Diagnosing attention deficit disorders with the Behavioral Assessment System for Children and the Child Behavior Checklist: test and construct validity analyses using optimal discriminant classification trees.

The usefulness of the Behavioral Assessment System for Children (BASC) and Child Behavior Checklist (CBCL) Parent scales was examined with respect to (a) differentiating students with attention deficit-hyperactivity disorder (ADHD) from non-ADHD students and (b) discriminating between the predominantly inattentive-type and combined-type ADHD-afflicted students. For both the BASC and the CBCL, a different optimal discriminant classification tree analysis (CTA) model was developed for each of the 2 diagnostic predictions. For distinguishing ADHD students from non-ADHD students, the BASC model was more parsimonious and accurate than the CBCL model. Toward the goal of differentiating between primarily inattentive and combined types, the CBCL's model was superior for predicting primarily inattentive students. The results demonstrate the diagnostic utility of the BASC and CBCL and describe salient behavioral dimensions associated with subtypes of ADHD.

Duke Scholars

Author Kevin Phillip Weinfurt Population Health Sciences