Development and Evaluation of Culturally Adapted CBT to Improve Community Mental Health Services for Canadians of South Asian Origin - Final Report 2023
Bibliographic record
Abstract
Phase 1: Five themes were identified from the analysis: Awareness and preparation: matters that impact the individual’s cognizance of therapy and mental illness Access and delivery of care: SA Canadians’ perception of barriers, facilitators and access to treatment Assessment and engagement: experiences of receiving helpful treatment Adjustments to therapy: modifications and suggestions to standard CBT Ideology and ambiguity: racism, immigration, discrimination and other socio-political factors that affect mental health and access to care. Phase 2: The CaCBT group scored lower than standard CBT on all symptom measures. The CaCBT group exhibited significantly greater levels of engagement and satisfaction than the standard CBT group, as evidenced by VSSS and WAI results. South Asians born in Canada showed greater reduction in depressive symptoms (approaching statistical significance) than those born outside of Canada, indicating that CaCBT may be more widely accepted among those born in Canada. The study had a high recruitment response and retention rate, demonstrating the feasibility of CaCBT. Phase 3: There was significant increase in knowledge of both multicultural counselling skills and cultural adaptation after training. There was a significant increase in Southampton Adaptation Framework knowledge after training, with a 37% average normalized gain in knowledge Average satisfaction post-training was 91.66%.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".