The screening efficiency of 2 methods to convert Child Behavior Checklist (CBCL) assessment data into Diagnostic and Statistical Manual of Mental Disorders (4th ed. [DSM–IV]; American Psychiatric Association, 1994) diagnoses was compared. The Machine-Aided Diagnosis (MAD) method converts CBCL input data directly into DSM–IV symptom criteria. The Achenbach System of Empirically Based Assessment (ASEBA) proceeds more indirectly and uses DSM-oriented scales. The power of the 2 methods to predict DSM–IV diagnoses obtained via administration of the structured Diagnostic InterviewSchedule for Children (DISC–IV) interview in a clinical sample was examined. DISC–IV interviews and CBCL reports from parents of 44 children, 25 boys, and 19 girls, ages 6 to 17 were used. The results showed comparable levels of predictive power for the 2 methods. Both methods were able to predict DSM–IV diagnoses and therefore can be used for screening DSM–IV diagnoses.
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