Effectiveness of a modified group cognitive behavioral therapy program for anxiety in children with ASD delivered in a community context
Bibliographic record
Abstract
BACKGROUND: Youth with autism spectrum disorder (ASD) experience high rates (approximately 50-79%) of comorbid anxiety problems. Given the significant interference and distress that excessive anxiety can cause, evidence-based intervention is necessary in order to reduce long-term negative effects. Cognitive behavioral therapy (CBT) has demonstrated efficacy for treating anxiety disorders across the lifespan, both in individual and group formats. Recently, modified CBT programs for youth with ASD have been developed, showing positive outcomes. To date, these modified CBT programs have primarily been evaluated in controlled research settings. METHODS: The current community effectiveness study investigated the effectiveness of a modified group CBT program (Facing Your Fears) delivered in a tertiary care hospital and across six community-based agencies providing services for youth with ASD. Data were collected over six years (N = 105 youth with ASD; ages 6-15 years). RESULTS: Hospital and community samples did not differ significantly, except in terms of age (hospital M = 10.08 years; community M = 10.87 years). Results indicated significant improvements in anxiety levels from baseline to post-treatment across measures, with medium effect sizes. An attempt to uncover individual characteristics that predict response to treatment was unsuccessful. CONCLUSIONS: Overall, this study demonstrated that community implementation of a modified group CBT program for youth with ASD is feasible and effective for treating elevated anxiety.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".