Robert H Margolis1, Richard H Wilson, Gerald R Popelka, Robert H Eikelboom, De Wet Swanepoel, George L Saly. 1. 1Audiology Incorporated, Arden Hills, Minnesota, USA; 2James H. Quillen VA Medical Center, Mountain Home, Tennessee, USA; 3Department of Otolaryngology, Stanford University, Stanford, California, USA; 4Ear Science Institute Australia, Subiaco, Australia; 5Department of Speech-Language Pathology and Audiology, University of Pretoria, Pretoria, South Africa; and 6Ear Sciences Centre, School of Surgery, The University of Western Australia, Nedlands, Australia.
Abstract
OBJECTIVES: Five databases were mined to examine distributions of air-bone gaps obtained by automated and manual audiometry. Differences in distribution characteristics were examined for evidence of influences unrelated to the audibility of test signals. DESIGN: The databases provided air- and bone-conduction thresholds that permitted examination of air-bone gap distributions that were free of ceiling and floor effects. Cases with conductive hearing loss were eliminated based on air-bone gaps, tympanometry, and otoscopy, when available. The analysis is based on 2,378,921 threshold determinations from 721,831 subjects from five databases. RESULTS: Automated audiometry produced air-bone gaps that were normally distributed suggesting that air- and bone-conduction thresholds are normally distributed. Manual audiometry produced air-bone gaps that were not normally distributed and show evidence of biasing effects of assumptions of expected results. In one database, the form of the distributions showed evidence of inclusion of conductive hearing losses. CONCLUSIONS: Thresholds obtained by manual audiometry show tester bias effects from assumptions of the patient's hearing loss characteristics. Tester bias artificially reduces the variance of bone-conduction thresholds and the resulting air-bone gaps. Because the automated method is free of bias from assumptions of expected results, these distributions are hypothesized to reflect the true variability of air- and bone-conduction thresholds and the resulting air-bone gaps.
OBJECTIVES: Five databases were mined to examine distributions of air-bone gaps obtained by automated and manual audiometry. Differences in distribution characteristics were examined for evidence of influences unrelated to the audibility of test signals. DESIGN: The databases provided air- and bone-conduction thresholds that permitted examination of air-bone gap distributions that were free of ceiling and floor effects. Cases with conductive hearing loss were eliminated based on air-bone gaps, tympanometry, and otoscopy, when available. The analysis is based on 2,378,921 threshold determinations from 721,831 subjects from five databases. RESULTS: Automated audiometry produced air-bone gaps that were normally distributed suggesting that air- and bone-conduction thresholds are normally distributed. Manual audiometry produced air-bone gaps that were not normally distributed and show evidence of biasing effects of assumptions of expected results. In one database, the form of the distributions showed evidence of inclusion of conductive hearing losses. CONCLUSIONS: Thresholds obtained by manual audiometry show tester bias effects from assumptions of the patient's hearing loss characteristics. Tester bias artificially reduces the variance of bone-conduction thresholds and the resulting air-bone gaps. Because the automated method is free of bias from assumptions of expected results, these distributions are hypothesized to reflect the true variability of air- and bone-conduction thresholds and the resulting air-bone gaps.
Authors: Stacy L Pineles; Nicholas J Volpe; Eydie Miller-Ellis; Steven L Galetta; Prithvi S Sankar; Kenneth S Shindler; Maureen G Maguire Journal: Arch Ophthalmol Date: 2006-03
Authors: Robert H Margolis; Richard H Wilson; Gerald R Popelka; Robert H Eikelboom; De Wet Swanepoel; George L Saly Journal: Int J Audiol Date: 2015-05-04 Impact factor: 2.117
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