An Analysis of Campus Culture, Mental Health, and Drinking at Three Canadian Universities
Bibliographic record
Abstract
Although many individual risk factors have been identified for student mental health problems and alcohol misuse, there is a relative paucity of research that examines how variables, such as campus environment, contribute to students’ experiences of these problems. This study examined a series of perceived campus environment factors (e.g., feeling valued, feeling they fit in, believing faculty care about them, perceived administrative concern for mental health and substance abuse) and the relationships among these perceived campus environment variables and students’ mental well-being, risk of harmful drinking, and their willingness to seek help for a substance use or mental health concern. A total of 1,885 first-year undergraduate university students including 938 females, 936 males and 11 “non-binary” participants, from three geographically diverse Canadian university sites, completed online surveys. The results demonstrated significant associations among the perceived campus environment variables and both mental health and alcohol misuse outcomes. It was also observed that whether a student lived in residence or off campus significantly affected which campus environment factors were most associated with their reported mental health and alcohol misuse. Additionally, willingness to help-seek was related with students’ perceptions of campus culture. These patterns globally demonstrated the importance of campus culture for student mental health and alcohol use. Strengths and limitations of the study, as well as directions for future research on the relations of campus culture to mental health, substance use, and help-seeking are discussed.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".