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Relative clinical utility of three Child Symptom Inventory-4 scoring algorithms for differentiating children with
Carla J DeVincent1, Kenneth D Gadow
1Cody Center for Autism and Developmental Disabilities, Department of Pediatrics, Putnam Hall, South Campus, Stony Brook University, Stony Brook, New York 11794-8790, USA.
Objective:
The present study compared three separate Child Symptom Inventory-4 (CSI-4) scoring algorithms for differentiating children with autism spectrum disorder (ASD) from youngsters with attention-deficit/hyperactivity disorder (ADHD).
Method:
Parents/teachers completed the CSI-4, a DSM-IV-referenced rating scale, for 6 to 12-year-old clinical referrals with ASD (N = 186) and ADHD (N = 251). Algorithms were based on either all CSI-4 items (forward logistic regressions) or the 12 DSM-IV symptoms of pervasive developmental disorder (PDD) included in the CSI-4.
Results:
ROC analyses indicated generally good to excellent values for area under the curve, sensitivity, specificity, and positive predictive power. Algorithms for parent ratings were superior to teacher ratings. The algorithm based solely on PDD symptoms evidenced the greatest generalizability.
Conclusion:
Although algorithms generated from regression analyses produced greater clinical utility for specific samples, the PDD-based algorithm resulted in greater stability across samples.
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