Predicting DSM-III-R disorders from the youth self-report: Analysis of data from a field study

Objective: To predict DSM-III-R diagnoses from Youth Self-Report (YSR) scor es. Method: The Diagnostic Interview Schedule for Children Version 2.1c (DI SC-2.1c) and YSR were administered to 289 homeless adolescents. Stepwise di scriminant analysis identified YSR scales contributing to predictions of DS M-III-R disorders. Paper-and-pencil prediction rules based on YSR "borderli ne" or "clinical" scores were evaluated. Results: Statistically significant discriminant functions for disruptive disorders, depressive disorders, man ic disorders, attention-deficit hyperactivity disorder, schizophrenia, and posttraumatic stress disorder, each based on a unique pair of YSR scales, p roduced overall hit rates of 0.66 to 0.90. Paper-and-pencil predictions pro duced comparable results. The weakest overall predictions were for the disr uptive behaviors; the best rule ("IF Aggressive OR Delinquent is at least b orderline THEN predict oppositional defiant disorder or conduct disorder") produced a 0.72 hit rate. The strongest overall predictions were for schizo phrenia; the best prediction rule ("IF [Thought Problems AND Delinquent are at least borderline] AND [at least one is clinical] THEN predict schizophr enia") produced a 0.87 hit rate. Conclusions: While the success rates repor ted here are specific to this sample, it appears that the YSR has good abil ity to predict DSM-IN-R diagnoses as determined by the DISC. Furthermore, i t was demonstrated that categorical diagnoses can be treated as locations o r cluster sectors in a multidimensional space.