title: Survey non-response in an internet-mediated, longitudinal autism research study.
abstract: OBJECTIVE
  To evaluate non-response rates to follow-up online surveys using a prospective cohort of parents raising at least one child with an autism spectrum disorder. A secondary objective was to investigate predictors of non-response over time.
  
  
  METHODS
  Data were collected from a US-based online research database, the Interactive Autism Network (IAN). A total of 19,497 youths, aged 1.9-19 years (mean 9 years, SD 3.94), were included in the present study. Response to three follow-up surveys, solicited from parents after baseline enrollment, served as the outcome measures. Multivariate binary logistic regression models were then used to examine predictors of non-response.
  
  
  RESULTS
  31,216 survey instances were examined, of which 8772 or 28.1% were partly or completely responded to. Results from the multivariate model found non-response of baseline surveys (OR 28.0), years since enrollment in the online protocol (OR 2.06), and numerous sociodemographic characteristics were associated with non-response to follow-up surveys (all p<0.05).
  
  
  CONCLUSIONS
  Consistent with the current literature, response rates to online surveys were somewhat low. While many demographic characteristics were associated with non-response, time since registration and participation at baseline played the greatest role in predicting follow-up survey non-response.
  
  
  CONCLUSIONS
  An important hazard to the generalizability of findings from research is non-response bias; however, little is known about this problem in longitudinal internet-mediated research (IMR). This study sheds new light on important predictors of longitudinal response rates that should be considered before launching a prospective IMR study.
authors.affiliation: Center for Autism and Related Disorders, Kennedy Krieger Institute, Baltimore, Maryland 21211, USA.
authors.forename: Luther G
authors.initials: LG
authors.lastname: Kalb
authors.forename: Cheryl
authors.initials: C
authors.lastname: Cohen
authors.forename: Harold
authors.initials: H
authors.lastname: Lehmann
authors.forename: Paul
authors.initials: P
authors.lastname: Law
mesh_terms: D000293:Adolescent; D000328:Adult; D002648:Child; D002659:Child Development Disorders, Pervasive / Q000453:epidemiology; D002675:Child, Preschool; D005260:Female; D006297:Health Services Accessibility; D006302:Health Services Research / Q000379:methods* / Q000706:statistics & numerical data; D006306:Health Surveys / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D007223:Infant; D020407:Internet; D053208:Kaplan-Meier Estimate; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D015999:Multivariate Analysis; D010290:Parents; D011159:Population Surveillance / Q000379:methods*; D014481:United States / Q000453:epidemiology; D055815:Young Adult