Smartphone Threshold Audiometry in Underserved Primary Health-Care Contexts

Int J Audiol. 2016;55(4):232-8. doi: 10.3109/14992027.2015.1124294. Epub 2016 Jan 21.

Abstract

Objective: To validate a calibrated smartphone-based hearing test in a sound booth environment and in primary health-care clinics.

Design: A repeated-measure within-subject study design was employed whereby air-conduction hearing thresholds determined by smartphone-based audiometry was compared to conventional audiometry in a sound booth and a primary health-care clinic environment.

Study sample: A total of 94 subjects (mean age 41 years ± 17.6 SD and range 18-88; 64% female) were assessed of whom 64 were tested in the sound booth and 30 within primary health-care clinics without a booth.

Results: In the sound booth 63.4% of conventional and smartphone thresholds indicated normal hearing (≤15 dBHL). Conventional thresholds exceeding 15 dB HL corresponded to smartphone thresholds within ≤10 dB in 80.6% of cases with an average threshold difference of -1.6 dB ± 9.9 SD. In primary health-care clinics 13.7% of conventional and smartphone thresholds indicated normal hearing (≤15 dBHL). Conventional thresholds exceeding 15 dBHL corresponded to smartphone thresholds within ≤10 dB in 92.9% of cases with an average threshold difference of -1.0 dB ± 7.1 SD.

Conclusions: Accurate air-conduction audiometry can be conducted in a sound booth and without a sound booth in an underserved community health-care clinic using a smartphone.

Keywords: Audiometry; air conduction; ambient noise; automated audiometer; mHealth; smartphone.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Acoustic Stimulation / instrumentation*
  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Audiometry, Pure-Tone / instrumentation*
  • Auditory Threshold*
  • Female
  • Hearing Disorders / diagnosis*
  • Hearing Disorders / psychology
  • Humans
  • Male
  • Medically Underserved Area*
  • Middle Aged
  • Mobile Applications
  • Predictive Value of Tests
  • Primary Health Care / methods*
  • Reproducibility of Results
  • Smartphone*
  • South Africa
  • Young Adult