| Title |
Modeling the Phenotypic Architecture of Autism Symptoms from Time of Diagnosis to Age 6
|
|---|---|
| Published in |
Journal of Autism and Developmental Disorders, June 2014
|
| DOI | 10.1007/s10803-014-2167-x |
| Pubmed ID | |
| Authors |
Stelios Georgiades, Michael Boyle, Peter Szatmari, Steven Hanna, Eric Duku, Lonnie Zwaigenbaum, Susan Bryson, Eric Fombonne, Joanne Volden, Pat Mirenda, Isabel Smith, Wendy Roberts, Tracy Vaillancourt, Charlotte Waddell, Teresa Bennett, Mayada Elsabbagh, Ann Thompson, Pathways in ASD Study Team |
| Abstract |
The latent class structure of autism symptoms from the time of diagnosis to age 6 years was examined in a sample of 280 children with autism spectrum disorder. Factor mixture modeling was performed on 26 algorithm items from the Autism Diagnostic Interview - Revised at diagnosis (Time 1) and again at age 6 (Time 2). At Time 1, a "2-factor/3-class" model provided the best fit to the data. At Time 2, a "2-factor/2-class" model provided the best fit to the data. Longitudinal (repeated measures) analysis of variance showed that the "2-factor/3-class" model derived at the time of diagnosis allows for the identification of a subgroup of children (9 % of sample) who exhibit notable reduction in symptom severity. |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 67 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 12 | 17% |
| Professor | 8 | 12% |
| Researcher | 8 | 12% |
| Student > Doctoral Student | 7 | 10% |
| Student > Ph. D. Student | 7 | 10% |
| Other | 12 | 17% |
| Unknown | 15 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 16 | 23% |
| Social Sciences | 10 | 14% |
| Medicine and Dentistry | 7 | 10% |
| Neuroscience | 6 | 9% |
| Computer Science | 2 | 3% |
| Other | 8 | 12% |
| Unknown | 20 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 June 2014.
All research outputs
#17,489,487
of 25,654,806 outputs
Outputs from Journal of Autism and Developmental Disorders
#4,185
of 5,484 outputs
Outputs of similar age
#147,499
of 243,550 outputs
Outputs of similar age from Journal of Autism and Developmental Disorders
#47
of 56 outputs
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