Title |
Homogeneous Subgroups of Young Children with Autism Improve Phenotypic Characterization in the Study to Explore Early Development
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Published in |
Journal of Autism and Developmental Disorders, September 2017
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DOI | 10.1007/s10803-017-3280-4 |
Pubmed ID | |
Authors |
Lisa D. Wiggins, Lin H. Tian, Susan E. Levy, Catherine Rice, Li-Ching Lee, Laura Schieve, Juhi Pandey, Julie Daniels, Lisa Blaskey, Susan Hepburn, Rebecca Landa, Rebecca Edmondson-Pretzel, William Thompson |
Abstract |
The objective of this study was to identify homogenous classes of young children with autism spectrum disorder (ASD) to improve phenotypic characterization. Children were enrolled in the Study to Explore Early Development between 2 and 5 years of age. 707 children were classified with ASD after a comprehensive evaluation with strict diagnostic algorithms. Four classes of children with ASD were identified from latent class analysis: mild language delay with cognitive rigidity, mild language and motor delay with dysregulation, general developmental delay, and significant developmental delay with repetitive motor behaviors. We conclude that a four-class phenotypic model of children with ASD best describes our data and improves phenotypic characterization of young children with ASD. Implications for screening, diagnosis, and research are discussed. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 67% |
Unknown | 1 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 67% |
Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 103 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 16 | 16% |
Student > Ph. D. Student | 14 | 14% |
Student > Doctoral Student | 11 | 11% |
Researcher | 9 | 9% |
Other | 8 | 8% |
Other | 15 | 15% |
Unknown | 30 | 29% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 34 | 33% |
Social Sciences | 10 | 10% |
Neuroscience | 8 | 8% |
Medicine and Dentistry | 5 | 5% |
Nursing and Health Professions | 3 | 3% |
Other | 10 | 10% |
Unknown | 33 | 32% |