Work

DSM-5 Based Algorithms for the Autism Diagnostic Interview-Revised for Children Ages 4–17 Years

Year: 2025

Type: article

Abstract: Background: The Autism Diagnostic Interview, Revised (ADI-R) is a caregiver interview that is widely used as part ofthe diagnostic assessment for Autism Spectrum Disorder (ASD). Few large-scale studies have reported the sensitivityand speciﬁcity of the ADI-R algorithms, which are based on DSM-IV Autistic Disorder criteria. Kim and Lord (Journalof Autism and Developmental Disorders, 2012, 42, 82) developed revised DSM-5-based toddler algorithms, which areonly applicable to children under 4 years. The current study developed DSM-5-based algorithms for children ages4–17 years and examined their performance compared to clinical diagnosis and to the original DSM-IV-basedalgorithms. Methods: Participants included 2,905 cases (2,144 ASD, 761 non-ASD) from clinical-researchdatabanks. Children were clinically referred for ASD-related concerns or recruited for ASD-focused researchprojects, and their caregivers completed the ADI-R as part of a comprehensive diagnostic assessment. Items relevantto DSM-5 ASD criteria were selected for the new algorithms primarily based on their ability to discriminate ASD fromnon-ASD cases. Algorithms were created for individuals with and without reported use of phrase speech.Conﬁrmatory factor analysis tested the ﬁt of a DSM-5-based two-factor structure. ROC curve analyses examinedthe diagnostic accuracy of the revised algorithms compared to clinical diagnosis. Results: The two-factor structure ofthe revised ADI-R algorithms showed adequate ﬁt. Sensitivity of the original ADI-R algorithm ranged from 74% to96%, and speciﬁcity ranged from 38% to 83%. The revised DSM-5-based algorithms performed similarly or better,with sensitivity ranging from 77% to 99% and speciﬁcity ranging from 71% to 92%. Conclusions: In this large sampleaggregated from US clinical-research sites, the original ADI-R algorithm showed adequate diagnostic validity, withpoorer speciﬁcity among individuals without phrase speech. The revised DSM-5-based algorithms introduced hereperformed comparably to the original algorithms, with improved speciﬁcity in individuals without phrase speech.These revised algorithms offer an alternative method for summarizing ASD symptoms in a DSM-5-compatiblemanner.

Source: Scholar Commons (University of South Carolina)

DOI: 10.1111/jcpp.14159">https://doi.org/10.1111/jcpp.14159</a></p