International Students and Mental Health
Bibliographic record
Abstract
This study aimed to explore international students' perceptions regarding their mental health challenges and the availability of support systems in Ontario's colleges and universities. Using a quantitative research method, we developed 15 survey questions to collect comprehensive data from 70 international students over the age of 18. The findings revealed that many respondents reported experiencing feelings of depression, anxiety, and stress while navigating their studies in Canada. The key factors contributing to these mental health challenges included a lack of awareness regarding available mental health support services, cultural differences, language barriers, and experiences of discrimination. Additionally, many students highlighted the urgent need for increased awareness of culturally and linguistically appropriate mental health support services. A unique aspect identified in this research was the stigma associated with seeking help, particularly among male international students, who often expressed fear surrounding mental health support. This study contributes valuable insights into the mental health experiences of international students by identifying specific gaps in current support systems and emphasizing the necessity for culturally competent services. Based on these findings, practical and policy recommendations include enhancing accessibility to mental health resources, training staff in cultural sensitivity, and developing targeted programs to address international students' unique challenges.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".