Title |
Comparing Diagnostic Outcomes of Autism Spectrum Disorder Using DSM-IV-TR and DSM-5 Criteria
|
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Published in |
Journal of Autism and Developmental Disorders, November 2014
|
DOI | 10.1007/s10803-014-2306-4 |
Pubmed ID | |
Authors |
Elizabeth B. Harstad, Jason Fogler, Georgios Sideridis, Sarah Weas, Carrie Mauras, William J. Barbaresi |
Abstract |
Controversy exists regarding the DSM-5 criteria for ASD. This study tested the psychometric properties of the DSM-5 model and determined how well it performed across different gender, IQ, and DSM-IV-TR sub-type, using clinically collected data on 227 subjects (median age = 3.95 years, majority had IQ > 70). DSM-5 was psychometrically superior to the DSM-IV-TR model (Comparative Fit Index of 0.970 vs 0.879, respectively). Measurement invariance revealed good model fit across gender and IQ. Younger children tended to meet fewer diagnostic criteria. Those with autistic disorder were more likely to meet social communication and repetitive behaviors criteria (p < .001) than those with PDD-NOS. DSM-5 is a robust model but will identify a different, albeit overlapping population of individuals compared to DSM-IV-TR. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Canada | 3 | 13% |
United Kingdom | 3 | 13% |
United States | 2 | 9% |
Netherlands | 2 | 9% |
Belgium | 1 | 4% |
Ireland | 1 | 4% |
South Africa | 1 | 4% |
Austria | 1 | 4% |
Unknown | 9 | 39% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 17 | 74% |
Science communicators (journalists, bloggers, editors) | 3 | 13% |
Scientists | 3 | 13% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 3% |
Jordan | 1 | <1% |
Unknown | 108 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 23 | 21% |
Student > Ph. D. Student | 14 | 13% |
Researcher | 13 | 12% |
Student > Bachelor | 11 | 10% |
Student > Postgraduate | 9 | 8% |
Other | 23 | 21% |
Unknown | 19 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 35 | 31% |
Medicine and Dentistry | 12 | 11% |
Neuroscience | 7 | 6% |
Social Sciences | 7 | 6% |
Computer Science | 5 | 4% |
Other | 19 | 17% |
Unknown | 27 | 24% |