A Survey of Mental Health Services at Post-Secondary Institutions in Alberta
Bibliographic record
Abstract
OBJECTIVES: The relatively high prevalence of mental health problems among students at post-secondary institutions in Canada is well documented; in contrast, less is known about the adequacy of mental health services available to Canadian post-secondary students on campuses. Our study sought to examine the current state of campus mental health initiatives and services in Alberta as well as the extent to which resources identified in mental health literature as being key in mental health problem prevention and promotion appear to be available. METHODS: A 60-question, online survey was sent to staff (primarily front-line workers; n = 45) at Alberta's 26 publicly funded post-secondary institutions. Responses were organized according to small (less than 2000 students), medium (2000 to 10 000 students), and large (10 000 or more students) institutions. RESULTS: All of Alberta's post-secondary institutions were represented in the responses. Mental health initiatives and services are available, to varying extent, at all of Alberta's post-secondary institutions. However, many institutions do not have initiatives and (or) services aimed at identifying students with mental health problems or policies for monitoring their mental health services. Additionally, smaller institutions are less likely to offer certain services (for example, gatekeeper training and campus medical services), compared with larger ones. Finally, a systematic review or an evaluation of services appears to be infrequently conducted. CONCLUSIONS: These findings highlight the need for post-secondary institutions in Alberta, and by extension in Canada, to develop and institute a comprehensive strategy to evaluate and optimize the delivery of mental health initiatives and services.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".