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 1.9-19 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). 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 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.
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 1.9-19 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). 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 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.
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Authors: Tracy A Becerra; Maria L Massolo; Vincent M Yau; Ashli A Owen-Smith; Frances L Lynch; Phillip M Crawford; Kathryn A Pearson; Magdalena E Pomichowski; Virginia P Quinn; Cathleen K Yoshida; Lisa A Croen Journal: Perm J Date: 2017