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

Abstract

Introduction

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

Methods

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

Results

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

Discussion

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

Keywords

Mass screening hearing loss child audiometry pure-tone telemedicine

Introduction

The World Health Organization (WHO) estimates that over 5% of the world’s population suffers from disabling hearing loss.¹ When mild hearing loss is considered, the estimates increase to approximately 10%.^2–4

Furthermore, estimates indicate that 34 million children have disabling hearing loss.¹ Each year, approximately 798,000 new borns are diagnosed with congenital permanent hearing loss, and over 90% of these children reside in developing countries.^1,2,5–10

In addition to permanent hearing loss, otitis media (OM) is one of the most common pathological conditions in childhood. Approximately 80% of children suffer at least one episode of transient hearing loss annually due to OM.¹¹ Chronic OM might be considered the main cause of mild to moderate hearing loss;^12–14 its global prevalence varies from 1 to 46% according to the geographical region and population.^12,15–17

Permanent and transient hearing losses have a negative impact on the development of speech and language and on school performance.^1,17–20 Early detection and intervention are crucial to minimizing the impact of hearing loss on a child’s development and educational achievements.¹

It should be emphasized that half of the causes of childhood hearing loss can be prevented by well-known and proven methods.^9,21 Sufferers typically exhibit few symptoms, so hearing loss often passes unnoticed by those close to the affected children. Therefore, to minimize the adverse effects of hearing loss, hearing screenings and assessments should be performed routinely to facilitate the early detection of abnormalities.^22,23

Despite the abundant evidence for the negative consequences of hearing loss in children, many developing countries lack well-established screening programmes²⁴ because of a lack of hearing health services and an unequal distribution of specialists.^3,10,25–28

As a rule, a diagnosis of hearing loss is based on a conventional audiological evaluation, including pure-tone audiometry, which is considered the gold standard for determining hearing thresholds.^3,29,30 Audiometry is usually performed with a standard nonportable clinical audiometer, which could thus represent a limitation on access to hearing evaluations.^30,31

Telehealth applications in audiology have been developed that aim to improve access to hearing health services and increase the efficiencies of existing systems.^{4,10,26,28,29,32,33} Using telehealth applications, these barriers, such as the lack of specialized professionals, lack of equipment or difficulty using nonportable equipment, can be overcome, improving the access to, quality of and effectiveness of services, as well as reducing costs.^4,34

However, before these applications can be used, they must be clinically validated.³¹ Therefore, studies that propose and validate new methods for locations in which access to conventional audiometry is difficult, particularly in developing countries, are justified.

The aim of this study was to assess the performance of a tablet-based tele-audiometry method for the automated hearing screening of schoolchildren by comparing the results of several approaches to hearing screening (exclusively tablet-based – with and without 500 Hz included, and combined tests – series and parallel) with gold-standard pure-tone audiometry.

Methods

The study was approved by the research ethics committee of the institution (n.088/2014). All parents/guardians authorized the participation of their children by providing consent, and in addition, all children gave assent to participate.

Participants

Children attending an elementary regular school in the neighbourhood of the University of São Paulo, Brazil, participated in the study. The sample consisted of 244 children (49.6% female; 50.4% male) aged six to 12 years (mean: 8.95; SD = 4.24). The sample calculation indicated the need for a minimum sample size of 215 children. The calculation was carried out using the following sample size formula:³⁵

N= \frac{Z^{2} (P (1 - P))}{d^{2}}

where n = sample size, Z = Z statistic for a level of confidence, P = expected prevalence or proportion, and d = precision (α = 0.05; confidence interval (CI) 95%).

Data collection was performed at the school during class hours. The room in which the evaluation was performed was one of the school’s quietest, and the noise level was monitored using an application on a tablet throughout the data collection period (NoiSee, EA Lab, Ljubljana, Slovenia). Whenever noise exceeded the levels permitted by ANSI standard S3.1³⁶ (i.e. 49.5 dB SPL at 1000 Hz, 54.5 dB SPL at 2000 Hz and 62 dB SPL at 4000 Hz), the tests were stopped.

The participants met the following inclusion criteria: no foreign bodies and/or excess wax in the ear canals and the ability to understand the instructions for the procedures.

