinical practice for various reasons. Mobile audiometry (MA) offers cost and convenience advantages over conventional pure-tone audiometry (CA) and it is currently used in hearing screening. However, there is no consensus on whether MA can replace CA for measuring hearing thresholds in OMPs. This scoping review examines the challenges of OMPs and evaluates the diagnostic accuracy of MA for hearing thresholds. A comprehensive search was conducted in four databases from their inception to December 2024. Data on study characteristics, reported OMP challenges, MA specifications, test settings, and performance measures were extracted. Nine studies on OMP challenges were reviewed. Identified barriers were inconsistent referrals, resource constraints, low awareness of ototoxicity monitoring, and patient-related factors. Twenty-three studies reporting on three portable audiometers, and 14 app-based hearing tests were evaluated for the diagnostic accuracy of MA for hearing thresholds. Only two studies involved testing at extended high frequencies. Studies used measures including MA-CA threshold differences, sensitivity/specificity, and test-retest reliability. App-based MA represents an accessible and scalable solution to the resource constraints faced by OMPs. However, its diagnostic accuracy remains uncertain given the substantial methodological variability across studies. OMPs using MAs should consider clinically validated modalities.

Keywords: Ototoxicity · Hearing loss · Hearing tests · Mobile applications · Otoxicity monitoring.

Introduction

Ototoxicity-induced hearing loss (HL) is a common adverse event of cisplatin chemotherapy [1]. It is typically sensorineural [2] and affects higher frequencies above 8 kHz first [3]. Though initially asymptomatic, cumulative cisplatin exposure may eventually cause HL at speech frequencies [4], compromising communication and quality of life [5]. Since cisplatin is effective against many tumours, early HL detection and management are more practical than avoiding its use [6]. Early HL detection lets clinicians and patients weigh the risk of permanent HL against continued cisplatin use [7]. Ototoxicity monitoring programs (OMPs) are hospital-based programs that prospectively monitor hearing thresholds for patients on ototoxic medications [8] using conventional pure-tone audiometry (CA) with extended high frequencies (EHF). Beyond early HL detection, OMPs also longitudinally monitor patients to fit them with hearing devices at the earliest opportunity, or as soon as the need arises [9]. Unfortunately, OMPs are not well adopted in clinical practice. Reported barriers include patient inconvenience, logistical challenges, and costly infrastructure [9]. It is not known whether other OMPs worldwide face similar barriers.

Mobile audiometry (MA) is an alternative to CA. MA leverages on portable audiometers and mobile applications to assess hearing levels [10] and can be used in non-sound-treated test settings [11]. Mobile applications (henceforth referred to as “app-based MA”) have shown good sensitivity and specificity for hearing screening (binary outcomes of pass or fail) [12] while providing cost savings and convenience over CA. It is widely used for workplace screening and hearing screening in rural areas [13]. However, evidence supporting the use of MA for diagnostic threshold testing remains inconclusive, with meta-analyses both endorsing [14] and opposing its use [15]. Hence, the authors conducted this scoping review for two reasons: first, to identify the challenges faced by OMPs for patients on cisplatin; and second, to evaluate the diagnostic accuracy of MA for hearing thresholds.

Materials and Methods

Protocol

This scoping review was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for Scoping Reviews (PRISMA-ScR) guidelines [16]. We included full-length articles published in peer-reviewed journals including primary and observational studies. Case reports, systematic reviews, meta-analyses, opinion pieces, theses, dissertations, and study protocols were excluded.

Search strategy

The authors searched three electronic databases (PubMed, Scopus, and Embase) and one search engine (Google Scholar) for articles published from database inception through December 2024 using the search terms listed in Table 1. Our search strategy included Medical Subject Headings (MeSH) terms and free-text words related to two concepts: 1) challenges facing OMPs for patients on cisplatin and 2) accuracy of MA for diagnostic hearing thresholds.

Study selection

Each investigator (P. W. C. Y. and L. Z. H.) manually performed screening of the titles and abstracts to select eligible articles. The full text of these articles were then examined for inclusion. All disputes regarding article selection were resolved through discussion. The study selection process is documented in a PRISMA diagram (Fig. 1).

Data extraction

Both authors (P. W. C. Y. and L. Z. H.) autonomously extracted pertinent data from included articles into a standardized data charting form. The data extracted included authors, publication year, title of study, study characteristics, reported OMP challenges, MA specifications (equipment type, calibration procedures, frequency ranges), test setting, and performance measures (sensitivity, specificity, and accuracy compared to CA).

Results

Characteristics of studies on OMP challenges

Database searches yielded a total of 379 articles, of which 34 full text were retrieved. There were nine studies included in the final review [9,17-24]. Publication years spanned 2018 to 2024. There were four mixed-methods studies [9,18,22,24], three qualitative studies [20,21,23] and two retrospective studies [17,19]. Study population included healthcare workers (physicians, audiologists, and nurses) and cancer patients on cisplatin chemotherapy. Four studies were from the United States (US) [9,18,19,22], three from South Africa [21,23,24], and two from Europe [17,20]. Table 2 shows the summary of the included studies.

Inconsistent referrals

Inconsistent referrals was reported as the key barrier by seven studies [9,17,20-24]. These studies noted the lack of standardized referral systems to OMPs, with patients either self-referring upon experiencing HL or being referred postchemotherapy at oncologists’ discretion.

Resource constraints

Insufficient sound booths and manpower to support OMPs was reported by four studies [9,11,21,24]. Such resource constraints reduced appointment slots for OMPs and necessitated testing in non-sound-treated test setting (such as clinic waiting area). It also made it difficult to coordinate OMPs on the same day as patients’ chemotherapy appointments [24], leading to increased travel, greater fatigue, and reduced compliance to OMP. Some centers lacking referral pathways allocate the responsibility of screening and enrolment of patients for OMP to audiologists, adding on to their regular workload [9].

Low awareness of ototoxicity monitoring

Despite the availability of ototoxicity monitoring guidelines, six studies [9,11,17,20,21,23] reported low awareness leading to inconsistent implementation. Two centers were unsure of monitoring protocols and testing procedures [17,20]. In some cancer centers, staff awareness of reason and purpose ototoxicity monitoring was low [24].

Patient-related factors

Fatigue, scheduling constraints and financial matters influenced patient participation in OMPs [9,18-20,23,24]. In chemotherapy centers without co-located audiology departments, patients reported increased fatigue from travel and difficulty keeping up with OMP appointments [9,24]. Two studies reported that lack of insurance coverage and patients with non-head and neck cancer were associated with lower rates of monitoring [17,19].

Characteristics of studies on MA

Initial database searches yielded only two articles on MA use in OMPs. The search was expanded to include MA in general, yielding a total of 501 articles, of which 61 full text articles were retrieved. Twenty-three studies relevant to MA were included in the final analysis to evaluate its diagnostic accuracy for hearing thresholds [25-47]. Eight studies were from the US [26,31,39,40,43,44,47], three from Canada [27,28,35], two from India [37,45] and South Africa [38,41], and one from each of these countries: Australia [33], Denmark [48], Indonesia [46], South Korea [30], Singapore [36], the United Kingdom (UK) [42], and Uganda [25]. Publication years spanned 2013 to 2024. Table 3 shows the summary of the included studies.

