We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Survey non-response in an internet-mediated, longitudinal autism research study.
- Authors
Kalb, Luther G.; Cohen, Cheryl; Lehmann, Harold; Law, Paul
- 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. Materials and Methods Data were collected from a US-based online research database, the Interactive Autism Network (IAN). A total of 19 497 youths, aged 1.9e19 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). Discussion 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. Conclusion An important hazard to the generalizability of findings from research is non-response bias; however, little is known about this problem in longitudinal internetmediated research (IMR). This study sheds new light on important predictors of longitudinal response rates that should be considered before launching a prospective IMR study.
- Subjects
AUTISM research; SURVEYS; ONLINE databases; LOGISTIC regression analysis; ELECTRONIC information resources; MULTIVARIATE analysis; DEVELOPMENTAL disabilities; MANAGEMENT science
- Publication
Journal of the American Medical Informatics Association, 2012, Vol 19, Issue 4, p668
- ISSN
1067-5027
- Publication type
Article
- DOI
10.1136/amiajnl-2012-000863