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Review
Validated Smartphone-Based Apps for Ear and Hearing
Assessments: A Review
Tess Bright, BBiomedSc, MClinAud, MSc; Danuk Pallawela, BSc, MSc
London School of Hygiene & Tropical Medicine, London, United Kingdom
Corresponding Author:
Tess Bright, BBiomedSc, MClinAud, MSc
London School of Hygiene & Tropical Medicine
Keppel St
London, WC1E 7HT
United Kingdom
Phone: 44 (0)20 7636 8636
Fax: 44 (0)20 7436 5389
Email: tess.bright1@lshtm.ac.uk
Abstract
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.
(JMIR Rehabil Assist Technol 2016;3(2):e13) doi:10.2196/rehab.6074
KEYWORDS
hearing; testing; mobile; audiometry; smartphone; applications; app; hearing loss; hearing impairment; surveys; prevalence
Introduction
In 2012, the World Health Organization (WHO) estimated that
disabling hearing impairment (DHI) affects approximately 360
million people, or 5.3% of the global population [1,2]. The
definition of DHI is a pure tone average (PTAv) of thresholds
at 500, 1000, 2000 and 4000 hertz (Hz) in the better hearing ear
of greater than 30 decibels (dB) in children, and greater than
40 dB in adults. Most people with DHI live in low- and
middle-income countries (LMICs), with the greatest burden in
the Asian Pacific, southern Asian, and sub-Saharan African
regions [3]. The estimated global prevalence of DHI is
increasing [3,4], and may be due to greater life expectancy in
many countries, resulting in: increased prevalence of age-related
hearing loss; early detection of hearing loss facilitated through
increased availability of hearing screening equipment; increasing
hearing loss due to occupational, recreational, and environmental
noise exposure; and increased and extensive use of ototoxic
medications for treating a range of medical conditions, such as
human immunodeficiency virus (HIV) [3,4].
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Hearing loss has a substantial impact on psychosocial wellbeing
and economic independence [3]. If acquired in childhood, before
speech has developed, hearing loss can impede language
development and hence limit educational attainment [3]. Hearing
loss also has high societal costs, mainly due to losses in
productivity [5]. If hearing impairment is identified early and
treatment is provided, many of these negative effects can be
avoided [6,7]. Screening for hearing impairment can be useful
for a range of age groups and patient groups, including
newborns, to detect congenital hearing impairment; school
children, to detect late-onset hearing impairment; the elderly,
to identify age-related hearing loss (presbyacusis); and those
with HIV [3,8-11]. In addition, screening for hearing impairment
in population-based surveys is important to determine its
magnitude and plan services accordingly [12]. However,
substantial challenges exist in screening for hearing impairment
(especially in LMICs) such as the need for a quiet testing
environment, prohibitively expensive specialist hearing
assessment equipment that requires regular calibration, and
skilled professionals to conduct clinical tests. In many LMICs,
there is a severe shortage of hearing health care professionals
(ie, audiologists, speech pathologists, and ear, nose, and throat
[ENT] specialists). In most of sub-Saharan Africa, services are
either nonexistent or limited to urban centers, resulting in 1
ENT per 250,000 to 7.1 million people [13]. This scarcity
contrasts with Europe, where there is 1 ENT per 10,000-30,000
people [14]. Due to these barriers, hearing impairment remains
undetected and unmanaged for a substantial number of people
in LMICs, and robust data from population-based surveys is
lacking. 2012 WHO prevalence estimates comprised of 42
population-based surveys in 29 countries [1,2,6]. In contrast,
the Rapid Assessment of Avoidable Blindness survey
methodology been used in over 200 population-based surveys
of visual impairment [33].
The gold standard for hearing screening for people >4 years of
age is Pure Tone Audiometry (PTA) [12]. For subjects <4 years
of age, objective tests such as Otoacoustic Emissions (OAE)
and Auditory Brainstem Response (ABR) testing are
recommended [12]. Understanding the probable causes of
hearing loss is vital for management and referral processes.
