Coworker health awareness training: An evaluation
Bibliographic record
Abstract
Mental health issues are extremely common in the developed world, with as many as one in five people experiencing a mental illness every year. There are a host of negative outcomes for both organizations and individuals with mental health problems. One strategy that previous research has shown to be effective in reducing stigma around mental illness in organizations is mental health awareness training (MHAT) for leaders. The aim of the current study was to evaluate a complementary program to the MHAT, the Coworker Health Awareness Training Program (CHAT) for employees. The present study uses a wait‐list control design (N = 40) to test the effectiveness of the CHAT on various outcomes, such as knowledge, stigma, self‐efficacy in recognizing and addressing mental health problems, mental health promotion intentions, and willingness to use resources. Results showed that those employees who were trained with the CHAT displayed increases in knowledge, self‐efficacy, mental health promotion, and willingness to use resources. These results provide support for the effectiveness of the CHAT, and have practical and methodological implications.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".