From CBCL to DSM: A Comparison of Two Methods to Screen for DSM–IV Diagnoses Using CBCL Data

Abstract

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 Interview Schedule 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.