Procedures

Ear canal otoscopy to assess the statuses of the ear canal and tympanic membrane was performed. In cases of excess of earwax, the children were referred to an otorhinolaryngologist from the public national healthcare system, and following removal of the earwax, they received the evaluation.

Automated hearing screening was completed using an Apple iPad^® tablet computer in a non-acoustically treated room. Specifically, the P.E.T.I.T. (Programa de extensão de triagem infantil por tom) application³⁷ was used with TDH39 headphones (Telephonics Corporation, NY, USA). The P.E.T.I.T. app was developed by the researchers of this study in 2014, and a formal description of it can be found in the paper by Samelli et al. (2017).³⁷ The application performs pure-tone screening using a yes/no two-alternative forced choice task. In the task, a visual presentation of stimuli is randomly combined with sounds (i.e. calibrated warble tones) or silence. The expected answers require a motor response of touching the figure that appears on the tablet screen and then dragging and moving the figure to a specific icon depending on other conditions (i.e. the presence or absence of a sound stimulus). The results were automatically recorded by the tablet according to pass/fail criteria. ‘Pass’ was defined as at least two out of three responses to the emitted sounds for all frequencies^38,39 at 20 dB HL for 1000, 2000 and 4000 Hz and 30 dB HL for 500 Hz in each ear. The calibration met international standards.^40–45 All the test results were stored on the tablet and were transmitted to a central database via private, secure Wi-Fi at the university without the need for internet connectivity in the room in which the screenings were conducted (store-and-forward telehealth).

Conventional pure-tone audiometry was conducted in an acoustically treated room to establish the air conduction thresholds of each ear separately at 500, 1000, 2000 and 4000 Hz (Maico MA-41 audiometer; TDH39 headphones). If the air conduction threshold was equal to or greater than 20 dB HL, then the bone conduction threshold was also measured at the same frequency. Abnormal hearing thresholds were defined as being over 20 dB HL.³⁹ Abnormal cases were classified according to the hearing loss type (i.e. conductive, sensorineural or mixed)⁴⁶ and degree (21–40 dB HL: mild, 41–70 dB HL: moderate, 71–90 dB HL: severe and >91 dB HL: profound; based on the average threshold).⁴⁷

Acoustic immittance measurements (tympanometry; ipsilateral acoustic reflex testing at 100 dB and 500–4000 Hz) were performed to analyse the middle ear (Otoflex 100, Madsen). The tests were automatically performed by the testing device. Tympanogram types B, C, Ad and As and an absence of acoustic reflexes were considered failures.^48,49

All the procedures were performed at the school on the same day by a team of audiologists from the University of Sao Paulo who were trained for this screening protocol. Each procedure was applied only once to each child according to the order described above.

Data analysis

To characterize hearing thresholds, the prevalence of hearing loss was described according to the age range (CI 95%), and proportions of participants with normal hearing thresholds or hearing loss were compared according to sex (difference between two proportions hypothesis testing).

Based on the screening results, the participants were divided into two groups (pass or fail) according to the described criteria. The groups were compared to the results – normal or abnormal – of conventional pure-tone audiometry (the gold standard). Based on this comparison, the following measures were calculated: sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio and accuracy.

To analyse the various approaches to hearing screening, the following comparisons were performed:

Result of binaural tablet screening (including and excluding 500 Hz) v. result of binaural conventional audiometry.

Result of serial screening (including and excluding 500 Hz) v. result of binaural conventional audiometry (Figure 1).

Figure 1.

Flow chart: serial approach.

Result of parallel screening (including and excluding 500 Hz) v. result of binaural conventional audiometry (Figure 2).

Figure 2.

Flow chart: parallel approach.

For each approach (tablet, serial or parallel screening), the sensitivity was defined as the percentage of individuals whose results were ‘fail’ in the screening among those who presented with abnormal conventional audiometry. The specificity was defined as the percentage of individuals whose results were ‘pass’ in the screening and who had normal conventional audiometry. The PPV was defined as the probability of an individual presenting with abnormal audiometry being among the individuals with a ‘fail’ result in the screening, while the NPV was defined as the probability of an individual presenting with normal audiometry being among those with a ‘pass’ result in the screening. Accuracy was measured as the sum of the true-positive and true-negative cases over the total number of cases. In the case of serial and parallel analyses, the same criteria defined above were employed, but a combination of two instruments (tablet and/or immittance testing) was used. The serial analysis considered the result of the tablet assessment and, for those who failed, the result of immittance testing as well; in this case, a child ‘failed’ the screening only if they failed in both instruments (increased specificity). For the analysis in parallel, the results of both instruments were considered simultaneously; in this case, a child ‘passed’ the screening only if they passed both assessments (increased sensitivity).

