Culturally adapted cognitive behavioral therapy for psychosis (CaCBTp): A review of key features of cultural adaptation and considerations for psychologists.
Bibliographic record
Abstract
Cognitive behavioral therapy for psychosis is an effective treatment for psychosis. However, psychosis presents differentially according to an individual's cultural context, and it is currently unclear which methods have been used to formulate culturally adapted cognitive behavioral therapy for psychosis (CaCBTp). The current systematic review examines the approaches to CaCBTp that have been evaluated to date and comments on preliminary evidence for the efficacy of CaCBTp. Key features of CaCBTp interventions are discussed in reference to broader cultural adaptations of psychosocial interventions for psychosis and culturally adapted cognitive behavioral therapy for other disorders. Overall, our results identified 12 studies and highlighted five overarching themes of cultural adaptation that clinicians should integrate into the design of future CaCBTp interventions, including family members in treatment, targeting stigma, relying on spiritual leaders, using multifaceted models of mental health, and ensuring adequate language match. The results of this review also highlight the paucity of literature in global CaCBTp interventions, as only 10 studies examining CaCBTp interventions were found. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".