Need to Culturally Adapt and Improve Access to Evidence-Based Psychosocial Interventions for Canadian South-Asians: A Call to Action
Bibliographic record
Abstract
Research into social determinants of mental and emotional health problems highlighted the need to understand the cultural factors. Mental health of immigrants is influenced by a variety of cultural, psychological, social, and economic factors. There is some evidence to suggest that South Asian people have higher rates of mental and emotional health problems than the rest of the Canadian population. Limited research also suggests that psycho-social factors are highly likely to be responsible for these high rates of mental health problems. These psychosocial factors may be impeding access and engagement with the services. These socially determined emotional and mental health problems are more likely to respond to psychosocial interventions than biological treatments. Evidence-based psychosocial interventions such as Cognitive Behaviour Therapy (CBT) and Acceptance and Commitment Therapy (ACT) might offer the way forward. CBT can be offered in a low-cost, low intensity format in a variety of settings, thus addressing the attached stigma. However, these interventions need to be culturally adapted, as these are underpinned by a Western value system. CBT has been culturally adapted and found to be effective in this group elsewhere. This opinion paper describes the need to enhance research on psychosocial determinants of the mental and emotional health problems, status, and the psychosocial determinants of health amongst South Asians in Canada to inform our understanding of the cultural specificity of psychosocial interventions.
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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 | 0.053 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.006 | 0.012 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".