Predicting elementary school participation in children with disabilities

Objective: To identify predictors of participation in school activities fro m two sets of functional variables using classification and regression tree analysis. Design: Relational study. Participants: A nationwide sample of 341 children with various disabling co nditions, including physical and cognitive/behavioral types of impairment a nd various severity levels. Children attended public elementary school in 4 0 states in the United States. Main Outcome Measure: Overall participation in elementary school, combining children's participation in six different environments (transportation, tr ansitions, classroom, cafeteria, bathroom, and playground), as measured by the newly developed School Function Assessment. The children were dichotomi zed 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 di screte activities. Final predictive models included physical and cognitive- behavioral variables, suggested important interactions among predictors, an d 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 child ren's physical capabilities. Full participation was predicted by a combinat ion of physical and cognitive-behavioral variables. Findings underscore the relative utility of functional performance compared with impairment inform ation to predict the outcome, and suggest pathways of influence to consider in future research and intervention efforts.