Finally, based on the sensitivity and specificity obtained for each screening approach, ROC (receiver operating characteristic) curves were plotted to compare the performances between various approaches. In addition, the AUC (area under the curve) was calculated to verify if two or more ROC curves were significantly different. An AUC above 0.70 is considered satisfactory. The 95% CIs and significance levels were described for the paired comparison of curves (DeLong method).

The statistical analysis was performed using SPSS version 21 and MedCalc version 17.0.4. A signiﬁcance level of 5% was used.

Results

Of the 244 children included in the study, 23 (9.43%) exhibited hearing loss, without a difference between boys and girls observed (p-value: 0.210; difference between two proportions hypothesis testing). All the children with abnormal results on the audiological evaluations exhibited conductive hearing loss. In 15 of these children (65.21%), the hearing loss was one-sided and mild, and in seven children (30.44%), it was bilateral and mild. Only one child (4.35%) exhibited moderate hearing loss in one ear and mild hearing loss in the other. The prevalence of hearing loss by age range is presented in Table 1.

Table 1.

Prevalence of hearing loss by age range.

Age range(years)	N	N with hearing loss	Percent with hearing loss (95% CI^a)
6–7	33	5	15.15 (6.65–30.92)
8–9	123	11	8.94 (5.07–15.31)
10–12	88	7	7.95 (3.91–15.52)
Total	244	23	9.43 (6.36–13.75)

CI: confidence interval.

A comparison of all the investigated screening approaches (Table 2) showed that the highest sensitivity values were observed in tablet-based and parallel screening. The two serial approaches exhibited the highest specificity values. The highest accuracy levels were found for the two serial approaches, followed by the tablet-based screening.

Table 2.

Summary of the sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+) and accuracy (A) of all investigated approaches considering conventional audiometry as the gold standard.

Approach	Se (%)(95% CI)	Sp (%)(95% CI)	PPV (%)(95% CI)	NPV (%)(95% CI)	LR+(95% CI)	A (%)(95% CI)
Tablet	95.7(78.1–99.9)	81.0(75.2–85.9)	34.4(22.9–47.3)	99.4(96.9–100)	5.03(3.01–8.43)	82.4(77–86.9)
Tablet (excluding 500 Hz)	87.0(66.4–97.2)	81.0(75.2–85.9)	32.3(20.9–45.3)	98.4(95.3–99.7)	4.58(2.69–7.79)	81.6(76.1–86.2)
Serial	65.2(42.7–83.6)	91.4(86.9–94.7)	44.1(27.2–62.1)	96.2(92.6–98.3)	7.59(3.8–14.93)	88.9(84.3–92.6)
Serial (excluding 500 Hz)	60.9(38.5–80.3)	89.6(84.8–93.3)	37.8(22.5–55.2)	95.7(91.9–98)	5.85(3.0–11.37)	86.9(82–90.9)
Parallel	95.7(78.1–99.9)	44.8(38.1–51.6)	15.3(9.8–22.2)	99.0(94.6–100)	1.73(1.1–2.73)	49.6(43.2–56)
Parallel (excluding 500 Hz)	91.3(72–98.9)	46.6(39.9–53.4)	15.1(9.6–22.2)	98.1(93.3–99.8)	1.71(1.08–2.72)	50.8(44.4–57.3)

AUCs were calculated (Table 3) based on the ROC curves (Figure 3). The largest AUC was found for the tablet-based approach. A paired comparison showed that the AUC for the tablet-based approach differed significantly from that for most of the approaches (Table 4).

Table 3.

AUC and 95% CI results for all investigatedapproaches.

Approach	AUC	95% CI
Tablet	0.883	0.836–0.921
Tablet (excluding 500 Hz)	0.840	0.788–0.883
Serial	0.783	0.726–0.833
Serial (excluding 500 Hz)	0.752	0.693–0.805
Parallel	0.702	0.641–0.759
Parallel (excluding 500 Hz)	0.690	0.627–0.747

AUC: area under the ROC curve; CI: confidence interval.

