Global Mental Health and Services for Migrants in Primary Care Settings in High-Income Countries: A Scoping Review
Bibliographic record
Abstract
Migrants are at a higher risk for common mental health problems than the general population but are less likely to seek care. To improve access, the World Health Organization (WHO) recommends the integration of mental health services into primary care. This scoping review aims to provide an overview of the types and characteristics of mental health services provided to migrants in primary care following resettlement in high-income countries. We systematically searched MEDLINE, EMBASE, PsycInfo, Global Health, and other databases from 1 January 2000 to 15 April 2020. The inclusion criteria consisted of all studies published in English, reporting mental health services and practices for refugee, asylum seeker, or undocumented migrant populations, and were conducted in primary care following resettlement in high-income countries. The search identified 1627 citations and we included 19 studies. The majority of the included studies were conducted in North America. Two randomized controlled trials (RCTs) assessed technology-assisted mental health screening, and one assessed integrating intensive psychotherapy and case management in primary care. There was a paucity of studies considering gender, children, seniors, and in European settings. More equity-focused research is required to improve primary mental health care in the context of global mental health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".