4.3 Article

Investigating the Accuracy of a Novel Telehealth Diagnostic Approach for Autism Spectrum Disorder

期刊

PSYCHOLOGICAL ASSESSMENT
卷 29, 期 3, 页码 245-252

出版社

AMER PSYCHOLOGICAL ASSOC
DOI: 10.1037/pas0000317

关键词

autism; diagnosis; video; telehealth; remote assessment

资金

  1. National Institute of Mental Health's Small Business Innovation Research Grant [9 R44 MH099035]
  2. SARRC
  3. Georgia Institute of Technology

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Research indicates that a substantial amount of time elapses between parents' first concerns about their child's development and a formal diagnosis of autism spectrum disorder (ASD). Telehealth presents an opportunity to expedite the diagnostic process. This project compared a novel telehealth diagnostic approach that utilizes clinically guided in-home video recordings to the gold standard in-person diagnostic assessment. Participants included 40 families seeking an ASD evaluation for their child and 11 families of typically developing children. Children were between the ages of 18 months and 6 years 11 months; mean adaptive behavior composite = 75.47 (SD = 15.94). All parent participants spoke English fluently. Families completed the Naturalistic Observation Diagnostic Assessment (NODA) for ASD, which was compared to an in-person assessment (IPA). Agreement between the 2 methods, as well as sensitivity, specificity, and interrater reliability, were calculated for the full sample and the subsample of families seeking an ASD evaluation. Diagnostic agreement between NODA and the IPA was 88.2% (kappa = 0.75) in the full sample and 85% (kappa = 0.58) in the subsample. Sensitivity was 84.9% in both, whereas specificity was 94.4% in the full sample and 85.7% in the subsample. Kappa coefficients for interrater reliability indicated 85% to 90% accuracy between raters. NODA utilizes telehealth technology for families to share information with professionals and provides a method to inform clinical judgment for a diagnosis of ASD. Due to the high level of agreement with the IPA in this sample, NODA has potential to improve the efficiency of the diagnostic process for ASD.

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