Reference test

CA performed manually using clinical audiometers and calibrated transducers in sound booths is the gold standard for diagnosing HL type and severity [42,47]. CA is the reference test for comparison with MA in all but one study. The sole exception was the KUDUwave Type 2 Clinical Audiometer (MoyoDotNet, Johannesburg; IEC 60645-1/2 compliant) [41], which meets international standards for diagnostic audiometry.

Types of MA

Two device types were used for MA. The first comprised portable audiometers (n=3 studies), specifically the OtoID [47], KUDUwave 5000 [33], and KUDUwave Prime [46].

App-based hearing tests (n=20 studies) formed the second device type. iOS-compatible applications included SHOEBOX [26-28,37,39,40], EarTrumpet [27,31,44], Mimi [36,49], Easy Hearing Test [42], Hearing Test and Ear Age Test [42], Audiogram Mobile [44], and Care 4 Ear [30]. Android-compatible applications included H3 Hearing Test [45], Wulira [48], R-App [48], and hearTest [32,38,41], while Eartone Hearing Test [42], Hearing Test [42], and Hearing Test with Audiogram [44] were compatible with both Android and iOS. Etymotic Home Hearing Test ran on Windows OS via touchscreen computer tablet [43].

Test settings for MA

Test settings varied across studies. The majority conducted MA outside sound booths, with seven studies not specifying any ambient noise monitoring measures [28,36,37,41,42,45,49]. Of the eight studies that measured or monitored ambient noise levels [26,30,33,35,44,46-48], two implemented noise control by pausing the test when ambient noise exceeded 40 dB [30], and when broadband noise exceeded 70 dB SPL [47]. Four studies performed MA exclusively inside sound booths [25,27,32,38]. One of these studies introduced white noise in the sound booth, and implemented placement of circumaural muffs over subjects’ ears for “passive noise cancellation” during hearing testing through audiometric insert earphones [27]. Two studies conducted MA in both settings without noise monitoring [31,42], while one study did not report the test environment [40].

Transducers for MA

A variety of transducers were utilized for air conduction testing. Some studies used more than one transducer. Audiometric headphones were used in nine studies [26,28,35,37-39,45,47,48]. Audiometric insert earphones were used in three studies [27,28,43]. Proprietary commercial headphones and earphones (non-audiometric headphones and earphones typically bundled with mobile phones and available for sale to consumers) were used in three studies [30,31,49]. Non-proprietary commercial headphones and earphones (non-audiometric headphones and earphones available for sale to consumers) were used in four studies [36,40,42,44]. One study reported using “standard headphone” without specifying the model and type [25].

Transducer placement for MA

Transducer placement was performed by researchers in four studies [33,41-43], by subjects in six studies [28,31,45,47-49], and not specified in 13 studies [25-27,30,32,35-40,44,46]. All MA hearing tests were automated.

Intensity range for MA

The intensity range of MA hearing tests was not indicated in 13 studies. Even among studies using the same MA, the reported intensity ranges varied. For instance, SHOEBOX with TDH-39 supra-aural audiometric headphones had lower and upper limits set to 15 and 90 dB HL in one study [26], while another study using the same MA with ER3A audiometric insert earphones and TDH-50 supra-aural headphones reported limits of 10 and 90 dB HL [28]. Another example would be hearTest app. One study using Sennheiser HD 202 II supra-aural audiometric headphones as transducer tested at ≥10 dB HL [32], while another study using Sennheiser 280 Pro supra-aural commercial headphones as transducer tested at 10–90 dB HL for 2 and 4 kHz and 10–80 dB HL for 8 kHz [41]. When the hearTest app was used for EHF testing with Sennheiser HDA 300 circumaural audiometric headphones and Sennheiser HDA 200 circumaural audiometric headphones, the intensity ranges were specified as follows: from 10 dB up to 75 dB HL at 8 kHz, up to 70 dB HL at 10 kHz, up to 75 dB HL at 12.5 kHz, and up to 65 dB HL at 16 kHz [38]. In some studies using other MA hearing tests, only the upper intensity limits were provided. For example, R-App, when used with RadioEar DD450 supra-aural audiometric headphones, had a limit of <80 dB HL [48], while the Etymotic Home Hearing Test with ER-3 insert earphones had a limit of ≤85 dB HL [43]. Mimi, when used with Apple EarPods proprietary commercial earphones, had a maximum measurement of 90 dB HL [49], but when paired with Baseus Encok D02Pro non-proprietary commercial headphones, the limit was reduced to 70 dB HL at 4 kHz (other frequencies not specified) [36]. Finally, OtoID used with Sennheiser HDA200 circumaural audiometric headphones was reported to have an intensity range of -10 to 105 dB SPL (not dB HL) .

Frequency range for MA

The frequencies tested in MA varied widely. Several studies assessed the standard pure-tone audiometry (PTA) frequencies (250 Hz, 500 Hz, 1 kHz, 2 kHz, 4 kHz, 8 kHz) [28,30,33,36,39,40,44], with some including inter-octave frequencies [31,42,46,48]. Others tested at fewer than the standard frequencies [25,26,32,37,41,43,49]. Two studies excluded 250 Hz but added inter-octave 6 kHz [27,35,45]. One study tested at both the standard frequencies and EHFs (10, 12.5, 16, and 20 kHz) [47], while another assessed only EHFs (8, 10, 12.5, and 16 kHz) without standard frequencies [38].

Calibration for MA

Eight studies did not report any calibration done [25,30,31,33,35,36,40,45]. One study reported utilizing a calibrated sound card in their MA [43]. Among the studies that reported [26-28,32,37-39,41,42,44,46-49], methodological approaches varied considerably.

Results from statistical analysis

In the 23 studies reviewed, hearing thresholds obtained by MA were compared to that of the reference test’s (CA) for statistical analysis.

Applied statistical method

The statistical analysis methods for outcome measures also differed substantially across the studies. Three studies reported within-threshold differences between MA and CA using descriptive ranges of 0–5 dB or 0–10 dB threshold differences [27,28,31]. For MA conducted using EarTrumpet app-based MA, the proportion of thresholds falling within 10 dB of CA results ranged from 88% at 6 kHz to 98% at 750 Hz when testing was performed in a sound booth. When conducted in a quiet room, the agreement ranged from 87% at 250 Hz and 6 kHz to 96% at 750 Hz. Confidence intervals were not reported [31]. Another study that also used EarTrumpet reported more precise estimates, with 91.1% difference (95% confidence interval [CI]: 89.1%–98.2%) in a sound booth and 95.8% difference (95% CI: 93.5%–98.0%) when white noise was introduced in the same booth [27]. In the same study but using SHOEBOX MA, the 0–10 dB threshold difference was 86.5% (95% CI: 82.6%–88.5%) in a sound booth and 91.3% (95% CI: 88.5%–92.8%) when white noise was added to the testing environment [27]. Also using SHOEBOX, another study reported frequency-specific 0–10 dB threshold differences: 85.9% (95% CI: 76.0%–92.2%) at 250 Hz, 91.8% (95% CI: 83.2%–96.2%) at 500 Hz, 97.1% (95% CI: 89.9%–99.2%) at 1 kHz, 96.9% (95% CI: 89.5%–99.2%) at 2 kHz, 100% (95% CI: 94.0%–100%) at 4 kHz, and 85.5% (95% CI: 74.7%–92.2%) at 8 kHz [28].

