Effects of the Anti-stigma Workplace Intervention “Working Mind” in a Canadian Health-Care Setting: A Cluster-Randomized Trial of Immediate Versus Delayed Implementation
Bibliographic record
Abstract
OBJECTIVES: The Working Mind is a program designed to reduce stigmatizing attitudes toward mental illness, improve resilience, and promote mental health in the general workplace. Previous research has revealed positive program effects in a variety of workplace settings. This study advances previous work in implementing randomization and a control group to assess the intervention's efficacy. METHODS: The program was evaluated using a cluster-randomized design, with pretest, posttest, and a 3-month follow-up in 2 implementation groups across 4 sites. RESULTS: The Working Mind program was effective at decreasing mental health stigma and increasing self-reported resilience and coping skills at the pre-post assessment in both delivery groups. The program's effects were maintained to the time of 3-month follow-up. Qualitative data provided further evidence that participants benefited from the program. CONCLUSIONS: This study represents an advancement over past research and provides further support for efficacy of the Working Mind program. Directions for future research, including replication using rigorous methodological procedures and examination of program effects over longer follow-up intervals, are discussed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".