The Prevalence of Anxiety and Mood Problems among Children with Autism and Asperger Syndrome
Bibliographic record
Abstract
The objective of this study was to report on the prevalence and correlates of anxiety and mood problems among 9- to 14- year-old children with Asperger syndrome (AS) and high-functioning autism. Children who received a diagnosis of autism ( n 40) or AS ( n 19) on a diagnostic interview when they were 4 to 6 years of age were administered a battery of cognitive and behavioural measures. Families were contacted roughly 6 years later (at mean age of 12 years) and assessed for evidence of psychiatric problems including mood and anxiety disorders. Compared with a sample of 1751 community children, AS and autistic children demonstrated a greater rate of anxiety and depression problems. These problems had a significant impact on their overall adaptation. There were, however, no differences in the number of anxiety and mood problems between the AS and autistic children within this high-functioning cohort. The number of psychiatric problems was not correlated with early autistic symptoms but was predicted to a small extent by early verbal/non-verbal IQ discrepancy scores. These data indicate that high-functioning PDD children are at greater risk for mood and anxiety problems than the general population but the correlates and risk factors for these comorbid problems remain unclear.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".