From CBCL to DSM: a comparison of two methods to screen for DSM-IV diagnoses using CBCL data.
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.
Krol
Nicole P C M
NP
Diagnostic Decision Making, Behavioral Science Institute, Radboud University Nijmegen, The Netherlands. n.krol@pwo.ru.nl
De Bruyn
Eric E J
EE
Coolen
Jolanda C
JC
van Aarle
Edward J M
EJ
D000293:Adolescent; D002648:Child; D002652:Child Behavior / Q000523:psychology*; D003937:Diagnosis, Differential; D039721:Diagnostic and Statistical Manual of Mental Disorders; D005260:Female; D006801:Humans; D007406:Interview, Psychological; D008297:Male; D008403:Mass Screening / Q000379:methods*; D001523:Mental Disorders / Q000175:diagnosis* / Q000453:epidemiology*