Two studies reported threshold agreement rates but omitted confidence intervals. The first study, using EarTrumpet MA, found that 95% of thresholds obtained in a quiet room fell within 10 dB of CA results, compared to 88% agreement in a clinic waiting area [44]. The second study, using SHOEBOX, reported slightly lower agreement rates—76.4% at 250 Hz, 82.1% at 500 Hz, 85.7% at 1 kHz, 87.9% at 2 kHz, and 81.4% at 4 kHz [37]. The latter also analyzed threshold differences using paired t-tests.

Parametric

Paired t-test was done in six studies [26,37-40,45]. Other parametric methods identified across the reviewed studies were: Student’s t-test [35], Pearson’s correlations [30,42,43,45], ANOVA [33], and linear regression [41,43,48]. Among the studies where paired t-test was done, four utilized the SHOEBOX app-based MA. The first study [40], which did not specify the transducer or test environment, found statistically significant differences (p<0.05) only at 8 kHz (mean difference: 3.34 dB±11.55, p<0.0004) among standard PTA frequencies. The second study [26], conducted with TDH-39 supra-aural audiometric headphones in a clinic consultation room, reported significant differences at 1 kHz (3.18±4.5 dB, p<0.001) and 2 kHz (2.8±5.5 dB, p=0.002). The third study [39], using RadioEar DD450 supra-aural audiometric headphones in a clinic consultation room, demonstrated significant differences at 250 Hz (3.60±8.19 dB, p=0.006) and 500 Hz (2.74±8.71 dB, p=0.048). The fourth study [37], employing TDH-39 audiometric headphones in a hospital clinic room, found significant differences at 250 Hz, 500 Hz, and 1 kHz (all p<0.05).

In contrast, a study using the hearTest app-based MA with Sennheiser HDA 300 circumaural audiometric headphones in a sound booth [38] revealed no significant threshold differences between MA and CA (p>0.05) across tested EHF frequencies. Another study examining the H3 Hearing Test app-based MA with non-proprietary commercial earphones in home settings [45] reported significant differences (p<0.05) at all frequencies except 500 Hz in the left ear. This study also applied Pearson’s and Spearman’s correlations, finding significant correlations (p<0.05) for most frequencies in both ears, except at 500 Hz, 2 kHz, 3 kHz, and 4 kHz in the left ear.

The only study where Student’s t-test was applied used the Mimi app-based hearing test with Sennheiser HDA 200 and noise-cancelling HDA 300 audiometric headphones in a quiet room, demonstrating significant differences at 500 Hz, 1 kHz, and 2 kHz (all p<0.001) for both transducer types [35].

Using Pearson’s correlation, studies demonstrated varying degrees of agreement between MA and CA. One study evaluating four app-based MAs [42] using non-proprietary commercial earphones in non-sound-treated test settings reported the following means across tested frequencies: Easy Hearing Test (r=0.77), Hearing Test & Ear Age Test (r=0.47), Eartone Hearing Test (r=0.69), and Hearing Test (r=0.83).

A separate study utilizing the Care 4 Ear app-based MA [30] with proprietary commercial Apple EarPods in a quiet office setting found all frequencies to be significantly correlated with CA (all p<0.001), with the following coefficients: r=0.660 (250 Hz), r=0.748 (500 Hz), r=0.809 (1 kHz), r=0.791 (2 kHz), r=0.699 (4 kHz), and r=0.709 (8 kHz). The strongest correlations emerged in a study that used the Etymotic Home Hearing Test [43] with ER-3 audiometric insert earphones in a carpeted classroom environment. This study reported strong correlations for all frequencies in both ears: r=0.909 (500 Hz right ear), r=0.917 (500 Hz left ear), r=0.924 (1 kHz right ear), r=0.945 (1 kHz left ear), r=0.960 (2 kHz right ear), r=0.961 (2 kHz right ear), r=0.969 (4 kHz right ear), r=0.970 (4 kHz left ear), r=0.953 (8 kHz right ear), and r=0.968 (8 kHz left ear). It was further reported that between right and left ears, the side exhibiting strong correlation was statistically significant at each frequency (p<0.001).

Linear regression analyses in the reviewed studies found no significant associations between MA hearing threshold variability and: age, baseline ototoxicity-sensitive range, or cisplatin dosage [41]; degree of HL, age, or gender [43]; user-level effects in user-operated audiometry reliability [48].

Non-parametric

Three types of non-parametric tests were applied in some studies: Spearman’s rank correlation coefficient [36,45,49], Mann-Whitney U test [46], and Wilcoxon signed-rank test [32,41]. Graphical methods included Bland-Altman plots to evaluate CA-MA agreement [26,36,40,48] and violin plots to visualize data distributions [42].

Spearman’s rank correlation coefficient in Mimi app-based MA [49] with proprietary commercial Apple EarPods in a non-sound-treated room showed a Spearman correlation coefficient of 0.51 (p<0.0001) for normal hearing and mild HL, and 0.68 (p<0.0001) for moderate and worse HL. For normal hearing alone, the Spearman correlation coefficient was 0.22 (p=0.0001).

Another study using Mimi with Baseus Encok D02 Pro nonproprietary commercial headphones in a quiet clinic room demonstrated either strong or very strong correlations to CA at 250 Hz, 500 Hz, 1 kHz, 2 kHz, and 4 kHz [36]. These results were supported by Bland-Altman plots, which indicated good agreement between MA and CA at each frequency, with most data points falling within the limits of agreement and no proportional bias observed.

Two additional studies [26,40] reporting Bland-Altman plots for individual frequencies in MA and CA also found no proportional bias. Similarly, another study analyzing Bland-Altman plots based on mean thresholds—rather than individual frequencies—reported no proportional bias between MA and CA [48].

Sensitivity and specificity

Several studies reported the sensitivity and specificity of MA using different methodologies. One way was by frequency. The SHOEBOX app-based MA demonstrated sensitivity and specificity of 87.0% and 95.0% at 500 Hz, 100% and 92% at 1 kHz and 2 kHz, and 95.0% and 90.0% at 4 kHz, respectively [26]. The Wulira app-based MA reported frequency-specific results by frequency and ear, and these were the lower of the two values for each pair of ears, by frequency: 76.7% sensitivity and 75.6% specificity at 500 Hz, 87.0% sensitivity and 95.9% specificity at 1 kHz, 95.0% sensitivity and 98.0% specificity at 2 kHz, and 88.1% and 91.0% at 4 kHz [25].

