The overall fractions of coronary heart diseases and depression attributable to multiple dependent psychosocial work factors in Europe
Bibliographic record
Abstract
OBJECTIVES: The literature is nonexistent on the assessment of overall fractions of diseases attributable to multiple dependent psychosocial work factors. The objectives of the study were to calculate the overall fractions of coronary heart diseases (CHD) and depression attributable to multiple dependent psychosocial work factors in 35 European countries. METHODS: We used already published fractions of CHD and depression attributable to each of the following psychosocial work factors: job strain, effort-reward imbalance, job insecurity, long working hours, and workplace bullying. We took all exposures and their correlations into account to calculate overall attributable fractions. Wald tests were performed to test differences in these overall attributable fractions between genders and between countries. RESULTS: The overall fractions of CHD and depression attributable to all studied psychosocial work factors together were found to be 8.1% [95% CI: 2.0-13.9] and 26.3% [95% CI: 16.2-35.5] respectively in the 35 European countries. There was no difference between genders and between countries. CONCLUSION: Our study showed that the overall fractions attributable to all studied psychosocial work factors were substantial especially for depression. These overall attributable fractions may be particularly useful to evaluate the burden and costs attributable to psychosocial work factors, and also to inform policies makers at European level.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".