Postsecondary Mental Health Policy in Canada: A Scoping Review of the Grey Literature: Politique de santé mentale post-secondaire au Canada: un examen de la portée de la littérature grise
Bibliographic record
Abstract
OBJECTIVE: Concerns surrounding the mental health and well-being of Canadian postsecondary students have increased in recent years, with data suggesting increases in the prevalence of self-reported stress and psychological distress. Strategies to address postsecondary mental health have emerged at the national, provincial, and institutional levels. While reviews of the academic literature on the subject have been conducted, a detailed review of the grey literature has not. The objective of this study was to map the current state of grey literature related to current or recommended action supporting postsecondary mental health and well-being in Canada, with a focus on policy documents and guiding frameworks. METHODS: We conducted a review following Arksey and O'Malley's 5-step framework for scoping reviews, as well as the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Our search was restricted to documents with a primary focus on postsecondary mental health, a national or provincial scope, and publication date between 2000 and 2019. RESULTS: While a national policy or guiding framework applicable to all postsecondary institutions across Canada does not yet exist, recommendations for policy at both the national and provincial levels were well aligned, emphasizing the need for a comprehensive approach to addressing mental health services through the use of a whole-campus approach that encompasses both upstream and downstream services. CONCLUSION: Postsecondary sector stakeholders should consider how existing policy documents and guiding frameworks can be used to inform evidence-based, institutionally specific action on postsecondary mental health. More work is required to align the fragmented action occurring across Canada and incentivize postsecondary institutions to create a sustainable, effective strategy to address the increasingly complex and unique mental health needs of their students, staff, and faculty.
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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 | 0.033 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.028 | 0.052 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".