Other studies classified results by HL severity. The KUDU-wave Prime portable audiometer showed 80% sensitivity and 89% specificity for normal hearing, 89% and 37% for mild HL, 89% and 70% for moderate HL, 97% and 85% for moderately-severe HL, and 93% and 96% for severe HL respectively [46]. The Mimi app-based MA reported 35.5% sensitivity and 97.1% specificity for normal hearing (n=76), 57.9% and 59.3% for mild HL (n=83), 19.4% and 84.6% for moderate HL (n=45), 18.2% and 94.7% for moderately-severe HL (n=11), and 80.0% and 96.0% for severe HL (n=11), with overall values of 97.1% sensitivity and 35.5% specificity (n=104) [49].

Several studies reported overall performance metrics. The SHOEBOX app-based MA showed 89% sensitivity (95% CI 80%–94%) and 70% specificity (95% CI 56%–82%) [37], while the OtoID portable audiometer demonstrated 80.6% sensitivity and 85.3% specificity [47]. For detection of HL specifically, SHOEBOX showed 94.3% sensitivity (95% CI 91.9%–96.8%) and 92.3% specificity (95% CI 90.1%–94.4%) in one study [40], and 100% sensitivity and 62.5% specificity in another study [39]. Detection of at least mild HL in one ear using SHOEBOX showed 100% sensitivity (95% CI 88%–100%) and 91% specificity (95% CI 62%–98%) [28]. Detection of moderate HL using Mimi showed 100% sensitivity and 80.2% specificity [43]. Lastly, in a study that evaluated three app-based MA across different environments, EarTrumpet showed 96.3% sensitivity and 83.1% specificity in a quiet room versus 100% and 72% in a clinic waiting area; Audiogram Mobile [44] demonstrated 85.3% sensitivity and 95.1% specificity in a quiet room versus 87.6% and 92.3% in a waiting area. Hearing Test with Audiogram showed 87.8% sensitivity and 69.4% specificity in a quiet room versus 89% and 68.2% in a waiting area [44].

Test-retest reliability

Two studies evaluated test-retest reliability using intraclass correlation coefficient (ICC) to compare CA and MA hearing thresholds. In these studies, each subject completed MA twice, with both MA results compared against their CA thresholds. One study using SHOEBOX reported an overall ICC of 0.98 [28], while another testing four app-based MAs found an overall ICC of 0.90 [42].

Discussion

Challenges of OMPs

The key barriers to ototoxicity monitoring identified in the literature include inconsistent referrals, resource constraints, low awareness of ototoxicity monitoring, and patient-related factors.

Inconsistent referrals can stem from the lack of referral pathway [9] and variability in clinician referral practices [50]. It was observed that cancer patients who followed up with ENTs had higher referral rates to OMP, attributed to higher awareness of ototoxicity and direct audiology access [19]. This suggests that on-site provision of OMP may eliminate administrative inefficiencies of referral pathways. MA is mobile by design; it can enable point-of-care OMP delivery at the bedside.

Resource constraints arose from two sources: infrastructure and manpower. Essential infrastructure—sound booths, audiometers, and transducers—requires an estimated USD 56,700 setup cost [24]. MA could achieve comparable functionality at lower cost [47,51]. While manpower cannot be replaced, MA with automated testing function may improve efficiency by enabling concurrent multi-patient testing and eliminating manual test administration.

Low awareness of ototoxicity monitoring stems from three factors. One, an underlying lack of national guidelines such as in the UK and Italy meant no agreed-upon standard of care [17,20]. Two, where guidelines do exist, the scope of tests varied from hearing monitoring only (baseline/pre-dose/posttreatment), to having a battery of tests including distortion product otoacoustic emissions (DPOAE) and EHF [52]. Three, staff were unfamiliar with the reasons behind ototoxicity monitoring [24]. Centers initiating OMPs should prioritize basic hearing monitoring for a start. Implementing this via MA further lowers barriers of entry.

Patient related factors directly affect patient compliance to OMPs. The added demands of attending OMPs on the patients already experiencing cancer- and treatment-fatigue [53] increases dropout rates, resulting in patients being lost follow-ups. Bringing OMP to the patient by use of MA can mitigate this risk.

Mobile audiometry

This scoping review identified 14 distinct app-based hearing tests, and three portable audiometers utilized for MA. It is important to recognize that app-based MAs are software applications dependent on an operating system (OS) for functionality. The 14 app-based MAs ran on various OS platforms, including iOS, Android OS, and Windows OS. Each OS requires specific hardware infrastructure to operate, with Android and Windows OS showing broader hardware diversity [34].

This hardware diversity inherently leads to differences in key components that can directly impact MA performance. Of relevance is the digital-to-analog converter (DAC), which converts digital signals to analog outputs. While apps can manipulate the digital signal transmitted to DAC, apps cannot bypass DAC’s hardware constraints [54]. This was why the researchers in one study connected an external DAC to modify stimulus level limits [48]. Similarly, transducers represent another hardware component with fixed physical characteristics that apps cannot override.

Standardizing hardware components is a direct solution to mitigate hardware diversity. This approach could be observed in studies that utilized SHOEBOX app-based MA, which maintained strict hardware consistency by operating exclusively on iOS devices (iPads [26,37,39,40] and iPad Air [27]) and using only audiometric transducers. These included circumaural headphones (TDH-39 [26,37], TDH-50 [28], RadioEar DD450 [39]) and insert earphones (3A E-A-Rtone [27], ER3A [28]).

Following the hardware standardization principle, integrated and purpose-built units are the solution, as they eliminate all ambiguities. Such solution already exists in the form of clinical audiometers. Portable audiometers are a type of clinical audiometers. This review identified three portable audiometers used in MA: two models from KUDUwave and one from OtoID.

When hardware standardization proves impractical, calibration is an alternative for managing device-specific limitations. One study highlighted the lack of established calibration protocols for MA [27], which likely explains both the unaddressed calibration in eight studies [25,30,31,33,35,36,40,45] and the application of existing technical standards not designed for MA in others [39,41,48].

Two studies highlighted the lack of standardized calibration protocols for MA [25,27]. This explained the complete omission of calibration in eight studies [25,30,31,33,35,36,40,45]. It also explained the varied calibration approaches undertaken. In a study using the hearTest app-based MA, researchers adapted the calibration protocol from its affiliated screening tool, hearScreen [32]. In two studies, researchers applied published reference equivalent threshold sound pressure level (RETSPL) values to their transducers [32,38]—Sennheiser HD202 II supra-aural non-audiometric headphones were calibrated using RETSPLs from a hallmark study [29], while the Sennheiser HD 280 Pro supra-aural non-audiometric headphones were calibrated using values presented at a conference [55].

Interestingly, researchers bypassed standard calibration and hardware limitations in one study by inserting a pre-calibrated USB sound card to the tablet running the Etymotic Home Hearing Test. The practical viability of this approach remains unexamined, however [43].

