Document 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.

Digital Object Identifier (DOI)

https://doi.org/10.1111/jcpp.14159

Rights

© 2025 The Author(s). Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

APA Citation

Lampinen, L. A., Zheng, S., Olson, L., Bal, V. H., Thurm, A. E., Esler, A. N., Kanne, S. M., Kim, S. H., Lord, C., Parenteau, C., Nowell, K. P., Roberts, J. E., Takahashi, N., & Bishop, S. L. (2025). DSM ‐5 based algorithms for the autism diagnostic interview‐revised for children ages 4–17 years. Journal of Child Psychology and Psychiatry, 66(9), 1403–1413. https://doi.org/10.1111/jcpp.14159

Download

Included in

Psychology Commons

Share

COinS