Implications of cooccurring <scp>ADHD</scp> for the cognitive behavioural treatment of anxiety in autistic children
Bibliographic record
Abstract
BACKGROUND: Childhood mental health conditions commonly cooccur, with potential treatment implications. Autistic children frequently experience anxiety and attention deficit/hyperactivity disorder (ADHD). We investigated the implications of this cooccurrence for Cognitive Behavioural Therapy (CBT), a front-line treatment for anxiety in autistic children. We tested whether (1) ADHD predicts anxiety treatment response, (2) ADHD improves in response to anxiety treatment and (3) ADHD improvement is related to reductions in anxiety. METHOD: Autistic children with elevated anxiety (N = 167) enrolled in a multisite, randomised controlled trial comparing standard CBT, autism-adapted CBT and treatment as usual. ADHD symptoms and severity were assessed via a parent-report questionnaire and clinical interview, respectively. Linear regressions (questions 1 and 2) and linear mixed models (question 3) were conducted with adjustments for multiple comparisons. RESULTS: Participants meeting diagnostic criteria for ADHD (62%) had greater pretreatment anxiety severity and anxiety-related functional impairment, particularly at school. ADHD did not moderate anxiety response following CBT. Receiving CBT (standard or adapted) predicted reduction in evaluator-rated ADHD severity, but not parent-reported symptoms. Reduction in anxiety severity predicted reduction in ADHD symptoms and severity. CONCLUSIONS: Existing CBT programmes are suitable for treating anxiety in autistic children with cooccurring ADHD. Future research should identify mechanisms through which CBT for anxiety also mitigates ADHD, with the aim of improving treatment precision and effectiveness.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".