Unequal access? Use of sickness absence benefits by precariously employed workers with common mental disorders: a register-based cohort study in Sweden
Bibliographic record
Abstract
OBJECTIVE: This study compares the use of sickness absence benefits (SABs) due to a common mental disorder (CMD) between precariously employed and non-precariously employed workers with CMDs. DESIGN: Register-based cohort study. PARTICIPANTS: The study included 78 215 Swedish workers aged 27-61 who experienced CMDs in 2017, indicated by a new treatment with selective serotonin reuptake inhibitors (SSRIs). Excluded were those who emigrated or immigrated, were self-employed, had an annual employment-based income <100 Swedish Krona, had >90 days of unemployment per year, had student status, had SABs due to CMDs during the exposure measurement (2016) and the two previous years, had an SSRI prescription 1 year or less before the start of the SSRI prescription in 2017, had packs of >100 pills of SSRI medication, had a disability pension before 2017, were not entitled to SABs due to CMDs in 2016, and had no information about the exposure. OUTCOME: The first incidence of SABs due to CMDs in 2017. RESULTS: The use of SABs due to a CMD was slightly lower among precariously employed workers compared with those in standard employment (adjusted OR [aOR] 0.92, 95% CI 0.81 to 1.05). Particularly, women with three consecutive years in precarious employment had reduced SABs use (aOR 0.48, 95% CI 0.26 to 0.89), while men in precarious employment showed weaker evidence of association. Those in standard employment with high income also showed a lower use of SABs (aOR 0.74, 95% CI 0.67 to 0.81). Low unionisation and both low and high-income levels were associated with lower use of SABs, particularly among women. CONCLUSIONS: The study indicates that workers with CMDs in precarious employment may use SABs to a lower extent. Accordingly, there is a need for (1) guaranteeing access to SABs for people in precarious employment and/or (2) reducing involuntary forms of presenteeism.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".