Strategies to support the mental health and well-being of migrant LGBTQIA+ college and university students: a scoping review protocol
Bibliographic record
Abstract
OBJECTIVE: This review will identify and explore strategies employed by health care professionals, higher education institutions, and organizations to support the mental health and well-being of migrant lesbian, gay, bisexual, transgender, queer, intersex, asexual, and more (LGBTQIA+) college and university students. INTRODUCTION: Migrant LGBTQIA+ students face substantial challenges to their identity formation and social development while studying in their newly settled countries. Little is known about how colleges and universities support LGBTQIA+ students' mental health and well-being from the perspectives of migration status, stigma, and discrimination. Understanding what is known about strategies to support migrant LGBTQIA+ students can inform future policy directions for promoting LGBTQIA+ mental health and well-being in the context of higher education. INCLUSION CRITERIA: This review will incorporate literature from all geographical contexts that focuses on strategies to support the mental health and well-being of migrant LGBTQIA+ college and university students. Literature not related to LGBTQIA+ migrant students will be excluded. METHODS: The JBI methodology for scoping reviews will be followed, and the review will be reported in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews (PRISMA-ScR) guidelines. Several databases and sources of gray literature will be searched from 2004 onward. The review will include literature published in any language and will be independently screened by 2 reviewers. A modified JBI data extraction tool will be used and data will be presented as diagrams along with narrative summaries to answer the review questions. REVIEW REGISTRATION: Open Science Framework https://osf.io/bj2hu/.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".