The causal effect of switching from precarious to standard employment on mortality in Sweden
Bibliographic record
Abstract
Abstract Background Precarious employment (PE) is a well-known social determinant of health and health inequalities, yet the effect of PE on mortality has not been explored sufficiently and high-quality longitudinal studies are lacking. When studying this effect, several methodological factors must be considered, one of them being the immortal time bias or prevalent user bias. A framework that helps us overcome these biases is the target trial. Therefore, the aim of this study is to estimate the causal effect of switching from precarious to standard employment (SE) on the 12-year risk of all-cause mortality among precariously employed workers aged 20-55 in Sweden. Methods We emulated the target trial as a series of 11 target trials (starting at any year between 2005 and 2016), such that each individual may participate in multiple trials using Swedish register data (N = 251274). We classified individuals as: a) workers that at baseline (start) move from PE to SE and then followed while in SE or b) continuation of PE over follow-up. All-cause mortality was measured from 2006 to 2017. We pooled data for all 11 emulated trials and used pooled logistic regression to estimate intention-to-treat effects via hazard ratios and standardized survival curves. Results The following results are preliminary. Individuals that continued on PE were 185,480 and those that initiated SE were 65,794. Over the 12-year follow-up, 1553 individuals died. The estimated observational analogue of the intention-to-treat 12-year survival difference for all cause-mortality between workers that continued on PE and those that initiated SE was of -0.2%, and the HR:0.82, 95%CI:0.72-0.94. Conclusions The following conclusions are preliminary. According to our results, we find indication that shifting from PE to SE decreased the risk of death. Our study highlights the crucial role of decent employment conditions for health. Key messages
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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 | 0.043 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".