Deans

H. Wells Singleton, Ph.D. – Abraham S. Fischler School of Education Roni Leiderman, Ph.D. – Mailman Segal Center for Human Development Karen Grosby, M.Ed. – Center for Psychological Studies

Award Date

1-1-2009

Abstract

Accurate identification of Autism Spectrum Disorders (ASD) is crucial to meeting the needs of school-age children with ASD, but there is a paucity of research examining the efficacy of best practice diagnostic strategies and instruments used to identify ASD in school-age children. Current best practice parameters (Filipek, et al., 1999) for diagnosing ASD, include the use of diagnostic measures, such as the Autism Diagnostic Interview-revised (ADI-R), the Gilliam Autism Rating Scale (GARS), the Childhood Autism Rating Scale (CARS), and the Autism Diagnostic Observation Schedule-Generic (ADOS-G), as well as measures of intellectual, language, and adaptive functioning. To date, only one study, carried out with toddlers, considered the agreement among various best practice diagnostic strategies and instruments used to identify ASD (Ventola et al., 2006). However, there are no published studies which examine the agreement among best practice diagnostic strategies and instruments used to identify ASD in school-age children. The proposed study aims to bridge this gap in the existing literature by investigating concordance and discrepancy rates among the ADI-R, GARS-2, CARS and ADOS-G, as well as agreement with ASD diagnostic criteria outlined in the DSM-IV-TR in the diagnosis of ASD in school-age children (i.e., children ages 5-12). Approximately 40 participants will be recruited from referrals primarily emanating from the University of Miami/Nova Southeastern University Center for Autism Related Disabilities (UM-NSU CARD), and they and their parents will be administered the diagnostic instruments as part of a comprehensive evaluation. Cohen's kappa (k) will be used to evaluate the pair-wise agreement among the four instruments and the DSM-IV-TR criteria, and sensitivity, specificity, and positive predictive values will also be calculated for the four measures against the DSM-IV-TR.

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