Causes of hearing loss are typically determined using a
comprehensive battery of tests. In hearing screening programs,
these tests include tympanometry (a test of middle ear function)
and otoscopy (visual examination of the eardrum). The
equipment and expertise required for these tests and
examinations is lacking. However, new and innovative
technologies that are low-cost, easy to use, and automated have
recently been developed and may be useful in overcoming some
of the challenges. For instance, replacing PTA (typically
conducted by an audiologist) with automated computer-based
audiometry can provide comparable results on threshold testing
[15]. Developers of smartphone apps have begun to harness this
technology to generate apps for performing self-administered
hearing screening tests. In addition, apps exist for performing
video otoscopy, whereby images of the eardrum are captured
and may be sent to an ENT specialist to diagnose and manage
ear conditions remotely. With the global rise in smartphone
penetration, apps offer a promising avenue to screen for hearing
impairment and assess the causes in a low-cost manner. A large
number of apps for measuring ear and hearing function are
thought to exist that can potentially be utilized, but their
scientific validity has not been reviewed in-depth. The aim of
this review is to identify available apps to screen for hearing
impairment, and compare the features and peer-reviewed
validation studies performed to date.
Methods
A search was conducted to find apps for ear and hearing
assessments, using the most popular commercial app stores by
market share: Google Play (Android apps) and the Apple App
Store (iPhone/iPad apps) [16]. Next, a review of peer-reviewed
literature was conducted to determine whether any of the
identified apps had been validated against gold standard
measures.
Google Play and Apple App Store Search
A search was conducted on Google Play and Apple App Store
in July 2015. The main types of apps searched were those that
could perform audiometry, tympanometry, OAEs, ABR testing,
and otoscopy. These tests were chosen, as they can be used for
assessment of ear and hearing function in a range of settings,
including screening programs and population-based surveys
[12]. A range of search terms were used, including
clinically-recognized terms such as audiometry and layman’s
terms such as hearing test. Table 1 provides a list of all search
terms used.
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Table 1. Search terms used in Google Play and Apple App Store.
Search terms usedConcept
audiogramAudiometry
audiology
audiometry
hearing exam
hearing check
hearing loss
hearing problem
hearing
hearing test
hear
pure tone audiometry
tympanometryTympanometry
ear
ear nose and throat
ENT
ear test
otolaryngology
middle ear
middle ear test
otoacoustic emissionsOtoacoustic Emissions
OAE
ABR
otoscopeOtoscopy
otoscopy
otorhinoendoscope
otolaryngoscope
Inclusion and Exclusion Criteria
App titles were initially screened for relevance to the
measurement of auditory function or ear examination. Apps
were excluded based on their title if it was clear that the app
was not applicable. For example, in a search of hearing test,
apps such as Phone, Dog Hearing Test, and Motorola Gallery
were excluded based on title. Those with relevant (eg, Hearing
Test) or ambiguous titles (eg, iCare Health Monitor) went
through a second screening, in which they were reviewed in
more detail using the descriptions in the app store and on the
app’s website. Apps were included if they were
self-administered or professionally administered tests of ear or
hearing function. Apps were excluded if they did not focus on
ear examination or audiological testing; they were not in
English; they were included in the category of games,
entertainment, or music; or they were intended for educational
purposes.
Literature Review of Smartphone Apps
Information Sources
Once the app store review was complete, a literature review
was conducted in July 2015 to assess app validity testing. 6
databases were searched for peer-reviewed studies related to
apps of ear and hearing function: PubMed/MEDLINE,
EMBASE, Global Health, Web of Science, CINHAL, and
mHealth Evidence. Comprehensive search terms for smartphone
apps and auditory function were identified through MeSH and
previous systematic reviews on similar topics. The names of
identified apps from the commercial review were also included
(see Multimedia Appendix 1). Developers of apps that were
validated in peer-reviewed literature were contacted if specific
information about the app was not available online.
