Mental health literacy : A review of applications and effectiveness in the higher education workplace
Bibliographic record
Abstract
A growing body of international evidence indicates that education, prevention efforts and early intervention are critical to the mental health of our populations. These efforts are taking place across social systems and within organizational structures including public health, educational institutions and workplaces. Purpose: To review current literature in an effort to identify themes related to successful workplace-based mental health literacy (MHL) programs, specifically in the area of higher education. The purpose was also to use a UBC case study to highlight potential connections between existing evidence and higher education applications. Method: The bodies of literature consulted for the review were reflective of the unique interplay between the concept (MHL), context (workplaces) and setting (higher education) of this project. The supporting case study synthesizes the training outcomes of staff and faculty participants in two mental health literacy (MHL) education programs, and outlines the results of post-training surveys designed to measure MHL measures collected from 191 training participants. Findings: The project identified multiple sets of promising practices in areas of effective workplace health promotion, successful mental health literacy applications, and higher education workplace interventions. It also revealed a gap in current research examining MHL outcomes within higher education workplaces. The UBC case study results aim to close this gap by demonstrating the value and effectiveness of Mental Health First Aid and The Working Mind in increasing MHL of staff and faculty. Next steps: The aim of this paper is to grow the emerging research in this area as well as support the current MHL training efforts within UBC’s department of Human Resources.
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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 | 0.012 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".