Cj. Morgan et Am. Cauce, Predicting DSM-III-R disorders from the youth self-report: Analysis of data from a field study, J AM A CHIL, 38(10), 1999, pp. 1237-1245
Citations number
16
Categorie Soggetti
Psychiatry
Journal title
JOURNAL OF THE AMERICAN ACADEMY OF CHILD AND ADOLESCENT PSYCHIATRY
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.