Study Eligibility Criteria
Articles published between June 2007 and July 2015 were
included in the search to align with the time-period during which
apps have been available [17]. Any primary study identified in
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the app stores’ review that compared an app to gold standard
methods was considered for inclusion. Studies that measured
outcomes that allowed judgement of the app’s performance
were included. These outcomes included: sensitivity, specificity,
negative and positive predictive values, difference in pure-tone
thresholds, and kappa diagnostic agreement. No restrictions
were placed on study location, or types of participants included
in the studies. Studies were excluded if they were not in the
English language, or the study was not peer-reviewed. This
review focused on the validity of apps available for download
from commercial app stores. If the article did not specify the
name of the app, or if the app being studied was not previously
identified in the app stores’ review, the author was contacted
for further information about the app and its availability. The
article was included if the author could provide the app’s name
and the app was available for purchase, either on Google Play,
the Apple App Store, or elsewhere.
Study Selection
Articles were screened by two reviewers (TB and DP) first by
titles, then abstract, and finally by full paper to determine
eligibility.
Data Extraction
Data was extracted from eligible studies for the following study
components:
1. Methods, including study design, comparison being made
(ie, index test [app] and reference test [gold standard]), single
or multiple smartphone devices used, headphone/transducer
type, calibration methods, and test frequencies.
2. Participants, including age, sex, and sample size.
3. Study location, including country and setting.
4. Publication details, including year, journal, and declaration
of conflicts of interest.
5. Outcomes, including type of outcome, definitions (eg,
definition of hearing loss).
6. Results, including relevant measure of validity.
All data was extracted by one reviewer (TB), and checked by
the second reviewer (DP) to ensure accuracy.
Methodological Quality of Studies
Methodological quality for each study was assessed using the
Quality Assessment for Diagnostic Accuracy Studies
(QUADAS-2) tool [18,19]. This tool assesses the following 4
domains:
1. Patient selection: assessment of study design, sampling
method, and selection criteria.
2. Index test (app): assessment of chosen test (app), testing
method, and interpretation.
3. Reference standard: assessment of choice of reference
standard and interpretation.
4. Flow and timing: assessment of time interval between index
and reference tests, proportion of sample receiving reference
standard, and proportion of participants included in the analysis.
Each domain was assessed in terms of risk of bias, and the first
three domains were assessed in terms of concerns regarding
applicability to the review question. Risk of bias and concerns
regarding applicability were scored as low, high, or unclear
using a series of signalling questions. If each signaling question
had an answer of, “yes,” the domain was rated as having a low
risk of bias or low concern of applicability. If any signaling
question was answered, “no,” the domain was scored as high
risk of bias or high concern of applicability. If any domain
provided inadequate information to make a judgement, the
domain was scored as, “unclear.” Each paper was reviewed
independently for quality by two reviewers (TB and DP).
Synthesis of Results
Results from the literature review were synthesized using a
narrative approach, rather than a meta-analysis, due to the
heterogeneity of included studies.
Results
Google Play and Apple App Store Review
Over 1000 apps were reviewed in the searches of Google Play
and the Apple App Store, 30 of which met the inclusion criteria
(Figure 1). Of these, 17% (5/30) were Android (Google) apps,
70% (21/30) were iOS (Apple) apps, and a further 13% (4/30)
were compatible with both Android and iOS. Considering the
function of the apps, audiometry apps formed the majority, with
26 of the 30 (87%) functioning as either self-administered
automated PTA or professionally administered PTA. The
remaining apps (4/30, 13%) were designed for performing
otoscopy and required a separate specula phone attachment. No
apps for tympanometry, OAEs, or ABR were identified. Details
of the identified apps can be found in Multimedia Appendix 2.
Literature Review of Smartphone Apps
Search Results
The literature review yielded 534 results: 182 in EMBASE, 157
in MEDLINE, 153 in Web of Science, 21 in CINAHL, 13 in
Global Health, and 8 in mHealth Evidence. After removing
duplicates across search engines, and screening titles and
abstracts for relevant articles, 22 studies remained. Full text
article screening resulted in 7 eligible studies. Three studies
were excluded, as the app under study was not specified.
Attempts were made to contact the authors of these papers for
further information; however, this was not successful. Four
additional studies were identified from reference lists of included
articles, resulting in the inclusion of 11 studies overall (Figure
2). One further article was identified through app website
review; however, the full text could not be located and therefore
this article was excluded.
