Cumulated and most recent job control and risk of disability pension in the Danish Work Life Course Cohort (DaWCo)
Bibliographic record
Abstract
BACKGROUND: Previous studies have found low job control to be associated with a higher risk of disability pension (DP). Most studies have measured job control only at one time-point, and there is a lack of knowledge regarding the role of exposure duration. This study examines the prospective association between job control and DP measuring exposure both cumulated throughout work life and most recent. METHODS: We included 712 519 individuals (about 4.5 million person-years) from The Danish Work Life Course Cohort which follows young employees in Denmark from their entry into the labour market. Job control was assessed with a job exposure matrix and DP with register data on public transfer payments. We adjusted for several potential life course confounders, including physical demands at work and parental socioeconomic position and psychiatric and somatic diagnoses. RESULTS: Employees in occupations with low job control had a higher risk of DP. There were effects of both cumulated and most recent job control when mutually adjusted. Fully adjusted hazard ratios (HRs) were 1.14 [95% confidence intervals (CIs) 1.11-1.17] and 1.15 (95% CI 1.02-1.29) for cumulated and most recent job control, respectively. Without mutual adjustment, estimates were 1.15 (95% CI 1.13-1.18) and 1.55 (95% CI 1.39-1.72) for cumulated and most recent low job control, respectively. CONCLUSIONS: Low job control predicts a higher risk of DP, even after adjustment for physical demands at work. The results indicate both gradual and short-term effects of low job control on DP risk.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".