SARS/MERS/SARS-CoV-2 Outbreaks and Burnout Syndrome among Healthcare Workers. An Umbrella Systematic Review
Bibliographic record
Abstract
The coronavirus-19 (COVID-19) pandemic is putting a severe strain on all healthcare systems. Several occupational risk factors are challenging healthcare workers (HCWs) who are at high risk of mental health outcomes, including Burnout Syndrome (BOS). BOS is a psychological syndrome characterized by emotional exhaustion, depersonalization, and low personal accomplishment. An umbrella review of systematic reviews and meta-analyses concerning BOS and coronavirus (SARS/MERS/SARS-CoV-2) outbreaks was carried out on PubMed Central/Medline, Cochrane Library, PROSPERO, and Epistemonikos databases. Data relating to COVID-19 is insufficient, but in previous SARS and MERS outbreaks about one-third of HCWs manifested BOS. This prevalence rate is similar to the figure recorded in some categories of HCWs exposed to chronic occupational stress and poor work organization during non-epidemic periods. Inadequate organization and worsening working conditions during an epidemic appear to be the most likely causes of BOS. Preventive care and workplace health promotion programs could be useful for protecting healthcare workers during pandemics, as well as during regular health activities.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".