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J Am Acad Audiol 2017; 28(03): 200-208
DOI: 10.3766/jaaa.16002
Articles
Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Automated Smartphone Threshold Audiometry: Validity and Time Efficiency

Jessica van Tonder
*   Department of Speech-Language Pathology and Audiology, University of Pretoria, Pretoria, South Africa
,
De Wet Swanepoel
*   Department of Speech-Language Pathology and Audiology, University of Pretoria, Pretoria, South Africa
†   Ear Science Institute Australia, Subiaco, Australia
‡   Ear Sciences Centre, School of Surgery, The University of Western Australia, Nedlands, Australia
,
Faheema Mahomed-Asmail
*   Department of Speech-Language Pathology and Audiology, University of Pretoria, Pretoria, South Africa
,
Hermanus Myburgh
‡   Ear Sciences Centre, School of Surgery, The University of Western Australia, Nedlands, Australia
,
Robert H. Eikelboom
*   Department of Speech-Language Pathology and Audiology, University of Pretoria, Pretoria, South Africa
†   Ear Science Institute Australia, Subiaco, Australia
‡   Ear Sciences Centre, School of Surgery, The University of Western Australia, Nedlands, Australia
› Author Affiliations
Further Information

Publication History

Publication Date:
26 June 2020 (online)

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Abstract

Background:

Smartphone-based threshold audiometry with automated testing has the potential to provide affordable access to audiometry in underserved contexts.

Purpose:

To validate the threshold version (hearTest) of the validated hearScreen™ smartphone-based application using inexpensive smartphones (Android operating system) and calibrated supra-aural headphones.

Research Design:

A repeated measures within-participant study design was employed to compare air-conduction thresholds (0.5–8 kHz) obtained through automated smartphone audiometry to thresholds obtained through conventional audiometry.

Study Sample:

A total of 95 participants were included in the study. Of these, 30 were adults, who had known bilateral hearing losses of varying degrees (mean age = 59 yr, standard deviation [SD] = 21.8; 56.7% female), and 65 were adolescents (mean age = 16.5 yr, SD = 1.2; 70.8% female), of which 61 had normal hearing and the remaining 4 had mild hearing losses.

Data Analysis:

Threshold comparisons were made between the two test procedures. The Wilcoxon signed-ranked test was used for comparison of threshold correspondence between manual and smartphone thresholds and the paired samples t test was used to compare test time.

Results:

Within the adult sample, 94.4% of thresholds obtained through smartphone and conventional audiometry corresponded within 10 dB or less. There was no significant difference between smartphone (6.75-min average, SD = 1.5) and conventional audiometry test duration (6.65-min average, SD = 2.5). Within the adolescent sample, 84.7% of thresholds obtained at 0.5, 2, and 4 kHz with hearTest and conventional audiometry corresponded within ≤5 dB. At 1 kHz, 79.3% of the thresholds differed by ≤10 dB. There was a significant difference (p < 0.01) between smartphone (7.09 min, SD = 1.2) and conventional audiometry test duration (3.23 min, SD = 0.6).

Conclusions:

The hearTest application with calibrated supra-aural headphones provides a cost-effective option to determine valid air-conduction hearing thresholds.

Key Words

air conduction - automated audiometry - diagnostic audiometry - mHealth - smartphone
 

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