title: Demographic and occupational predictors of early response to a mailed invitation to enroll in a longitudinal health study.
abstract: BACKGROUND
  Often in survey research, subsets of the population invited to complete the survey do not respond in a timely manner and valuable resources are expended in recontact efforts. Various methods of improving response have been offered, such as reducing questionnaire length, offering incentives, and utilizing reminders; however, these methods can be costly. Utilizing characteristics of early responders (refusal or consent) in enrollment and recontact efforts may be a unique and cost-effective approach for improving the quality of epidemiologic research.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Defense Global Emerging Infections Surveillance and Response System (DoD-GEIS), Walter Reed Army Institute of Research, Silver Spring, MD, USA. Jean-Paul.Chretien@na.amedd.army.mil
authors.forename: Jean-Paul
authors.initials: JP
authors.lastname: Chretien
authors.forename: Laura K
authors.initials: LK
authors.lastname: Chu
authors.forename: Tyler C
authors.initials: TC
authors.lastname: Smith
authors.forename: Besa
authors.initials: B
authors.lastname: Smith
authors.forename: Margaret A K
authors.initials: MA
authors.lastname: Ryan
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D015331:Cohort Studies; D003625:Data Collection; D004522:Educational Status; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D009790:Occupations; D012044:Regression Analysis