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Figure 1. Flow diagram for apps found in app stores. Numbers are approximate due to limitations with the search platform (a=exact number of hits
not provided and thus manual counting conducted).
Figure 2. Flowchart of study selection process.
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Table 2. Characteristics of apps validated in peer-reviewed literature.
Additional featuresTransducer type
and model
CalibrationMaximum
testing out-
put (deci-
bels)
Test fre-
quency
(kilo-
hertz)
Cost (US $)a
App functionApp and op-
erating sys-
tem
Noise monitoring,
data storage with
user identification,
and questionnaire
to evaluate the im-
pact of hearing loss
Air conduction
(AC), standard ap-
ple headphones;
bone conduction
(BC), not mea-
sured
Calibrated with stan-
dard Apple head-
phones using refer-
ence equivalent
threshold sound pres-
sure levels for TDH39
headphones (ISO389-
1)
900.25, 0.5,
1, 2, 4, 6
Freeb
Self-administered
audiometry app
uHear, iOS
Noise monitoring,
masking (auto cal-
culated), and data
management
(cloud)
AC, TDH-39 or
EAR 3A insert
headphones; BC,
B-71 bone transduc-
er
Calibrated with audio-
metric transducers us-
ing American Nation-
al Standards Institute
S3.6-2004 standards
90-1150.25, 0.5,
1, 2, 4, 6,
8
Humanitarian
$2000c, standard
version $3100c, pro-
fessional version
$4100c
Self- or tester-ad-
ministered au-
diometry app
shoeBOX
audiometry,
iOS
Ability to export
results as a photo-
graph to photos
app, and integrated
with Print, Mail,
and WhatsApp
AC, Apple head-
phones; BC, not
measured
Calibrated for most
models of iPhone/iPad
using Apple head-
phones (standards not
specified)
750.5, 1, 2,
3, 4, 8
$1.99b
Tester-adminis-
tered audiometry
app
AudCal, iOS
Noise monitoring,
data capturing and
sharing, and loca-
tion-based referral
AC, Sennheiser
HD202 head-
phones; BC, not
measured
Calibrated with
nonaudiometric head-
phones according to
ISO389-1-specified
standards (within 0.1
decibel accuracy)
401, 2, 4
$600d
Tester-adminis-
tered screening
audiometry app
(ie, pass/fail re-
sult)
hearScreen,
Android
Data storage, auto-
mated masking
noise, and amplifi-
cation device
AC, commercially
available earbuds
(eg, standard Ap-
ple headphones);
BC, not measured
Calibrated with Ap-
ple’s earbuds (stan-
dards not specified)
90-1000.25, 0.5,
0.75, 1,
1.5, 2, 3,
4, 6, 8
$3.99b
Self-administered
audiometry app
EarTrumpet,
iOS
Port for pneumatic
otoscopy
N/AN/AN/ANot appli-
cable
(N/A)
$79efor iPhone
case, otoscope attach-
ment, 4 reusable
specula
Otoscopy app
with separate at-
tachment
CellScope,
iOS
aSubject to change.
bPrice excludes cost of device and transducers.
cPrice includes transducers, software, and first year’s calibration. Price excludes the price of the iPad.
dPrice includes device, transducers, and calibration.
ePrice excludes cost of device.
Results of Included Studies
Of the 30 apps found in the review of the app stores, 5 appeared
in validation studies in the peer-reviewed literature. These apps
were uHear, shoeBOX audiometry, EarTrumpet, CellScope,
and AudCal. One study was identified in the literature that
validated an Android hearing screening app, hearScreen, that
is not yet commercially available on Google Play. Thus, 6
previously validated apps were identified in the review. Of these
apps, the function of 4 was self- or tester-administered PTA
(uHear, shoeBOX audiometry, AudCal, and EarTrumpet), one
performed screening audiometry (hearScreen; pass/fail result),
and one functioned as video otoscope (CellScope).
Table 2 provides a summary of the validated apps and their
specific characteristics, including function, costs, test
frequencies, maximum output, calibration method, recommended
transducers, and administration method.