Hardware limitations directly affect downstream parameters, including intensity range and frequency range. Both are essential diagnostic elements of hearing threshold testing. Both were not consistently addressed in the studies reviewed. Frequency range is particularly important when it comes to ototoxicity monitoring (OMP). The studies that tested at standard frequencies and EHF used portable audiometers OtoID [47] and KUDUwave Prime [46]. The study that tested only at EHF of 8, 10, 12.5, and 16 kHz used hearTest app-based MA [38]. One thing in common for these three MAs were the transducers—only audiometric transducers were used. A study using hearTest MA reported 86.6% 0–5 dB threshold correspondence for audiometric headphones (Sennheiser HDA 300 circumaural), compared to 78.7% for commercial non-proprietary headphone (Sennheiser HD202 II supraaural) [38]. This highlighted an important trade-off: while some MAs can operate with various transducers, restricting use to audiometric transducers yields more accurate hearing threshold measurements.

The two studies that performed EHF testing through MA focused on populations at risk for high-frequency HL: adults potentially exposed to ototoxic medications [38] and veterans undergoing cisplatin chemotherapy [47]. MA was done in a sound booth in the first study [38] and done in “quiet patient care area around chemotherapy treatment unit” [47] in the latter study. Notably, only one of these studies [38] reported no statistically significant differences in EHF thresholds between CA and MA, though neither study provided sensitivity/specificity metrics or evaluated test-retest reliability. This indicated potential for OMP to be carried out in a non-sound-treated test setting like the chemotherapy bay using certain MA.

Within the scope of this review, only two app-based MA demonstrated capacity to mitigate the effects of dynamic ambient noise—testing halts if the ambient noise levels exceed 40 dB HL [30] or if broadband noise exceeds 70 dB SPL [47]. The different noise assessment approaches and cut offs indicates the lack of consensus on appropriate noise limits for MA done in non-sound-treated test settings.

The review found substantial variability in how studies reported statistical results, making comparisons difficult. A key factor was the difference in intensity ranges between MA and CA. When CA is able to test below 10 dB HL, MA testing down to only 10 dB HL inadvertently created a floor effect. This was acknowledged by the researchers, who reported results with and without floor effect: the 0–5 dB threshold correspondence of CA and hearTest app-based MA with audiometric headphones was 77% including floor effect, and 70.2% excluding floor effect [38]. Certain measures of meaningful variability are confounded by the floor effect. Three other studies also noted this limitation [32,41,48]. While one study pointed out that statistical significance is not equivalent to clinical significance [37], there can be clinical implications if the diagnostic accuracies are affected [38], whether by hardware constraints, intensity range, frequency range, or ambient noise to name a few.

Based on current evidence, there are more app-based options than portable audiometers options for MA. There were also more studies conducted on app-based MAs. App-based MA represent an accessible and scalable solution as they can be used with a wide variety of OS and hardware. However, the same latitude are also inherent flaws, affecting diagnostic accuracies. A study aptly concluded that, “If the test should be used for clinical purposes, it will require that the equipment should be approved for that purpose.” [48]. Among all the MA options, clinically validated MAs with ambient noise management at time of review are: KUDUwave, hearTest (by hearX Group), and SHOEBOX. There were few studies that used these MA, fewer that had EHF testing, and fewer still examined populations vulnerable to ototoxicity. The limited evidence precludes definitive conclusions about MA suitability for OMPs.

Limitations

While the benefits of and barriers to OMP adoption are well-documented, no studies have reported detailed implementation strategies for successful programs. There is no reference to guide implementation and practice. However, it also indicates that OMP is an emerging clinical framework with potential for growth.

The reviewed MA studies showed substantial methodological variability and limited reporting of key parameters, including the number of ears tested (which does not directly equate to the number of subjects), bone conduction testing, and air conduction masking, preventing meaningful cross-study comparisons. Only two studies evaluated MA use in OMPs.

Conclusion

There are various barriers to OMP adoption. MA presents as an accessible and scalable solution to overcome reported barriers, such as resource constraint, inconsistent referral, and patient-related factors. However, its diagnostic accuracy remains uncertain due to significant methodological variability across studies. For now, OMPs intending to use MA should consider clinically validated modalities.

Notes

Conflicts of Interest

The authors have no financial conflicts of interest.

Author Contributions

Conceptualization: Pierre W. C. Yim, Zee Hui Lim. Data curation: Pierre W. C. Yim, Zee Hui Lim. Formal analysis: Pierre W. C. Yim, Zee Hui Lim. Investigation: Pierre W. C. Yim, Zee Hui Lim. Methodology: Pierre W. C. Yim. Project administration: Pierre W. C. Yim. Supervision: Pierre W. C. Yim, Zee Hui Lim. Validation: Pierre W. C. Yim, Zee Hui Lim. Writing—original draft: Pierre W. C. Yim, Zee Hui Lim. Writing— review & editing: Pierre W. C. Yim, Zee Hui Lim. Approval of final manuscript: Pierre W. C. Yim, Zee Hui Lim.

Funding Statement

None

Acknowledgments

None

Fig. 1.

PRISMA diagram of study inclusion in scoping review.

Table 1.

Search terms used in the review

Database	Search terms	Number of articles
Objective 1: Ototoxicity monitoring challenges
PubMed	(ototoxicity monitoring OR ototoxicity screening) AND (challenges OR barriers OR obstacles) AND (platinum chemotherapy OR cisplatin OR carboplatin OR oxaliplatin)	28
Google Scholar	(“ototoxicity monitoring” OR “ototoxicity screening”) AND (“challenges” OR “barriers”) AND (“platinum chemotherapy” OR “cisplatin” OR “carboplatin” OR “oxaliplatin”)	296
Scopus	(“ototoxicity monitoring” OR “ototoxicity screening”) AND (“challenges” OR “barriers” OR “obstacles”) AND (“platinum chemotherapy” OR “cisplatin” OR “carboplatin” OR “oxaliplatin”)	6
Embase	(‘ototoxicity monitoring’ OR ‘ototoxicity screening’ OR ‘audiological monitoring’) AND (‘implementation challenge’ OR barrier* OR ‘feasibility’/exp OR feasibility OR ‘compliance’/exp OR compliance OR ‘adherence’/exp OR adherence OR limitation* OR ‘program evaluation’/exp OR ‘program evaluation’ OR ‘sustainability’/exp OR sustainability) AND (‘cisplatin’/exp OR ‘cisplatin’ OR ‘carboplatin’/exp OR ‘carboplatin’ OR ‘oxaliplatin’/exp OR ‘oxaliplatin’ OR ‘platinum-based chemotherapy’)	15
Objective 2: Accuracy of mobile audiometry for diagnostic hearing thresholds
PubMed	(“mobile health” OR “mHealth” OR “tele-audiology” OR “mobile audiology” OR “mobile audiometry”) AND (“ototoxicity” OR “hearing loss”) AND (“monitoring” OR “screening”)	70
Google Scholar	(“mobile audiometry” OR “portable audiometry” OR “teleaudiology” OR “remote hearing assessment” OR “smartphone audiometry”) AND (“ototoxicity” OR “chemotherapy-induced hearing loss”)	170
Scopus	(ALL (“mobile audiometry”) OR ALL (“portable audiometry”) OR ALL (“teleaudiology”) OR ALL (“remote hearing assessment”) OR ALL (“smartphone audiometry”) AND ALL (“hearing loss”) OR ALL (“ototoxicity”) OR ALL (“chemotherapy-induced hearing loss”)	84
Embase	(‘mobile audiometry’ OR ‘portable audiometry’ OR teleaudiology OR ‘remote hearing assessment’ OR ‘smartphone audiometry’) AND (‘hearing loss’/exp OR ‘hearing loss’ OR ‘hearing impairment’/exp OR ‘hearing impairment’ OR ‘ototoxicity’/exp OR ‘ototoxicity’ OR ‘hearing screening’/exp OR ‘hearing screening’ OR ‘audiometry’/exp OR ‘audiometry’)	211

Table 2.

