Predicting Developmental Status from 12 to 24 Months in Infants at Risk for Autism Spectrum Disorder: A Preliminary Report

• Authors: Suzanne L. Macari, Yale Child Study Center; Daniel Campbell, Yale University; Grace W. Gengoux, Yale University; Celine A. Saulnier, Emory University; Ami Klin, Emory University; Katarzyna Chawarska, Yale University
• Journal Title: Journal of Autism and Developmental Disorders
• Volume: Volume 42, Number 12
• Publisher: Springer Verlag (Germany) | 2012-12-01, Pages 2636-2647
• Type of Work: Article | Post-print: After Peer Review
• Publisher DOI: http://doi.org/10.1007/s10803-012-1521-0
• Subjects: Health Sciences, Mental Health; Psychology, Developmental
• Keywords: Social Sciences; Psychology, Developmental; Psychology; Autism; Infancy; High risk studies; Longitudinal studies; Pervasive developmental disorder; COMMUNICATION DEVELOPMENT; 2ND YEAR; CHILDREN; REGRESSION; TODDLERS; EMERGENCE; DIAGNOSIS; SIBLINGS; VALIDITY; LEVEL

Abstract

The study examined whether performance profiles on individual items of the Toddler Module of the Autism Diagnostic Observation Schedule at 12 months are associated with developmental status at 24 months in infants at high and low risk for developing Autism Spectrum Disorder (ASD). A nonparametric decision-tree learning algorithm identified sets of 12-month predictors of developmental status at 24 months. Results suggest that identification of infants who are likely to exhibit symptoms of ASD at 24 months is complicated by variable patterns of symptom emergence. Fine-grained analyses linking specific profiles of strengths and deficits with specific patterns of symptom emergence will be necessary for further refinement of screening and diagnostic instruments for ASD in infancy.