Overview of Study Characteristics
The 11 selected studies are summarized in Multimedia Appendix
3by study setting, study design, participants/sample and sample
size, index (app) and reference test (gold standard), transducers
and devices used, test administration method (eg, self- or
tester-administered), outcome measures, calibration method,
and results. Studies were performed in Canada (n=3) [20-22],
Spain (n=1) [23], Israel (n=2) [24,25], USA (n=2) [26,27], and
South Africa (n=3) [28-30]. The sample size of the included
studies ranged from 25 to 110 participants. Participants in the
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included studies came from a range of age groups: adults (>18
years; n=4) [21,23,24,27], the elderly (>65 years; n=1) [25],
children (<18 years; n=5) [20,26,28,30], and both children and
adults (15-80 years; n=1) [29].
All included studies used a within-subjects’ study design. Ten
of the 11 studies focused on comparing audiometry apps to
conventional PTA [20-25,27-30], while the remaining study
compared the diagnosis made with an otoscope app to traditional
otoscopy [26].
Of the 10 studies validating audiometry apps, the majority
carried out testing with the app in a quiet room (ambient noise
levels 40-50 A-weighted decibels [dBA]; n=7) [21,24,25,27-30].
The remaining studies were performed only in a soundproof
room (ambient noise <40 dBA; n=3) [20,22,23]. Three studies
performed testing in multiple environments to determine the
effect of ambient noise on test accuracy [21,27,29]. In terms of
outcome measures, most studies (6/10, 60%) performed
sensitivity and specificity analyses with defined pass/fail dB
cut-offs [20-22,24,25,29]. The remaining studies (4/10, 40%)
used alternative outcome measures, including the mean
difference in thresholds between the app and conventional PTA
[23,27,28,30]. Validation of audiometry apps in all 10 studies
focused on the comparison of air conduction (AC) thresholds
only, as opposed to including bone conduction (BC) threshold
as well. In the single study validating the otoscopy app, Cohen’s
kappa agreement was used to determine diagnostic agreement
with traditional otoscopy [26].
Summary of Main Results
Audiometry Apps
Of all the apps reviewed in the literature, uHear has been
validated in the most studies, none of which declared a conflict
of interest (n=5). Results from 3 of the 5 studies on uHear
suggest that when screening for moderate or worse DHI (PTAv
>40 decibels Hearing Level [dBHL]) in adults, a high sensitivity
(ranging from 98.2-100%) was achieved; however, specificity
was variable (ranging from 60.0-82.1%) if tests were conducted
in environments with ambient noise floor at 40-50 dBA (quiet
room) [21,25,29]. Ambient noise levels had significant impacts
on the accuracy of uHear [21,29]. Sensitivity remained high in
all test settings; however, specificity decreased in a waiting
room setting (ambient noise >50 dBA) and increased when
conducted in a soundproof room (ambient noise <40 dBA) [29].
Two studies concluded that uHear cannot accurately determine
the precise level of hearing impairment as compared to
conventional PTA, suggesting that the app could be used for
screening, but not diagnostic purposes [21,25].
Two validity studies compared shoeBOX audiometry to standard
pediatric audiometry, both of which declared a conflict of
interest [20,22]. Sensitivity in these studies ranged from
91.2-93.3% and specificity ranged from 57.8-94.5%, depending
on transducers used and test environment [20]. Individual
validity studies were identified for EarTrumpet, AudCal, and
hearScreen, each declaring a conflict of interest. Hearing
thresholds obtained with EarTrumpet and AudCal were found
to be within 10 dBHL of conventional PTA, on average [23,27].
hearScreen, a screening app that gives a pass/refer result, was
found to have comparable referral rates to conventional
screening audiometry [30].
Otoscopy Apps
Only one study focused on validating an otoscopy app. This
study compared the diagnosis obtained using traditional
otoscopy to that obtained using the iPhone otoscope, CellScope
(n=54) [26]. This study found high levels of agreement between
the two diagnostic methods. Refer to Multimedia Appendix 3
for further details of the study results.
Table 3. Summary of quality review of included studies (assessed using the QUADAS-2 tool) where 1 represents low risk of bias/low concern of
applicability, 2 represents unclear/inadequate information to make judgement, and 3 represents high risk of bias/high concern of applicability.