Characteristics of studies on challenges of ototoxicity monitoring programs

Study	Country	Title	Journal	Study design	Population	Challenges
Konrad-Martin (2018) [9]	United States	Applying U.S. national guidelines for ototoxicity monitoring in adult patients: perspectives on patient populations, service gaps, barriers and solutions	International Journal of Audiology	Mixed-methods	Ototoxicity experts	1) Inconsistent referrals
						2) Scheduling limitations
						3) Location and space limitations; Audio and onco clinic located in different buildings
						4) Staffing limitations
Lee (2023) [18]	United States	Audiologic follow-up in patients with head and neck cancer treated with cisplatin and radiation	Laryngoscope	Mixed-methods	Head and neck cancer patients on cisplatin	Patients without insurance and stage IV cancers were associated with complete loss of audiologic follow-up
Konrad-Martin (2023) [22]	United States	Audiologists’ perceived value of ototoxicity management and barriers to implementation for at-risk cancer patients in VA: the OtoMIC survey	Journal of Cancer Survivorship	Mixed-methods	Audiologists	1) Care and referral coordination with oncology
						2) Audiology workload
						3) Lack of protocols
Paken (2022) [24]	South Africa	Cisplatin-associated ototoxicity: perspectives from a single institution cervical cancer cohort and implications for developing a locally responsive monitoring …	BMC Health Services Research	Mixed-methods	Doctors, oncology nurses, pharmacists, radiotherapists, and patients	Creative appointment scheduling, easy facility access, and detailed locally comprehensible couselling improved patient compliance
Maru (2018) [20]	United Kingdom	Current practice of ototoxicity management across the United Kingdom (UK)	International Journal of Audiology	Qualitative	Audiologists, ENT specialists/AVPs, GPs	- 72% reported the absence of ototoxicity management protocols
Maru (2018) [20]	United Kingdom		International Journal of Audiology	Qualitative	Audiologists, ENT specialists/AVPs, GPs	- Great inconsistency and variation across the UK in ototoxicity management services provided, treatment modification, monitoring and referral pathways
Ehlert (2022) [23]	South Africa	Ototoxicity monitoring in South African cancer facilities: a national survey	South African Journal of Communication Disorders	Qualitative	Healthcare professionals (GPs, oncologists, nurses, pharmacists and audiologists)	- Referral system
						- Environmental noise
						- Compromised status of cancer patients
						- Poor awareness of best practice guidelines
Paken (2020) [21]	South Africa	Perspectives and practices of ototoxicity monitoring	South African Journal of Communication Disorders	Qualitative	Oncologists, nurses, and pharmacists did questionnaires.	- Only 33% of nurses were aware of ototoxicity in comparison to the oncologists and pharmacists
					Audiologists were interviewed	- No provision for ototoxicity monitoring in the chemotherapy protocols or any ototoxicity monitoring programme in place
						- No evidence that knowledge of cisplatin-associated ototoxicity translated into an appropriate management strategy
						- Audiologists require greater awareness of monitoring programmes
Gambacorta (2023) [17]	Italy	Practice of monitoring cisplatininduced ototoxicity by audiology, ENT, and oncology specialists: A survey-based study in a single Italian medical center	Audiology Research	Retrospective cohort study	Oncologists, audiologists, and ENT specialists	- No well-defined ototoxicity monitoring protocol
Lee (2024) [19]	United States	Trends in ototoxicity monitoring among cisplatin-treated patients with cancer	Journal of Cancer Survivorship	Retrospective cohort study	Cancer patients treated with cisplatin for curative intent	Patients with non–head and neck cancer may be at increased risk for loss of audiologic follow-up

ENT, ear, nose, and throat; AVPs, audio-vestibular physicians; GPs, general physicians

Table 3.

