Mental Health among Canadian Postsecondary Students: A Mental Health Crisis?
Bibliographic record
Abstract
OBJECTIVE: Recent reports express concerns about a mental health crisis among postsecondary students. These assertions, however, often arise from surveys conducted in postsecondary settings that lack the broader context of a referent group. The objectives of this study were (1) to assess the mental health status of postsecondary students 18 to 25 years old from 2011 to 2017 and (2) to compare the mental health status of postsecondary students to nonstudents. METHODS: Prevalence was estimated for a set of mental health outcomes using seven annual iterations of the Canadian Community Health Survey (2011 to 2017). Logistic regression was used to derive odds ratio estimates comparing mental health status among postsecondary students and nonstudents, adjusting for age and sex. Random effects metaregression and meta-analyses techniques were used to evaluate trends in prevalence and odds ratio estimates over time. RESULTS: Over the study period, the prevalence of perceived low mental health, diagnosed mood and anxiety disorders, and past-year mental health consultations increased among female students, whereas binge drinking decreased among male students. With the exception of perceived stress, the odds of experiencing each mental health outcome were lower among postsecondary students compared to nonstudents. CONCLUSIONS: These findings do not support the idea that postsecondary students have worse mental health than nonstudents of similar age. The perception of a crisis may arise from greater help-seeking behavior, diminishing stigma, or increasing mental health literacy. Regardless, the observance of these trends provide an opportunity to address a previously latent issue.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".