title: Accuracy of Mobile-Based Audiometry in the Evaluation of Hearing Loss in Quiet and Noisy Environments.
abstract: Objectives (1) To compare the accuracy of 2 previously validated mobile-based hearing tests in determining pure tone thresholds and screening for hearing loss. (2) To determine the accuracy of mobile audiometry in noisy environments through noise reduction strategies. Study Design Prospective clinical study. Setting Tertiary hospital. Subjects and Methods Thirty-three adults with or without hearing loss were tested (mean age, 49.7 years; women, 42.4%). Air conduction thresholds measured as pure tone average and at individual frequencies were assessed by conventional audiogram and by 2 audiometric applications (consumer and professional) on a tablet device. Mobile audiometry was performed in a quiet sound booth and in a noisy sound booth (50 dB of background noise) through active and passive noise reduction strategies. Results On average, 91.1% (95% confidence interval [95% CI], 89.1%-93.2%) and 95.8% (95% CI, 93.5%-97.1%) of the threshold values obtained in a quiet sound booth with the consumer and professional applications, respectively, were within 10 dB of the corresponding audiogram thresholds, as compared with 86.5% (95% CI, 82.6%-88.5%) and 91.3% (95% CI, 88.5%-92.8%) in a noisy sound booth through noise cancellation. When screening for at least moderate hearing loss (pure tone average >40 dB HL), the consumer application showed a sensitivity and specificity of 87.5% and 95.9%, respectively, and the professional application, 100% and 95.9%. Overall, patients preferred mobile audiometry over conventional audiograms. Conclusion Mobile audiometry can correctly estimate pure tone thresholds and screen for moderate hearing loss. Noise reduction strategies in mobile audiometry provide a portable effective solution for hearing assessments outside clinical settings.
authors.affiliation: 1 Department of Otolaryngology-Head and Neck Surgery, McGill University, Montreal, Canada.
authors.forename: Joe
authors.initials: J
authors.lastname: Saliba
authors.affiliation: 1 Department of Otolaryngology-Head and Neck Surgery, McGill University, Montreal, Canada.
authors.forename: Mahmoud
authors.initials: M
authors.lastname: Al-Reefi
authors.affiliation: 2 Department of Psychology, McGill University, Montreal, Canada.
authors.forename: Junie S
authors.initials: JS
authors.lastname: Carriere
authors.affiliation: 1 Department of Otolaryngology-Head and Neck Surgery, McGill University, Montreal, Canada.
authors.forename: Neil
authors.initials: N
authors.lastname: Verma
authors.affiliation: 1 Department of Otolaryngology-Head and Neck Surgery, McGill University, Montreal, Canada.
authors.forename: Christiane
authors.initials: C
authors.lastname: Provencal
authors.affiliation: 1 Department of Otolaryngology-Head and Neck Surgery, McGill University, Montreal, Canada.
authors.forename: Jamie M
authors.initials: JM
authors.lastname: Rappaport
mesh_terms: D000328:Adult; D001301:Audiometry, Pure-Tone / Q000379:methods*; D001309:Auditory Threshold; D005260:Female; D034381:Hearing Loss / Q000175:diagnosis*; D006801:Humans; D008297:Male; D008875:Middle Aged; D063731:Mobile Applications; D011446:Prospective Studies
keywords: audiometry; automated; hearing loss; mobile; noise reduction