Figure 3.

ROC curve of each investigated approach.

Table 4.

Paired comparisons (DeLong method) between AUC approaches.

Tablet–Tablet (excluding 500 Hz)
Difference between areas (95% CI)	0.0435 (−0.0190–0.106)
p-value = 0.1724
Tablet–Serial
Difference between areas (95% CI)	0.100 (0.00191–0.198)
p-value = 0.0457*
Tablet–Serial (excluding 500 Hz)
Difference between areas (95% CI)	0.131 (0.0280–0.234)
p-value = 0.0127*
Tablet–Parallel
Difference between areas (95% CI)	0.181 (0.149–0.213)
p-value < 0.0001*
Tablet–Parallel (excluding 500 Hz)
Difference between areas (95% CI)	0.194 (0.139–0.249)
p-value < 0.0001*
Tablet (excluding 500 Hz)–Serial
Difference between areas (95% CI)	0.0567 (−0.0521–0.165)
p-value = 0.3072
Tablet (excluding 500 Hz)–Serial (excluding 500 Hz)
Difference between areas (95% CI)	0.0874 (−0.00615–0.181)
p-value = 0.0671
Tablet (excluding 500 Hz)–Parallel
Difference between areas (95% CI)	0.138 (0.0700–0.205)
p-value = 0.0001*
Tablet (excluding 500 Hz)–Parallel (excluding 500 Hz)
Difference between areas (95% CI)	0.150 (0.0973–0.203)
p-value < 0.0001*
Serial–Serial (excluding 500 Hz)
Difference between areas (95% CI)	0.0308 (−0.0149–0.0765)
p-value = 0.1869
Serial–Parallel
Difference between areas (95% CI)	0.0809 (−0.0208–0.182)
p-value = 0.1189
Serial–Parallel (excluding 500 Hz)
Difference between areas (95% CI)	0.0935 (−0.00390–0.191)
p-value = 0.0599
Serial (excluding 500 Hz)–Parallel
Difference between areas (95% CI)	0.0501 (−0.0547–0.155)
p-value = 0.3490
Serial (excluding 500 Hz)–Parallel (excluding 500 Hz)
Difference between areas (95% CI)	0.0628 (−0.0388–0.164)
p-value = 0.2258
Parallel–Parallel (excluding 500 Hz)
Difference between areas (95% CI)	0.0127 (−0.0317–0.0571)
p-value = 0.5754

CI: confidence interval.* indicates statistical significance.

Discussion

Considering the prevalence of hearing loss worldwide and the global scarcity of hearing health services,^3,10,25–28 initiatives that seek to broaden the scope of action and improve access to hearing health have been developed through tele-audiology-based strategies.^{4,10,26,28,29,32,33}

In this study, 9.43% of the analysed children exhibited hearing loss, without a statistically significant difference according to sex, which is consistent with some recent studies showing that there is no higher prevalence for either sex.^50–53 All were cases of conductive hearing loss, mostly mild and either one-sided or bilateral, which is the most common profile observed in studies on the subject.^54–57

The results also showed that the prevalence of conductive hearing loss was lower among the older children, as found in other studies,^51,52,58,59 which is possibly associated with the decrease in the prevalence of OM that starts at five years of age.⁶⁰

Several studies have sought to assess tele-audiometry software or applications for automated audiometry that use tablets, smartphones or even remote audiometers by comparing the results of such methods to those of conventional audiometry. The results of most studies are expressed in dB HL relative to the difference in hearing thresholds obtained with both procedures.^{28,30,32,50,52,61–70}

Since the application assessed in this study was developed for screening and the results are expressed as pass/fail, the results were compared to those from studies that employed the same evaluation paradigm in children.

Overall, the highest sensitivity was found for tablet-based screening and the parallel approach (95.7% for both). In turn, the two serial approaches exhibited the highest specificity (91.4 and 89.6%), followed by tablet-based screening (81%).

Using a computer-based automated audiometry system for 500–4000 Hz, but with 40 dB HL as the criterion for hearing loss, researchers achieved 100% sensitivity and 49% specificity.⁶⁴ Following the exclusion of 500 Hz from the analysis, the sensitivity decreased to 78%, but the specificity increased to 92%. It is worth noting that this evaluation was performed in a school setting, in reasonably quiet rooms and with commercially available circumaural headphones.

