M Ganguli1, M E Lytle, M D Reynolds, H H Dodge. 1. Department of Psychiatry, School of Medicine, Graduate School of Public Health, University of Pittsburgh, Pennsylvania, USA. gangulim@vms.cis.pitt.edu
Abstract
BACKGROUND: Selection methods vary greatly in ease and cost-effectiveness. The effects of selection factors associated with subjects' recruitment into studies can introduce bias and seriously limit the generalizability of results. METHODS: For an epidemiologic study, we recruited an age-stratified random sample of 1,422 community-dwelling individuals aged 65+ years from the voter registration lists in a rural area of southwestern Pennsylvania. The first 1,366 of these were accrued through intensive recruitment efforts; the last 56 of them responded to a single mailing. To increase sample size for future risk factor analyses, we also recruited by direct advertisement a sample of 259 volunteers from the same area. The three groups were compared on selected baseline characteristics and subsequent mortality. RESULTS: The two subgroups of the random sample were not significantly different on any of the variables we examined. Compared to the random sample, in cross-sectional analyses, volunteers were significantly more likely to be women, more educated, and less likely to have used several health and human services. Volunteers also had higher cognitive test scores and Instrumental Activities of Daily Living (IADL) ability. Over 6-8 years (10,861 person-years) of follow-up, volunteers had significantly lower mortality rates than randomly selected subjects. CONCLUSIONS: Health-related studies with populations composed partly or entirely of volunteers should take potential volunteer bias into account when analyzing and interpreting data.
BACKGROUND: Selection methods vary greatly in ease and cost-effectiveness. The effects of selection factors associated with subjects' recruitment into studies can introduce bias and seriously limit the generalizability of results. METHODS: For an epidemiologic study, we recruited an age-stratified random sample of 1,422 community-dwelling individuals aged 65+ years from the voter registration lists in a rural area of southwestern Pennsylvania. The first 1,366 of these were accrued through intensive recruitment efforts; the last 56 of them responded to a single mailing. To increase sample size for future risk factor analyses, we also recruited by direct advertisement a sample of 259 volunteers from the same area. The three groups were compared on selected baseline characteristics and subsequent mortality. RESULTS: The two subgroups of the random sample were not significantly different on any of the variables we examined. Compared to the random sample, in cross-sectional analyses, volunteers were significantly more likely to be women, more educated, and less likely to have used several health and human services. Volunteers also had higher cognitive test scores and Instrumental Activities of Daily Living (IADL) ability. Over 6-8 years (10,861 person-years) of follow-up, volunteers had significantly lower mortality rates than randomly selected subjects. CONCLUSIONS: Health-related studies with populations composed partly or entirely of volunteers should take potential volunteer bias into account when analyzing and interpreting data.
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