Bibliographic record
Abstract
OBJECTIVE: The purpose of this scoping study was to identify and describe the principles and characteristics embedded in workplace mental health antistigma initiatives. Research in this area is diffuse and not well synthesized. Therefore, a scoping study is useful in generating a breadth of coverage and identifying all relevant literature on the topic regardless of study design. Results will inform evaluation strategies and can be used to distinguish the effectiveness of particular elements in future research. METHODS: The "York Framework," a five-stage methodological design (with an optional sixth stage) was used as the structure for this study. Eleven peer-reviewed and gray-literature databases were searched (2000-2011), and an extensive Internet review was also conducted. Two reviewers independently reviewed all abstracts to determine study selection. A data chart consisting of key issues and themes was utilized to extract data from the included studies. Preliminary results were used to inform a stakeholder consultation with seven international experts. RESULTS: Twenty-two antistigma interventions were included in the study. Most of the initiatives have appeared in the past four years and across geographic boundaries, reflecting the growing international interest in mental health in the workplace. A large proportion of the interventions utilize educational approaches to reducing stigma, and a substantial number target military personnel. CONCLUSIONS: Stronger evidence for effective practices needs to be established through the use of standardized workplace-specific interventions, reliable and valid evaluation tools, and overall enhanced scientific rigor.
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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 | 0.049 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.029 | 0.025 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 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".