Canadian Post-Secondary Student Mental Health and Wellbeing: A Descriptive Analysis
Bibliographic record
Abstract
BACKGROUND: Post-secondary students are considered to be at risk of chronic stress and languishing mental health, but there has been little analysis of the available population-level data. The purpose of this study was to examine the overall and sex-specific prevalence of self-reported stress, distress, mental illness, and help seeking behaviours among Canadian post-secondary students. METHODS: Using the 2016 National College Health Assessment II dataset, we analyzed frequencies for each item of interest, stratified by sex. Chi-square analyses were conducted to test for statistical significance between groups. RESULTS: A large proportion of students self-reported high stress levels as well as diagnoses of depression and anxiety. More female students reported higher levels of stress and distress than did male students. Similarly, more female students reported having sought help for mental health related difficulties compared to male students. While all students demonstrated a willingness to seek help in the future, this was true for significantly more females than males. CONCLUSIONS: Findings point to the need for increased upstream approaches, including mental health promotion and mental illness prevention to minimize stress and distress among post-secondary 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".