Factors associated with work performance and mental health of healthcare workers during pandemics: a systematic review and meta-analysis
Bibliographic record
Abstract
Introduction Healthcare workers' work performance and mental health are associated with positive mental health outcomes and directly related to increased productivity and decreased disability costs. Methods We conducted a systematic review to identify factors associated with work performance of healthcare workers during a pandemic and conducted a meta-analysis of the prevalence of mental health outcomes in this context. Primary papers were collected and analysed using the Population/Intervention/Comparison/Outcome framework and using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. To critically appraise the studies included in the review, we used the AXIS appraisal tool to assess each cross-sectional study's quality. Results The study identified nine factors associated with the work performance and mental health of healthcare workers, including experiencing feelings of depression, anxiety, having inadequate support, experiencing occupational stress, decreased productivity, lack of workplace preparedness, financial concerns associated with changes in income and daily living, fear of transmission and burnout/fatigue. Conclusion There is a rapidly rising need to address the work performance and mental health of healthcare workers providing timely care to patients. Regular and sustained interventions, including the use of information and communication technologies such as telehealth, are warranted.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.026 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".