Predicting elementary school participation in children with disabilities

Objective: To identify predictors of participation in school activities from two sets of functional variables using classification and regression tree analysis. Design: Relational study. Participants: A nationwide sample of 341 children with various disabling conditions, including physical and cognitive/behavioral types of impairment and various severity levels. Children attended public elementary school in 40 states in the United States. Main Outcome Measure: Overall participation in elementary school, combining children's participation in six different environments (transportation, transitions, classroom, cafeteria, bathroom, and playground), as measured by the newly developed School Function Assessment. The children were dichotomized into full (n = 117) and limited (n = 224) participation categories. Results: Two classification trees were developed identifying a small set of predictors from variables measuring performance of functional tasks and discrete activities. Final predictive models included physical and cognitive-behavioral variables, suggested important interactions among predictors, and identified meaningful cut-off points that classified the sample into the outcome categories with about 85% accuracy. Conclusions: Limited participation was predicted by information about children's physical capabilities. Full participation was predicted by a combination of physical and cognitive-behavioral variables. Findings underscore the relative utility of functional performance compared with impairment information to predict the outcome, and suggest pathways of influence to consider in future research and intervention efforts.