Managers’ Influence on the Prevention of Common Mental Disorders in the Workplace
Bibliographic record
Abstract
OBJECTIVE: To investigate the association among managers' attitudes toward subordinates with common mental disorders (CMDs), self-confidence in supporting these subordinates, and managerial preventive actions (MPAs). METHODS: A cross-sectional study was conducted among Swedish managers (n = 2988) and two types of MPAs: reviewing assignments and work situation (MPA-review), and talking about CMD at the workplace (MPA-talk). Binary logistic regression models were applied and adjusted for individual and organizational covariates. RESULTS: Managers with negative attitudes toward subordinates with CMD were less likely to have done both MPAs. Managers with higher self-confidence in supporting these subordinates were more likely to have done both MPAs compared with managers with lower self-confidence. CONCLUSIONS: Managerial negative attitudes toward CMD and self-confidence in supporting subordinates with CMD have a role in MPAs and should be addressed in manager training programs to encourage preventive actions.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".