Mental health concerns and needs of international students in higher education settings: A scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: The transition to higher education is a significant milestone for many individuals; however, it also brings new stressors and challenges, particularly for international students adjusting to life in a foreign country. Despite the increasing diversity of student populations globally, there remains a gap in existing reviews that capture the full scope of international student mental health concerns and needs. Existing reviews on the mental health and psychosocial adjustment of international students often concentrate on acculturation stress, thus overlooking other mental health concerns such as depression and anxiety, as well as positive mental health experiences like increased well-being. Meanwhile, other reviews tend to focus more heavily on specific regions, such as the United States and Australia, or student populations, particularly East-Asian students. While valuable, this focus may limit our understanding of the diverse mental health experiences of international students. OBJECTIVE: The objective of this scoping review is to map and summarize research on international students' mental health experiences and concerns (e.g., depression) as well as factors influencing their well-being (e.g., social support and institutional resources). METHODS: A search strategy guided by the Joanna Briggs Institute (JBI) Manual of Evidence Synthesis has been developed according to the Population, Concern, and Context (PCC) framework and will be applied to four electronic databases (i.e., MEDLINE, Embase, PsycInfo, and CINAHL). Two reviewers will pilot the selection strategy on subsets of 10 articles until a 90% agreement rate is achieved. Once this rate is reached, a single reviewer will screen the remaining articles independently. Two reviewers will pilot data extraction on subsets of 10 included studies, after which one reviewer will proceed independently. Main findings will be presented through descriptive statistics, using tables and figures. EXPECTED CONTRIBUTIONS: This scoping review will assess existing literature on the mental health needs and experiences of international students, highlighting overlooked issues, such as challenges beyond acculturation stress and the experiences of underrepresented student populations, including those studying outside of Western countries. Ultimately, the findings may identify areas for further research and inform educational institutions and mental health professionals in developing support resources that can effectively address diverse needs of international students.
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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 | 0.109 | 0.082 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.013 | 0.012 |
| Bibliometrics | 0.024 | 0.016 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.046 | 0.010 |
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".