%0 Journal Article
%T Demographic and occupational predictors of early response to a mailed invitation to enroll in a longitudinal health study
%A Jean-Paul Chretien
%A Laura K Chu
%A Tyler C Smith
%A Besa Smith
%A Margaret AK Ryan
%A the Millennium Cohort Study Team
%J BMC Medical Research Methodology
%D 2007
%I BioMed Central
%R 10.1186/1471-2288-7-6
%X To better understand early responders of any kind, we compared the characteristics of individuals who explicitly refused, consented, or did not respond within 2 months from the start of enrollment into a large cohort study of US military personnel. A multivariate polychotomous logistic regression model was used to estimate the effect of each covariate on the odds of early refusal and on the odds of early consent versus late/non-response, while simultaneously adjusting for all other variables in the model.From regression analyses, we found many similarities between early refusers and early consenters. Factors associated with both early refusal and early consent included older age, higher education, White race/ethnicity, Reserve/Guard affiliation, and certain information technology and support occupations.These data suggest that early refusers may differ from late/non-responders, and that certain characteristics are associated with both early refusal and early consent to participate. Structured recruitment efforts that utilize these differences may achieve early response, thereby reducing mail costs and the use of valuable resources in subsequent contact efforts.Survey instruments play an important role in epidemiologic research, and due to the relative ease and cost benefits they are frequently implemented utilizing the mail system. Although more convenient than telephone or in-person interviews, postal questionnaires have been found to yield lower response rates [1]. Declining response rates increase the concern that non-participation bias may substantially affect the results of the study. Differences in demographic characteristics between participants and nonparticipants in health survey research are well studied and suggest associations between survey participation and gender [2-4], age [3,5,6], ethnicity [7], and socioeconomic status [4,8]. However, these associations are inconsistent, possibly due to differences in survey methodology, type, or population between
%U http://www.biomedcentral.com/1471-2288/7/6