Mental health interventions for African refugees resettled in North America: A systematic review
Bibliographic record
Abstract
The number of African refugees migrating to North America (the United States and Canada) has increased significantly over the past decade. Notwithstanding, the prevalence of mental health disorders among African refugees signals an urgent need to address them. We reviewed mental health interventions tailored to African refugees in North America, identified existing gaps, and suggested mental health services improvement recommendations. Using PRISMA guidelines, we identified ( n = 1,164), screened ( n = 989), assessed ( n = 79), and included ( n = 7) peer-reviewed articles detailing interventions that addressed mental health and its associated concerns among African refugees in North America. Our results showed that pre-migration perils and acculturation stressors exacerbated mental health concerns such as anxiety, depression, dysphoria, and post-traumatic stress disorder symptoms. Interventions that culturally adapted cognitive behavior therapy, peer support, and psycho-education effectively reduced mental health symptoms and improved life satisfaction. Future interventions should contextualize and incorporate African cultural beliefs and practices within community settings to promote mental health services.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".