A study performed with the ShoeBOX application in an acoustic booth found a sensitivity of 93.9% and a specificity of 94.5% using 25 dB HL as the criterion for hearing loss.³⁰ In another study using the same procedure but in a clinical care room without acoustic treatment,³¹ the authors compared the obtained diagnostic measures with previous research.³⁰ The authors excluded 500 Hz from the analysis and obtained a sensitivity 91.2% and a specificity 57.8%.³¹

One study assessed children aged three to seven years in low-noise rooms in schools with noise-cancelling headphones by means of an automated application at 1000, 2000 and 4000 Hz.⁵¹ The hearing loss criterion was 30 dB HL. The sensitivity values ranged from 33 to 95%, and the specificity values ranged from 15 to 100%; these diagnostic measures had higher values in the older children. The same procedures were used in another study of children aged three to six years old; the sensitivity was 37%, and the specificity was 92.6%.⁵⁰

In our study, most diagnostic measures were higher for all the tested approaches when 500 Hz was included. This finding does not agree with findings reported in the literature, where higher values were obtained following the exclusion of 500 Hz from the analyses. Those authors suggested environmental noise as a possible interfering factor.^30,64

The frequencies from 500 to 2000 Hz are the most relevant for speech recognition and should thus be included in hearing screening protocols. Studies have observed that in this type of procedure, 500 Hz might be influenced by environmental noise but have stressed that 15% of children with conductive hearing loss only failed when tested at this frequency.^46,71

In our study, we paid considerable attention to noise during the data collection (monitored using NoiSee). The data collection was stopped during recess and at other times when the environmental noise exceeded levels permitted by the standards.^38,39 Thus, we believe that the influence of this variable on the present results was not significant.

Based on our findings and the relevance of 500 Hz, we suggest including it in hearing screening programmes for schoolchildren. We also suggest controlling and monitoring environmental noise to attenuate its influence on false-positive results.

A comparison of the results of tablet-based screening including all frequencies (500–4000 Hz) – because the values of the diagnostic measures were the highest – to the results in the cited literature^{30,31,50,51,64} showed that, except for the results reported by McPherson,⁶⁴ the sensitivity in the tablet-based approach was the highest at 100%. These findings demonstrate the high quality of the tool assessed in this study for the identification of true-positive cases.

According to the American Academy of Audiology (AAA), to be acceptable, hearing screening protocols should exhibit 90–95% sensitivity and specificity. The sensitivity of the instrument assessed in this study met this criterion.³⁹

However, the specificity of the tested instrument was 81% and thus below the level recommended by the AAA.³⁹ Regarding the three studies^31,50,64 that achieved a higher specificity, it should be noted that the first (92% specificity) did not include 500 Hz in the analysis, the second (94.5% specificity) was performed in an acoustic booth and a controlled hospital environment, and the third used hearing thresholds over 30 dB HL as the hearing loss criterion. These factors may have interfered with the results, contributing to a more precise identification of true-negative cases, therefore resulting in higher specificity values.

The negative predictive value obtained in this study was the highest found compared to those in some other studies.^30,31,50,64 This finding indicates high reliability when the individuals passed the screening, suggesting a prediction of the absence of hearing loss with 99% certainty.

Several screening approaches were analysed. For the serial approach, the diagnostic measures were as follows: sensitivity of 65.2%, specificity of 91.4% and accuracy of 88.9%. As expected, the specificity increased but the sensitivity decreased. When a similar approach to ours was applied,⁷² the obtained diagnostic measures had a sensitivity of 50%, a specificity of 97% and an accuracy of 89%. Therefore, the accuracy was similar to that found in this study.

Other authors also applied serial approaches to hearing screening, although with different combinations of procedures (parent questionnaires, otoscopy and immittance testing). In such studies, specificity values ranged from 58 to 86%. Thus, the specificity found in this study was the highest.^23,55

However, diagnostic measures should not be considered in isolation; the cost of screening should be taken into account, particularly when combinations of tests are used. The inclusion of immittance testing might increase the cost of hearing screening because specific equipment and audiologists are required to complete the assessments in those who fail tablet-based screening. Nevertheless, the number of false-positive cases is probably lower, thus reducing the indirect costs of screening associated with referrals (e.g. transportation, parents missing work, unnecessary procedures and tests).^23,72,73

