Sickness absence due to common mental disorders and antidepressant prescription among health and social care workers during compared with before the COVID-19 pandemic: a nationwide register study of the Swedish population
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: Essential workers, particularly in health care and social services, were critical during the peak of the COVID-19 pandemic, yet their mental health outcomes remain understudied. We examined changes in (1) sickness absence (SA) due to common mental disorders (CMDs), and (2) antidepressant prescription in health and social care workers during versus pre-pandemic periods. METHODS: Using Swedish national registers, we included health care and social workers (aged 19-65 years) from 2018 to 2021. We compared quarterly incidence rate (IR) trends for SA >90 days due to CMDs, and for antidepressant prescriptions, across 2 periods: pre-pandemic (January 2018 to February 2020) and during the pandemic (March 2020 to December 2021) using interrupted time-series analysis. Analyses accounted for seasonality and were stratified by age, sex, and education. RESULTS: There was no evidence of a difference in IR trends for SA >90 days or for antidepressant prescription pre-pandemic versus during the pandemic for the entire sector. However, trends of IR for antidepressant prescription increased among workers in medical laboratories (8.7% per quarter change; 95% CI, 4.4%-13.1%) and hospitals (1.5%; 95% CI, 0.6%-2.5%) and decreased per quarter for ambulance transports (5.4%; 95% CI, 0.4-10.0%). Women (10.9%; 95% CI, 7.2%-14.7%) and highly educated individuals (10.0%; 95% CI, 4.1%-16.1%) working in medical laboratories as well as 19-25-year-olds working in primary and dental care (7.3%; 95% CI, 1.7%-13.1%) also experienced an increase in antidepressant prescription. CONCLUSIONS: Although overall trends in SA >90 days and in antidepressant prescription remained stable, certain occupational and sociodemographic groups were found to be affected in regard to antidepressant prescription. These groups warrant targeted support in future health crises.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it