Barriers and facilitators associated with the use of mental health services among immigrant students in high-income countries: a scoping review protocol
Bibliographic record
Abstract
BACKGROUND: While the mental health of immigrants is a growing issue that is attracting increasing interest from researchers, the same cannot be said for the mental health of immigrant students especially for international students. Indeed, the mental health of immigrant students and their use of mental health services are still poorly documented despite the significant increase in the number of these students in many high-income countries. This scoping review aims to providing an overview and exploring gaps in existing research regarding access to mental health care among immigrant students by identifying barriers and facilitators associated with the use of mental health services in high-income countries. METHODS: With the help of a professional librarian, we will develop a search strategy including several keywords such as mental health, mental illness, immigrant, students, immigrant students, or international students and access to care or use of mental health services. The following electronic databases will be searched (from their inception onwards): MEDLINE, APA PsycINFO, CINAHL, Web of Science Core Collection, Education Source, and Embase. Studies addressing access to and use of mental health care conducted on immigrant students (adolescent and above) in high-income countries will be included. Two reviewers will independently screen all citations, full-text articles, and abstract data. A narrative summary of findings will be conducted. Data analysis will involve quantitative (e.g., frequencies) and qualitative (e.g., content and thematic analysis) methods. DISCUSSION: The purpose of this scoping review is to better map the literature on the mental health of immigrant students and their use of mental health care services. In doing so, we aim to identify barriers and facilitators to access and use of mental health care. Identifying barriers and facilitators of mental health services by immigrant students will support the development of appropriate interventions that can help improve access and use of mental health services by immigrant students in high-income countries. SYSTEMATIC REVIEW REGISTRATION: Open Science Framework ( osf.io/a2rk6 ).
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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 | 0.098 | 0.074 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.015 | 0.016 |
| Bibliometrics | 0.022 | 0.016 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.046 | 0.008 |
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".