For the parallel approach, there was an expected increase in sensitivity (95.7%). However, the specificity decreased to 44.8%. Previous studies tested combinations of tests in parallel, albeit employing other procedures (i.e. parent questionnaires, otoscopy and tympanometry), and obtained different sensitivity results, for example, 76%⁵⁵ and 95–97%.²³ One study that performed computer-based automated screening combined with immittance testing obtained a specificity of 98%.⁷²

We stress that differences in methods and cut-off criteria might account for discrepancies among results. However, independent of the values found for the combination in parallel and despite the beneficial increase in the identification of true-positive cases, this approach substantially increases the cost of screening because all individuals are subjected to all the screening procedures.^23,72,73

In the analysis of the diagnostic measures of screening methods, the AUC is also relevant because it simultaneously considers the sensitivity and specificity. The paired comparison of AUCs is also important because it facilitates the detection of possible differences. In this regard, tablet-based screening had a larger AUC, and a paired comparison (with the inclusion of 500 Hz) revealed a significant difference relative to all the other investigated approaches. Therefore, considering the diagnostic measures and the AUC comparison, we might infer that the protocol that yielded the most consistent results was tablet-based hearing screening with 500 Hz included.

It is worth observing that in terms of the direct cost, tablet-based screening is the most advantageous approach because there is no need to purchase expensive equipment, such as audiometers and immittance equipment, or to perform testing in an acoustic booth. In addition, for this screening method, it is not necessary to have an audiologist present during the exam, as the screening may be performed by another professional in the school setting who can then send the results for a remote audiological analysis.

Comparing the direct costs of computer-based screening and conventional audiometry, some authors found that the cost of the former was approximately half that of the latter.⁶⁴

Considering the indirect costs of screening, which result from the referral of false-positive cases (e.g. transportation, unnecessary procedures and parents missing work),^23,72,73 we suggest that the serial approach (i.e. tablet-based screening followed by immittance testing only for children who failed the initial screening) is the best approach.⁷⁰

In this way, the method of using tele-audiometry via a tablet, as proposed in the present study, was shown to be a valuable hearing screening tool for use with schoolchildren. Validation of the system was performed using TDH39 headphones outside of an acoustic booth and with results automatically generated by the system.

The telehealth mode used in this system was asynchronous, as the results were stored on the tablet and were later transmitted to the central database for management. For this reason, this system can be used even in places where there is no internet available at the time of the evaluation.

Remote data management through a central database (Cloud) allows for the systematic and accurate tracking of participants’ results, even for large-scale screening programmes.⁵¹ In addition, the automatic determination of the results made by the system, together with central data storage, decreases the possibility of data loss and human error during the process.⁵⁰

Regarding the use of TDH39 headphones as well as the absence of an acoustic booth during screening in school environments, it is essential to perform noise monitoring, either using dosimeters or specific applications, in order to reduce negative effects of this variable on the results, as mentioned previously.

Concerning the main potentialities of the test, it is important to highlight that the instrument in question evaluates the main frequencies necessary for speech recognition, including the frequency of 500 Hz, which is often the only one that is abnormal in children with conductive hearing disorders.

In addition, the intensity of the tones used in the application allows for the identification of mild hearing loss, which may be neglected by parents or teachers. Moreover, as each ear is evaluated separately, unilateral hearing loss can be detected.

It should be noted that the costs of tablets and TDH headphones are usually lower than those of an audiometer, allowing hearing screening to take place in locations with limited resources. While the costs of screening were not evaluated or measured in the present study, we recommend that future researchers investigate this issue. Moreover, because this is an automated procedure based on an interactive game, it can be easily applied in the paediatric population by other professionals who are not necessarily audiologists.

In terms of limitations of the study, we can cite the absence of evaluations of children under six years of age, who may have more difficulties in performing the tablet screening. Thus, we suggest that future studies evaluate younger children as well as different populations, allowing the validity of the screening protocol to be assessed in different samples.

In conclusion, based on the potential of the investigated tool and the study results, we consider tablet-based hearing screening to be a valid and promising instrument for use in the school setting. However, it does not replace a complete audiological evaluation.

Footnotes

Acknowledgements

The authors would like to thank FAPESP and CNPq for their financial support for this study.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo – Grant no. 2013/22013-7) and CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico – Grant no. 304550/2015-9).

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