Reliability and Accuracy of Differentiating Pervasive Developmental Disorder Subtypes

OBJECTIVE: To evaluate the ability of the DSM-IV criteria for the pervasive developmental disorders (PDD) to reliably and accurately differentiate PDD subtypes. METHOD: The sample consisted of 143 children with various types of developmental disabilities. A diagnosis of PDD and PDD subtype was made by one clinician using information obtained from the Autism Diagnostic Interview-Revised and the Autism Diagnostic Observation Schedule. The raw data from the Autism Diagnostic Interview-Revised, clinical notes (excluding diagnostic opinion), Autism Diagnostic Observation Schedule, IQ, and other available data were independently assessed by three experienced raters, each of whom then made a separate, blind diagnosis. If there was any disagreement, a consensus best-estimate (CBE) diagnosis was made after discussion. To assess reliability, the agreement between the three raters was calculated using k. Accuracy was assessed by calculating the agreement between the clinician's diagnosis and the CBE and by calculating the error rates associated with the three raters using latent class analysis. RESULTS: The current DSM-IV criteria show good to excellent reliability for the diagnosis of PDD, Asperger's disorder (AsD), and autism, but they show poor reliability for the diagnosis of atypical autism. The clinician (compared to the CBE) had little difficulty differentiating PDD from non-PDD children and autism from AsD but had more difficulty identifying children with atypical autism. The latent class analysis also showed that the average error rates of the three raters for a differentiation of atypical autism from autism were unacceptably high. CONCLUSIONS: Although the psychometric properties of the current DSM-IV criteria for autism and AsD appear quite acceptable, there is likely to be a high rate of misclassification of children given a diagnosis of atypical autism.