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Direct linkHoltman, Sara Julsrud; Winans, Katherine Skillestad; Hoch, John D. – Journal of Autism and Developmental Disorders, 2022
Logistic regression was used to examine the use of Autism Spectrum diagnostic categories from pre-COVID-19 in-person evaluations and COVID-19 telehealth evaluations at a specialist community mental health clinic. The diagnostic classification for children 0-5 (DC: 0-5) affords a wider range of diagnoses that allowed for inferences of clinician…
Descriptors: Clinical Diagnosis, Classification, Young Children, Autism Spectrum Disorders
Yen-Chin Wang; Chung-Yuan Cheng; Chi-Shin Wu; Chi-Chun Lee; Susan Shur-Fen Gau – Autism: The International Journal of Research and Practice, 2025
Machine-learning models can assist in diagnosing autism but have biases. We examines the correlates of misclassifications and how training data affect model generalizability. The Social Responsive Scale data were collected from two cohorts in Taiwan: the clinical cohort comprised 1203 autistic participants and 1182 non-autistic comparisons, and…
Descriptors: Artificial Intelligence, Autism Spectrum Disorders, Clinical Diagnosis, Error Patterns
Kathleen Lynne Lane; Nathan Allen Lane; Mark Matthew Buckman; Katie Scarlett Lane Pelton; Kandace Fleming; Rebecca E. Swinburne Romine – Behavioral Disorders, 2025
We report the results of a convergent validity study examining the externalizing subscale (SRSS-E5, five items) of the adapted Student Risk Screening Scale for Internalizing and Externalizing (SRSS-IE 9) with the externalizing subscale of the Teacher Report Form (TRF) with two samples of K-12 students. Results of logistic regression and receiver…
Descriptors: Data Analysis, Decision Making, Data Use, Test Validity