Applicability concernsRisk of biasStudy authors (year)
Reference
Standard
Index TestPatient Selec-
tion
Flow and
Timing
Reference
Standard
Index TestPatient
Selection
1131113Abu-Ghanem et al (2015) [25]
1111113Khoza-Shangase et al (2013) [28]
1113111Peer et al (2015) [29]
1111112Szudek et al (2012) [21]
3331133Handzel et al (2013) [24]
1111111Foulad et al (2013) [27]
1113111Yeung et al (2013) [20]
1113131Yeung et al (2015) [22]
1111111Larrosa et al (2015) [23]
1111113Swanepoel et al (2014) [30]
1111133Richards et al (2015) [26]
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Methodological Quality of Included Studies
Of the 11 peer-reviewed studies included in this review, 2
achieved a rating of low risk of bias and low concern of
applicability in all domains [23,27]. The main source of bias in
the included studies was selection bias. Results of the quality
assessment are summarized in Table 3 and detailed in
Multimedia Appendix 4.
Discussion
Screening for hearing impairment is not feasible for many
LMICs, mainly due to the dearth of skilled professionals
available to conduct the required tests and high costs of specialist
equipment. However, the increasing availability of apps provides
an opportunity to integrate their use into screening for ear and
hearing conditions in a cost effective and mobile way. This
paper provides a comprehensive summary of the currently
available apps for ear and hearing assessments (up to July 2015)
and provides a summary of those that have been validated
against gold standard measures.
Thirty commercially available apps meeting the inclusion criteria
were identified on Google Play and the Apple App Store. Of
these, only 5 had undergone validation, as per the peer-reviewed
literature (Table 2). One additional peer-reviewed validation
study referred to an Android app that is not yet available
commercially. The vast majority of apps identified in the initial
commercial review have not been validated against a gold
standard measure in peer-reviewed literature. Most of the
available apps were designed to perform audiometry (26/30,
87%) with a small proportion for otoscopy (4/30, 13%). No
apps were identified for conducting OAEs, ABR, or
tympanometry.
The literature review identified 11 peer-reviewed validation
studies. Studies were quite heterogeneous, with variation in the
cut-off level for performing sensitivity/specificity analyses,
patient population, units of analysis (results of each ear
separately or individual), and exclusion/inclusion criteria for
participants, thus making direct comparisons across apps
difficult. The quality of included studies was variable, with only
2 studies achieving a low risk of bias and low concerns about
applicability in all domains (Table 3). Five peer reviewed studies
were identified on uHear; however, the accuracy results varied
considerably across these studies (Multimedia Appendix 3)
[21,24,25,28,29]. A specificity as low as 60%, found by
Abu-Ghanem et al in a quiet room setting, would result in a
high rate of false positives in a screening program, and thus an
unnecessary rate of referrals for diagnostic assessments, which
would increase the burden on already strained health services
[25]. The small sample sizes and the limited variability in degree
and types of hearing loss included in the studies on uHear may
limit generalizability based on the studies reviewed. Individual
peer-reviewed validation studies were identified for AudCal,
hearScreen, EarTrumpet, and CellScope [23,27,30]. Although
the results of these studies appear to be promising, there is
limited evidence to allow robust conclusions to be drawn.
Several studies demonstrated that the testing environment had
a significant impact on the accuracy of results [21,27,29]. This
finding is important, as ambient noise levels in screening
environments are a substantial challenge and can often exceed
the recommended minimum of 40 dBA [7]. Studies of
audiometry apps focused on comparison with AC thresholds
only, reinforcing the fact that these apps function as screening
(rather than diagnostic) tools. BC testing is important for
differentiating between conductive and sensorineural hearing
loss; however, shoeBOX audiometry that runs on an iPad device
is currently the only app compatible with BC transducers. Thus,
the validity of BC testing from smartphone devices warrants
further investigation. The range of frequencies that are tested
in the current audiometry apps does not typically extend to 8000
Hz, thus screening for certain conditions such as ototoxicity
and noise-induced hearing loss would not be possible with
current app technology.
