Low-quality employment trajectories and the risk of common mental health disorders among individuals with Swedish and foreign background – a register-based cohort study
Bibliographic record
Abstract
OBJECTIVE: This study aimed to examine the effects of low-quality employment trajectories on severe common mental disorders (CMD) according to Swedish and foreign background. METHODS: In this longitudinal study based on Swedish population registries (N=2 703 687), low- and high-quality employment trajectories were the main exposures observed across five years (2005-2009), with severe CMD as outcome variable (2010-2017). Adjusted hazard ratios (HR) were calculated by means of Cox regression models and stratified according to Swedish and foreign background [first-generation (i) EU migrants, (ii) non-EU migrants, (iii) second-generation migrants, (iv) Swedish-born of Swedish background] and sex. The reference group was Swedish-born of Swedish background in a constant high-quality employment trajectory. RESULTS: Second-generation migrants had an increased risk of CMD compared to Swedish-born of Swedish background when following low-quality employment trajectories [eg, male in constant low-quality HR 1.54, 95% confidence interval (CI) 1.41-1.68]. Female migrant workers, especially first-generation from non-EU countries in low-quality employment trajectories (eg, constant low-quality HR 1.66, 95% CI 1.46-1.88), had a higher risk of CMD compared to female Swedish-born of Swedish background. The risk for CMD according to employment trajectories showed little differences between first- and second-generation migrants. CONCLUSION: Low-quality employment trajectories appear to be determinants of risk for CMD in association with Swedish or foreign background of origin and sex. Our study shows a higher risk for severe CMD in second-generation and non-EU migrant compared to Swedish-born of Swedish background in constant low-quality employment. Further qualitative research is recommended to understand the mechanism behind the differential mental health impact of low-quality employment trajectories according to foreign background.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".