Efficacy and Moderators of Cognitive Behavioural Therapy for Psychosis Versus Other Psychological Interventions: An Individual-Participant Data Meta-Analysis
Bibliographic record
Abstract
Background: Study-level meta-analyses have demonstrated the efficacy of cognitive-behavioural therapy for psychosis (CBTp). Limitations of conventional meta-analysis may be addressed using individual-participant-data (IPD). We aimed to determine a) whether results from IPD were consistent with study-level meta-analyses and b) whether demographic and clinical characteristics moderate treatment outcome. Methods: We systematically searched PubMed, Embase, PsychInfo and CENTRAL. Authors of RCTs comparing CBTp with other psychological interventions were contacted to obtain original databases. Hierarchical mixed effects models were used to examine efficacy for psychotic symptoms. Patient characteristics were investigated as moderators of symptoms at post-treatment. Sensitivity analyses were conducted for risk of bias, treatment format and study characteristics. Results: We included 14 of 23 eligible RCTs in IPD meta-analyses including 898 patients. 10 RCTs minimised risk of bias. There was no significant difference in efficacy between RCTs providing IPD and those not (p>0.05). CBTp was superior vs. other interventions for total psychotic symptoms and PANSS general symptoms. No demographic or clinical characteristics were robustly demonstrated as moderators of positive, negative, general or total psychotic symptoms at post-treatment. Sensitivity analyses demonstrated that number of sessions moderated the impact of treatment assignment (CBTp or other therapies) on total psychotic symptoms (p=0.02). Conclusions: IPD suggest that patient characteristics, including severity of psychotic symptoms, do not significantly influence treatment outcome in psychological interventions for psychosis while investing in sufficient dosage of CBTp is important. IPD provide roughly equivalent efficacy estimates to study-level data although significant benefit was not replicated for positive symptoms. We encourage authors to ensure IPD is accessible for future research.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".