Most studies conducted tests using a single device and
transducer; however, in reality there may be significant
variability in results obtained with different transducer/device
combinations due to issues with calibration. Annual calibration
of audiometric devices is a key consideration to ensure test
accuracy. Of 10 audiometry studies, only half performed
calibration as part of their study [20,22,23,27,30]. This finding
may be due to the fact that no standardized calibration procedure
currently exists for performing tests on smartphone devices
coupled with nonaudiometric headphones [30]. Several recent
studies have investigated calibration methods; however, further
research evidence is necessary [31,32]. Some authors suggested
that poor sound attenuation provided by commercially available
earbuds might have resulted in the poor accuracy of results
found in nonsoundproof environments. Accuracy may improve
if headphones with greater attenuation of ambient noise are
utilized. However, the cost of these types of headphones can be
prohibitive and calibration is still an important issue.
Audiometric headphones adhering to International Organization
for Standardization calibration standards (ISO389-9:2009) are
vastly more expensive than commercially available headphones.
Nonaudiometric supraaural headphones may assist in providing
some attenuation from ambient noise. Swanepoel et al
determined that Sennheiser HD202 headphones coupled to a
smartphone hearing screening device can be calibrated to a
professional standard using TDH-39 Reference Equivalent
Threshold in Sound Pressure Levels as a reference [30]. Thus,
it seems possible to use lower-cost transducers whilst ensuring
test accuracy. The expertise required to professionally calibrate
audiometric devices is often nonexistent in low resource settings,
and equipment can remain out of calibration for lengthy periods.
Hence, ongoing calibration is an additional challenge for
performing accurate screening of hearing loss using apps.
Although the cost of the apps themselves are low (indeed many
are free; Multimedia Appendix 2) additional costs are incurred
for the device, headphones, and regular calibration. Android
devices are often much less expensive than Apple products and
more widely available in LMICs; however, the vast majority of
available apps identified in this review were designed for Apple
devices. Some of the apps identified in the literature search
(shoeBOX audiometry, and hearScreen) are sold as a package
including headphones, calibration for the first year, and the
device (hearScreen). Although these apps appear to be
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higher-cost, these features allow for a level of quality control
that is not currently available for apps that can be downloaded
from app stores and used on various device/transducer
combinations.
Strengths and Limitations
This review has several strengths. Comprehensive search terms
were identified and applied across multiple electronic databases
to reduce publication bias. A clear approach to searching,
screening, reviewing, and extracting data was performed
independently by two reviewers. Citation bias was minimized
by reviewing references of included studies. Thus, the search
strategy of peer-reviewed literature is not likely to be a
significant limitation.
The search of app stores was conducted using a range of search
terms and the most commonly used commercial app stores were
searched; however, this search had several limitations. First,
unlike searches of academic databases, app store searches do
not allow complex search functions such as Boolean operators
or the searching of phrases such as, “hearing test.” Second,
search engines did not provide the total number of hits for each
search. Therefore, an estimation had to be made of the total
number of apps reviewed (>1000). In addition, app store
categories may not always reflect the true nature of the app,
implying that some relevant apps (ie, those in the category of
games) may have been missed. Furthermore, the range of search
terms used may not have been fully exhaustive. For instance,
alternative screening tools for hearing loss, such as self-reported
questionnaires, were not included in the search. Finally, if time
and resources permitted, each app would have been downloaded
and tested to assess eligibility. However, this was not feasible
within the scope of this study. Thus, assessment of the apps’
eligibility proved difficult in some instances if limited or vague
information about the app was provided on the app stores. Given
these limitations, the search of the app stores may not have been
fully exhaustive, despite the range of search terms utilized and
the predefined eligibility criteria.
In addition to the limitations in the app store search, given the
rapid pace of app development and lengthy publication process,
it might have been appropriate to broaden the search to include
grey literature (eg, reports, conference papers). However, given
the lack of peer review of grey literature sources, the decided
methodology was justified. Finally, the review is based on an
electronic search, which was completed in July 2015, and as
such the review may not be entirely up-to-date.
