Early Predictors of ASD in Young Children Using a Nationally Representative Data Set
| Autor: | Daniel J. Laxman, Rosa Milagros Santos, Laurie M. Jeans, Brent A. McBride, W. Justin Dyer |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Psychomotor learning
media_common.quotation_subject Cognition Self-control medicine.disease Social relation Developmental psychology Psychiatry and Mental health Pediatrics Perinatology and Child Health Cohort Developmental and Educational Psychology medicine Autism Early childhood Psychology media_common Multinomial logistic regression |
| Zdroj: | Journal of Early Intervention. 35:303-331 |
| ISSN: | 2154-3992 1053-8151 |
| DOI: | 10.1177/1053815114523319 |
| Popis: | Current clinical diagnosis of Autism Spectrum Disorders (ASD) occurs between 3 and 4 years of age, but increasing evidence indicates that intervention begun earlier may improve outcomes. Using secondary analysis of the Early Childhood Longitudinal Study–Birth Cohort data set, the current study identifies early predictors prior to the diagnosis of ASD at 4 years for approximately 100 children. Children with ASD were compared with children with other disabilities and children who were typically developing. Multinomial logistic regression analyses identified limited unique characteristics (e.g., self-regulation and sleep patterns) at the 9-month time point. A majority of the differences in communication and language, mental/cognitive function, motor function, social interaction, and self-regulation were found at the 2-year time point. Implications for research and practice are presented. |
| Databáze: | OpenAIRE |
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