Work-related violence and depressive disorder among 955,573 employees followed for 6.99 million person-years. The Danish Work Life Course Cohort study
Bibliographic record
Abstract
BACKGROUND: We examined the association between probability of work-related violence and first diagnosis of depressive disorder whilst accounting for the potential selection of individuals vulnerable to depression into occupations with high probability of work-related violence. METHODS: Based on a pre-published study protocol, we analysed nationwide register data from the Danish Work Life Course Cohort study, encompassing 955,573 individuals followed from their entry into the workforce, and free from depressive disorder before work-force entry. Depressive disorder was measured from psychiatric in- and outpatient admissions. We measured work-related violence throughout the worklife by the annual average occupational risk of violence exposure. Using Cox proportional hazards regression, we examined the longitudinal association between work-related violence (both past year and cumulative life-long exposure) and first depressive disorder diagnosis, whilst adjusting for numerous confounders including parental psychiatric and somatic diagnoses, childhood socioeconomic position, and health services use before workforce entry. RESULTS: The risk of depressive disorder was higher in individuals with high probability of past year work-related violence (hazard ratio: 1.11, 95% CI: 1.06-1.16) compared to employees with low probability of exposure, after adjustment for confounders. Among women, associations were robust across industries, whereas among men, associations were limited to certain industries. LIMITATIONS: Violence was measured on the job group and not the individual level, likely resulting in some misclassification of the exposure. CONCLUSIONS: Work-related violence may increase the risk of depressive disorder, independent of pre-existing risk factors for depressive disorder. These findings underline the importance of preventing work-related violence.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".