Reducing respirator fit test errors: a multi-donning approach.
As a continuation of recent studies to assess the accuracy of existing fit test methods, a multi-donning approach to fit testing is presented. As an example of that approach, a multi-donning quantitative fit test for filtering-facepiece respirators is presented and analyzed by comparing its error rates with those of the single-donning approach of current fit test methods. That analysis indicates the multi-donning fit test has the potential to reduce both the alpha error and the beta error to half that of single-donning fit tests. The alpha error is the error of failing a respirator that should pass; the beta error is the error of passing a respirator that should fail. Lowering fit test error rates for filtering-facepiece respirators is important because fit testing is an essential means of helping assure that an individual has selected an adequately fitting respirator. To reduce the alpha and beta error inherent in current fit test methods, the proposed fit test for filtering-facepiece respirators incorporates five donnings of the facepiece, unlike the single donning of existing fit test methods. The analysis presented here indicates that the multiple-donning approach reduces the element of chance in the fit test result and thereby increases the consistency and accuracy of the fit tests. The time to conduct the multi-donning test can approximate the time for current, single-donning tests by shortening the time the respirator is worn after each donning to about 10 sec. And, unlike current fit tests for filtering-facepieces that measure only faceseal leakage, the example multiple-donning fit test considered here is based on a measurement of total leakage (faceseal plus filter). Utilizing total respirator leakage can result in simpler quantitative fit test instrumentation and a fit test that is more relevant to the workplace. Further trials with human subjects are recommended in order to validate the proposed multi-donning approach.
Campbell
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DL
Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Morgantown, West Virginia, USA.
Coffey
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CC
Jensen
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PA
Zhuang
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Z
D019544:Equipment Failure Analysis / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D012134:Respiratory Protective Devices