Investigating dysfunctional cognition change as a putative mechanism of CBT for youth anxiety, OCD and PTSD: protocol for an individual participant data meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Anxiety disorders, obsessive-compulsive disorder (OCD) and post-traumatic stress disorder (PTSD) are common in children and adolescents and can lead to significant impairment. Cognitive behavioural therapy (CBT) with exposure is the first-line treatment, yet approximately half of treated youth do not achieve full remission. Dysfunctional cognitions-negative automatic thoughts, maladaptive beliefs and distorted interpretations-are considered key targets of CBT, but evidence in youth is mixed and underpowered. This study will examine whether change in dysfunctional cognitions mediates treatment outcome in anxiety, OCD and PTSD symptoms and whether this association varies across individual characteristics. METHODS AND ANALYSIS: An individual participant data meta-analysis (IPDMA) of randomised controlled trials of CBT for youth aged 5-18 years with anxiety disorders, OCD or PTSD will be conducted. The search strategy includes the databases APA PsycINFO, MEDLINE and Web of Science Core Collection from inception to 8 September 2025. It is supplemented by screening reference lists, trial registries, grey literature and outreach to relevant research groups. Eligible trials must include at least one validated measure of dysfunctional cognitions administered at minimum pre- and post-treatment, and clinical outcomes assessed at post-treatment and follow-up. The two primary outcomes are (1) child-reported symptom severity and (2) clinician-rated clinical severity. Data will be harmonised for dysfunctional cognition scores, moderators (age, gender, socioeconomic status, comorbidity), and primary outcomes. One-stage Bayesian mixed-effects models will examine whether changes in dysfunctional cognitions predict improvements in primary outcomes and whether these effects are moderated by individual characteristics. Missing data will be addressed using multiple imputation within the Bayesian framework, and study-level heterogeneity will be modelled using random intercepts and slopes. ETHICS AND DISSEMINATION: All datasets will be de-identified and managed under General Data Protection Regulation standards. Each included trial will have ethical approval permitting data sharing and reuse, and the secondary analysis of the shared datasets has been approved by the University of Amsterdam. Findings will be disseminated via a peer-reviewed publication, scientific conferences and open sharing of analysis scripts and harmonisation procedures. PROSPERO REGISTRATION NUMBER: CRD420251139130.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".