Future Research
This review has identified a need for further research, as many
of the commercially available apps have not been validated
against gold standard measures. Furthermore, many of the
validated apps were not studied independently. Thus, further
independent validation studies are needed for each available
app for ear and hearing assessments. Studies providing a
comparison of the accuracy between available audiometry apps
would also be useful. The utility of telemedicine techniques,
such as video otoscopy using otoscopy apps such as CellScope,
could be investigated in field studies. These techniques would
involve an offsite ENT, negating the need for such a specialist
to be present with the patient, to help deal with the substantial
human resource shortage. This additional evidence would assist
in making a clear evidence-based decision about which of the
apps, if any, could be recommended to be used for screening
of ear and hearing conditions.
Most studies in this review focused on populations in high
income countries, in which the need for validated smartphone
apps still exists; however, we focused on screening for hearing
impairment in low-resource settings. This discrepancy highlights
the need for further research evidence for populations with DHI
living in LMICs, where the greatest burden exists [2]. Finally,
it is important to regularly update this review and monitor further
app developments, especially for suitable apps to test pediatric
populations and those who cannot perform PTA.
Conclusions
There are a number of apps available for ear and hearing
assessments; however, very few have been validated in
peer-reviewed literature. Of the apps that have been validated,
further independent research is required to fully understand their
accuracy for detecting ear and hearing conditions. Given the
results of this review, audiometry apps cannot be recommended
to replace gold standard PTA conducted by an audiologist.
However, despite the limited evidence obtained in this review,
the portability, accessibility, self-administration, and low-cost
nature of ear and hearing apps still offer an exciting opportunity
to overcome the key barriers to screening for ear and hearing
conditions in LMICs.
Acknowledgments
We thank Dr Hannah Kuper, Islay MacTaggart, and Dr Silvia Ferrite for providing thoughtful feedback during the preparation
of the manuscript.
Conflicts of Interest
None declared.
Multimedia Appendix 1
Search strategy for EMBASE.
[PDF File (Adobe PDF File), 28KB - rehab_v3i2e13_app1.pdf ]
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Multimedia Appendix 2
Summary of apps identified on Google Play and AppStore reviews.
[PDF File (Adobe PDF File), 48KB - rehab_v3i2e13_app2.pdf ]
Multimedia Appendix 3
Summary of selected peer-reviewed studies included in the review.
[PDF File (Adobe PDF File), 78KB - rehab_v3i2e13_app3.pdf ]
Multimedia Appendix 4
Risk of bias of included studies.
[PDF File (Adobe PDF File), 32KB - rehab_v3i2e13_app4.pdf ]
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Abbreviations
ABR: Auditory Brainstem Response
AC: air conduction
BC: bone conduction
dB: decibel
dBA: A-weighted decibels
dBHL: decibels Hearing Level
ENT: ear, nose, and throat
HIV: human immunodeficiency virus
Hz: Hertz
LMIC: low- and middle-income country
OAE: Otoacoustic Emissions
PTA: Pure Tone Audiometry
PTAv: Pure Tone Average
QUADAS-2: Quality Assessment for Diagnostic Accuracy Studies
WHO: World Health Organization
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Edited by G Eysenbach; submitted 23.06.16; peer-reviewed by A Paglialonga, O Handzel, F Mahomed-Asmail, S Moodie; comments
to author 23.08.16; revised version received 15.09.16; accepted 29.10.16; published 23.12.16
Please cite as:
Bright T, Pallawela D
Validated Smartphone-Based Apps for Ear and Hearing Assessments: A Review
JMIR Rehabil Assist Technol 2016;3(2):e13
URL: http://rehab.jmir.org/2016/2/e13/
doi:10.2196/rehab.6074
PMID:28582261
©Tess Bright, Danuk Pallawela. Originally published in JMIR Rehabilitation and Assistive Technology (http://rehab.jmir.org),
23.12.2016. This is an open-access article distributed under the terms of the Creative Commons Attribution License
(http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work, first published in JMIR Rehabilitation and Assistive Technology, is properly cited. The complete
bibliographic information, a link to the original publication on http://rehab.jmir.org/, as well as this copyright and license information
must be included.
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