Characteristics of studies on mobile audiometry

Study	Country	Title	Participants (n)	Mobile audiometry/Type	Operating system	Transducer type	Transducer	Calibration	Frequency range (Hz)	Intensity range	Test setting
Foulad (2013) [31]	United States	Automated audiometry using apple iOS-based application technology	42	EarTrumpet (version 1.1.0; PraxisBiosciences, Irvine, California)	iOS on 10 variants of Apple devices (Apple Inc)	Proprietary commercial headphone	Apple intraconchal earphones (MA814LL & MB770G)	NR	250, 500, 750, 1,000, 1,500, 2,000, 3,000, 4,000, 6,000, 8,000	NR	Sound booth and quiet place (bedroom)
Foulad (2013) [31]	United States		42	App-based MA	iOS on 10 variants of Apple devices (Apple Inc)	Proprietary commercial headphone	Apple intraconchal earphones (MA814LL & MB770G)	NR		NR	Sound booth and quiet place (bedroom)
Garcia (2021) [40]	United States	Implementation of Mobile Audiometry During the COVID-19 Pandemic	52	SHOEBOX Ltd	iOS (iPad; Apple Inc)	NR	NR	NR	Standard PTA frequencies	NR	NR
Garcia (2021) [40]	United States		52	App-based MA	iOS (iPad; Apple Inc)	NR	NR	NR	Standard PTA frequencies	NR	NR
Katyayan (2022) [45]	India	Validation of app-based hearing assessment (H3 hearing test) through smart phone: preliminary trends	44	H3 Hearing Test	Android OS (subjects’ own Android mobile devices)	Commercial earphones	Subjects’ own earphones hence various brands and makes	No	500, 1,000, 2,000, 3,000, 4,000, 6,000	NR	Closed room at subjects’ home
Katyayan (2022) [45]	India		44	App-based MA	Android OS (subjects’ own Android mobile devices)	Commercial earphones	Subjects’ own earphones hence various brands and makes	No	500, 1,000, 2,000, 3,000, 4,000, 6,000	NR	Closed room at subjects’ home
Sørensen (2023) [48]	Denmark	AMTASTM and user-operated smartphone research application audiometry–An evaluation study	58	Research app “R-App” (Maersk McKinney Moeller Institute, SDU Odense)	Android OS (version 8, Sony Xperia XZ1 smartphone, Sony Group Corp, Tokyo, Japan)	Audiometric headphone	RadioEar DD450 circumaural headphones, with external DAC	Yes: type 4153 artificial ear (IEC 60318–1 coupler)	250, 500, 1,000, 2,000, 3,000, 4,000, 6,000, 8,000	<80 dB HL	Non-sound-treated consultation room with ambient noise monitoring
Sørensen (2023) [48]	Denmark		58	App-based MA		Audiometric headphone	RadioEar DD450 circumaural headphones, with external DAC	Yes: type 4153 artificial ear (IEC 60318–1 coupler)	250, 500, 1,000, 2,000, 3,000, 4,000, 6,000, 8,000	<80 dB HL
Batte (2019) [25]	Uganda	The accuracy of a mobile phone application (Wulira app) compared to standard audiometry in assessing hearing loss among patients on treatment for multidrug-resistant tuberculosis in Uganda	120	Wulira app	Android OS on unspecified device	NR	“Standard headphones”	NR	500, 1,000, 2,000, 3,000, 4,000	NR	Soundproof booth
Batte (2019) [25]	Uganda		120	App-based MA	Android OS on unspecified device	NR	“Standard headphones”	NR	500, 1,000, 2,000, 3,000, 4,000	NR	Soundproof booth
Brennan-Jones (2016) [33]	Australia	Clinical validation of automated audiometry with continuous noise-monitoring in a clinically heterogeneous population outside a sound-treated environment	44	KUDUwave 5000 (eMoyoDotNet; Pretoria, South Africa) (IEC 60645-1/2)	NA	Part of the portable audiometer	Part of the portable audiometer	NR	Standard PTA frequencies	NR	Quiet room with mean ambient noise level measured
Brennan-Jones (2016) [33]	Australia		44	Portable audiometer	NA	Part of the portable audiometer	Part of the portable audiometer	NR	BC: 500, 1,000, 2,000, 4,000	NR	Quiet room with mean ambient noise level measured
Mosley (2019) [43]	United States	Reliability of the home hearing test: Implications for public health	112	Etymotic Home Hearing Test	Windows OS (Microsoft Surface Pro 4 tablet)	Audiometric insert earphones	ER-3 insert earphones	Calibrated sound card	500, 1,000, 2,000, 4,000, 8,000	≤85 dB HL	Carpeted classroom (up to 8 subjects on simultaneous testing)
Mosley (2019) [43]	United States		112	App-based MA	Windows OS (Microsoft Surface Pro 4 tablet)	Audiometric insert earphones	ER-3 insert earphones	Calibrated sound card	500, 1,000, 2,000, 4,000, 8,000	≤85 dB HL
Moazzami (2024) [35]	Canada	The Emerging Future of Mobile Audiometry: A Prospective Validation Study of the Mimi Hearing Test Application	75	Mimi hearing test version 5.2.1, Mimi Hearing Technologies GmbH)	iOS on iPhone X, (version 14.8.1; Apple Inc., Cupertino, CA)	Audiometric headphones	Sennheiser HDA 200 over-the-ear headphones (Sennheiser Electronic Corporation, Lower Saxony, Germany)	NR	500, 1,000, 2,000, 4,000, 6,000, 8,000	NR	Quiet room with background sound monitoring
Moazzami (2024) [35]	Canada		75	App-based MA		Audiometric headphones	Sennheiser HDA 300 over-the-ear headphone	NR	500, 1,000, 2,000, 4,000, 6,000, 8,000	NR	Quiet room with background sound monitoring
Swords (2024) [42]	United Kingdom	A Multicenter Validity Study of Four Smartphone Hearing Test Apps in Optimized and Home Environments	139	2 or more of following apps on subjects’ personal devices:	1), 2) iOS	Non-proprietary commercial earphones	Prosignal (PSG08468)	Verified adequate output and frequency response with KEMAR	500, 1,000, 2,000, 4,000, 8,000	NR	Once in sound treated room, thrice in subject’s own home
				1) Easy Hearing Test	3) Android OS
				2) Hearing Test and Ear Age Test	4) iOS & Android OS
				3) Eartone Hearing Test
				4) Hearing Test
				App-based MA
Kelly (2018) [44]	United States	Tablet-based screening for hearing loss: feasibility of testing in nonspecialty locations	107	1) EarTrumpet (Version 1.2.0, Praxis BioSciences, LLC, Irvine, CA)	iOS on Apple iPad	Non-proprietary commercial headphones	Bose QuietComfort 15 acoustic noise cancelling headphones	“Self-calibrated”	Standard PTA frequencies	NR	Quiet examination room in clinic waiting area with ambient noise measured
				2) Audiogram Mobile (Version 3.1.6, Vincenzo Cocciolo)					Additional 6,000 Hz for 1) and 2)
				3) Hearing Test with Audiogram (Version 1.0.1, Pieezo Hearsay Pte Ltd, Singapore)
				App-based MA
Thompson (2015) [26]	United States	Accuracy of a tablet audiometer for measuring behavioral hearing thresholds in a clinical population	49	SHOEBOX audiometry application	iOS on Apple iPad (Apple, Inc)	Audiometric headphones	TDH-39 supra-aural headphones	Calibration by Clear Water Association	500, 1,000, 2,000, 4,000	15 to 90 dB HL	Clinic consultation room with moderate traffic, ambient noise measured
Thompson (2015) [26]	United States		49	App-based MA	iOS on Apple iPad (Apple, Inc)	Audiometric headphones	TDH-39 supra-aural headphones	Calibration by Clear Water Association	500, 1,000, 2,000, 4,000	15 to 90 dB HL
Saliba (2017) [27]	Canada	Accuracy of Mobile-Based Audiometry in the Evaluation of Hearing Loss in Quiet and Noisy Environments	33	1) EarTrumpet	iOS on Apple iPad (iOS 8; Apple, Cupertino, California)	Audiometric insertphone with circumaural muffs placed over ears	EA-RTONE 3A insert earphones (3M Auditory Systems, Indianapolis, Indiana)	Calibrated by Genie Audio Inc (St-Laurent, Canada)	500, 1,000, 2,000, 4,000, 6,000, 8,000	NR	1) Sound booth
				2) SHOEBOX							2) Sound booth with 50 dB white noise
