99 Factors associated with anxiety disorders in children with autism spectrum disorder
Bibliographic record
Abstract
Mood disorders such as anxiety are prevalent in children with Autism Spectrum Disorder (ASD) and can be responsible for significant morbidity. Better understand the risk factors for anxiety disorders in children diagnosed with ASD using a large sample from a Canadian metropolitan area. Analyzed a dataset with diagnoses from children age 0–19 years assessed for ASD between 2010–2014. ASD was diagnosed by a qualified specialist using the appropriate Autism Diagnostic Observation Schedule (ADOS-2) module and Autism Diagnostic Interview-Revised (ADI-R). Differences in the rates of anxiety diagnoses were analyzed by age (<6, 6–12, >12 years), gender, intellectual disability, language impairment, attention deficit hyperactivity disorder (ADHD) and reported family history of mood disorder. The complete dataset included 4079 assessments and ASD was diagnosed in 2171 (53.2%). Rates for ASD+anxiety diagnoses in females (6.9%) did not differ significantly from males (9.2%; p=0.197). ASD+anxiety rates increased significantly (p<0.01) from 1.1% of children <6 years, to 19.8% at 6–12 years, and 32.4% of children >12 years. Children with intellectual disability were diagnosed with ASD+anxiety significantly less (3.6%) than children without intellectual disability (10.6%; p<0.01). ASD+anxiety was present in significantly fewer (5.7%) children with a language impairment, than those without (10.7%; p<0.01). Significantly more children with ADHD were diagnosed with ASD+anxiety (23.5%) compared to only 5.8% of those without ADHD (p<0.01). ASD+anxiety was present in significantly more (14.5%) children with a family history of anxiety than those without (8.3%; p=0.01). Factors associated with an increased rate of anxiety diagnoses for children with ASD include increasing age, absence of an intellectual disability, absence of a language disorder, presence of a co-morbid ADHD diagnosis, as well as a positive family history for an anxiety disorder. There were no gender differences in anxiety diagnoses in the ASD population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".