Work‐related suicide: Evolving understandings of etiology & intervention
Bibliographic record
Abstract
Previously published analyses of suicide case investigations suggest that work or working conditions contribute to 10%-13% of suicide deaths. Yet, the way in which work may increase suicide risk is an underdeveloped area of epidemiologic research. In this Commentary, we propose a definition of work-related suicide from an occupational health and safety perspective, and review the case investigation-based and epidemiologic evidence on work-related causes of suicide. We identified six broad categories of potential work-related causes of suicide, which are: (1) workplace chemical, physical, and psychosocial exposures; (2) exposure to trauma on the job; (3) access to means of suicide through work; (4) exposure to high-stigma work environments; (5) exposure to normative environments promoting extreme orientation to work; and (6) adverse experiences arising from work-related injury or illness. We summarise current evidence in a schema of potential work-related causes that can also be applied in workplace risk assessment and suicide case investigations. There are numerous implications of these findings for policy and practice. Various principle- and evidence-based workplace intervention strategies for suicide prevention exist, some of which have been shown to improve suicide-prevention literacy, reduce stigma, enhance helping behaviours, and in some instances maybe even reduce suicide rates. Prevailing practice in workplace suicide prevention, however, overly emphasises individual- and illness-directed interventions, with little attention directed to addressing the working conditions that may increase suicide risk. We conclude that a stronger emphasis on improving working conditions will be required for workplace suicide prevention to reach its full preventive potential.
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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 | 0.021 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".