				Both apps are automatic masking function
				App-based MA
van Tonder (2017) [32]	South Africa	Automated smartphone threshold audiometry: Validity and time efficiency	95	HearTest application	Android OS v4.4 on Samsung SM-G313H Trend Neo Smartphone (Samsung, Suwon, South Korea)	Audiometric headphones	Sennheiser HD 202 II supra-aural headphones (Wedemark, Germany)	Adapted calibration protocol of affiliated hearing screening app hearScreen	500, 1,000, 2,000, 4,000, 8,000	≥10 dB HL	Sound booth
van Tonder (2017) [32]	South Africa		95	App-based MA		Audiometric headphones			500, 1,000, 2,000, 4,000, 8,000	Highest limit NR	Sound booth
Davis (2022) [49]	United States	Pure tone audiometry as assessed by a commercially-available mobile phone application compared to formal audiometry	90	Mimi^TM (Mimi Hearing Technologies, Berlin, Germany)	iOS on 6th generation Apple iPad^TM (Cupertino, CA) model number MR7K2LL/A	Propietary consumer earphones	Apple EarPods (Cupertino, CA) with disposable sheath	Reported as “calibrated” with no further details	500, 1,000, 2,000, 4,000	≤90 dB HL	Non-sound isolated room
Davis (2022) [49]	United States		90	App-based MA		Propietary consumer earphones	Apple EarPods (Cupertino, CA) with disposable sheath	Reported as “calibrated” with no further details	500, 1,000, 2,000, 4,000	≤90 dB HL	Non-sound isolated room
Bastianelli (2019) [28]	Canada	Adult validation of a self-administered tablet audiometer	40	SHOEBOX Audiometry, (SHOEBOX Inc., Ottawa, ON)	iOS on unspecified device	1) Audiometric insert earphones	1) ER3A insert earphones	Reported as “calibrated” with no further details	Standard PTA frequencies	10 to 90 dB HL	Quiet clinical exam room
Bastianelli (2019) [28]	Canada	Adult validation of a self-administered tablet audiometer	40	App-based MA	iOS on unspecified device	2) Audiometric headphones	2) TDH-50 supra-aural headphones	Reported as “calibrated” with no further details	Standard PTA frequencies	10 to 90 dB HL	Quiet clinical exam room
Bornman (2019) [38]	South Africa	Extended high-frequency smartphone audiometry: Validity and reliability	24	HearTest application (HearX Group, Pretoria, South Africa)	Android OS v4.0.4 on Samsung Galaxy Trend Neo smartphone	1) Audiometric headphones	1) Sennheiser HDA 300 circumaural headphones	Calibrated on calibration feature of hearTest app	EHF 8k, 10k, 12.5k, 16k	Lowest limit 10 dB HL up to 75/ 70/ 75/ 65 in respective EHF	Sound booth
Bornman (2019) [38]	South Africa		24	App-based MA	Android OS v4.0.4 on Samsung Galaxy Trend Neo smartphone	2) Audiometric headphones	2) Sennheiser HDA 200 circumaural headphones	Calibrated on calibration feature of hearTest app	EHF 8k, 10k, 12.5k, 16k		Sound booth
Brittz (2019) [41]	South Africa	Monitoring hearing in an infectious disease clinic with mHealth technologies	200	HearTest application (HearX Group, Pretoria, South Africa)	Android OS v4.3 on Samsung Galaxy A3 smartphone	Audiometric headphones	Supra-aural Sennheiser HD 280 Pro headphones (Sennheiser, Wedemark, Germany)	Calibrated according to RETSPL values published in research	2,000, 4,000, 8,000Hz	Lowest limit 10 dB HL up to 90 dB HL (2 & 4 kHz), 80 dB HL (8 kHz)	Quiet room in clinics
Brittz (2019) [41]	South Africa		200	App-based MA	Android OS v4.3 on Samsung Galaxy A3 smartphone	Audiometric headphones		Calibrated according to RETSPL values published in research	2,000, 4,000, 8,000Hz		Quiet room in clinics
Dille (2015) [47]	United States	A store-and-forward tele-audiology solution to promote efficient screenings for ototoxicity during cisplatin cancer treatment	21	OtoID (VA NCRAR)	NA	Audiometric headphones	Sennheiser HDA 200 circumaural headphones (Sennheiser; Old Lyme, CT)	Calibration by VA NCRAR	500, 1,000, 2,000, 4,000, 8,000	-10 to 105 dB SPL	Quiet patient care area around chemo treatment unit with ambient noise monitoring
Dille (2015) [47]	United States		21	Portable audiometer MA	NA	Audiometric headphones		Calibration by VA NCRAR	Additional EHF 10k, 12.5k, 16k, 20k	-10 to 105 dB SPL
Purnami (2022) [46]	Indonesia	Validity of automated audiometry for hearing examination in patients with multidrug-resistant tuberculosis	36	KUDUwave audiometer (model KUDUwave Prime)	NA	Part of the portable audiometer	Part of the portable audiometer	Described as “done routinely”	Standard PTA frequencies	NR	Open space of pulmonology unit with ambient noise measured
Purnami (2022) [46]	Indonesia		36	Portable audiometer MA	NA	Part of the portable audiometer	Part of the portable audiometer	Described as “done routinely”	Standard PTA frequencies	NR	Open space of pulmonology unit with ambient noise measured
Lubner (2020) [39]	United States	Hearing Vital Signs: Mobile Audiometry in the Emergency Department for Evaluation of Sudden Hearing Loss	23	SHOEBOX (Clear Water Association)	iOS on iPad-based device (Apple)	Audiometric headphone	RadioEar supra-aural DD450 headphones	Calibrated to American National Standards Institute standards	Standard PTA frequencies	NR	Non-sound treated consultation rooms
Lubner (2020) [39]	United States		23	App-based MA	iOS on iPad-based device (Apple)	Audiometric headphone	RadioEar supra-aural DD450 headphones		Standard PTA frequencies	NR	Non-sound treated consultation rooms
Lee (2024) [30]	Korea	Assessing the accuracy and reliability of application-based audiometry for hearing evaluation	70	Care 4 Ear application (version 1.0.6, MIJ Co., Ltd.)	iOS on iPad mini 3 (iOS 8; Apple, Cupertino, CA, USA)	Proprietary commercial earphones	EarPods with 3.5 mm headphone plug (Apple, Cupertino, CA, USA)	NR	Standard PTA frequencies	NR	Quiet office
Lee (2024) [30]	Korea		70	App-based MA	iOS on iPad mini 3 (iOS 8; Apple, Cupertino, CA, USA)	Proprietary commercial earphones		NR	Standard PTA frequencies	NR	Quiet office
Wong (2025) [36]	Singapore	Evaluating the accuracy of a self-administered smartphone hearing test application in a geriatric population	52	Mimi Hearing Test 5.2.2 (Mimi Hearing Technologies, Berlin, Germany)	iOS on iPod 7th generation (version 15.2)	Commercial headphone	Baseus Encok D02 Pro headphones	NR	Standard PTA frequencies	NR	Quiet clinic room to simulate quiet home setting
Wong (2025) [36]	Singapore		52	App-based MA	iOS on iPod 7th generation (version 15.2)	Commercial headphone	Baseus Encok D02 Pro headphones	NR	Standard PTA frequencies	NR	Quiet clinic room to simulate quiet home setting
Yalamanchali (2022) [37]	India	Evaluation of portable tablet-based audiometry in a South Indian population	70	SHOEBOX Audiometry applications (Clear-water Clinical Limited, Ottawa, Canada)	iOS on iPad	Audiometric headphones	TDH-39 supra-aural headphones	Reported as “calibrated” with no further details	Standard PTA frequncies	NR	Hospital clinic room
Yalamanchali (2022) [37]	India		70		iOS on iPad	Bone conductor NR	Bone conductor NR	Reported as “calibrated” with no further details	Standard PTA frequncies	NR	Hospital clinic room

MA, mobile audiometry; EHF, extended high frequencies; NA, not applicable; NR, not reported; RETSPL, reference equivalent threshold sound pressure levels; PTA, pure-tone audiometry; standard PTA frequencies: 250, 500, 1,000, 2,000, 4,000, and 8,000 Hz

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