Using audiometric data base analysis.
Audiometric data base analysis (ADBA) offers the most direct means of judging the effectiveness of a hearing conservation program (HCP) in preventing occupational hearing loss. However, numerous factors need to be accounted for if the findings are to be meaningful. This paper discusses several parameters known to influence the interpretation of group data statistics in assessing HCP effectiveness. Testing factors that affect the stability of the data base include audiometric techniques, calibration procedures, testing environment, and the motivation and prior experience of the subject. Pertinent population parameters include age, sex, race, current and prior noise exposures, learning effects, and the types of hearing protectors in use. Two case histories are presented to illustrate the application of ADBA techniques. Specific analysis procedures reviewed include comparisons of mean thresholds for selected industrial and nonindustrial populations, rates of change in mean hearing levels over a period of time, baseline and sequential test-retest comparisons, and different threshold shift criteria. The preliminary results of ADBA research being done by the American National Standards Institute (ANSI) S12.12 Working Group are summarized, including desirable criterion ranges for several statistics established by applying them to control data sets.
D001299:Audiometry / Q000592:standards*; D004430:Ear Protective Devices / Q000592:standards*; D006317:Hearing Loss, Noise-Induced / Q000517:prevention & control*; D006801:Humans; D007256:Information Systems; D009784:Occupational Diseases / Q000517:prevention & control*; D009786:Occupational Health Services / Q000592:standards*; D011482:Protective Devices / Q000592:standards*; D014481:United States