COVID-19, SARS-CoV-2: Impact on healthcare workers in the pandemic’s initial months: Rapid review
Bibliographic record
Abstract
On March 11, 2020 the World Health Organisation declared the SARS-CoV-2 viral outbreak a pandemic. This rapid review aimed to identify the pandemic's impact on frontline healthcare workers during the viral outbreak's initial months. Database searches December 1, 2019 to August 29, 2020 retrieved 18 relevant studies. Findings showed that healthcare workers internationally were negatively impacted by the pandemic. Compared to non-frontline healthcare workers a significantly greater proportion of frontline healthcare workers experienced: burnout, stress, and stressors regarding: childcare, job interference with work-family balance and difficulty getting off-duty time. Compared to male physicians, a significantly greater proportion of female physicians scored low for psychological well-being. Mean scores for stress were significantly higher among females and young healthcare workers (22 to 35 years). Mean scores for anxiety were significantly higher for: nurses compared to technicians, healthcare workers reporting extreme lack of protective equipment and those aged > 30 years. The prevalence of depression among frontline healthcare workers across studies in this review ranged from 9% to 51%. The prevalence of sleep issues ranged from 24% to 60% with some reporting nightmares. However, these studies lack homogeneity. Healthcare workers experienced fear of: contracting the virus (89.8%), spreading it to family (91.3%) and fear of an uncontrollable epidemic (86.8%). Over 90% reported skin lesions due to prolonged use of personal protective equipment. Many lost their lives to the SARS-CoV-2 virus. One prominent impact of the SARS-CoV-2 pandemic is the reported loss of healthcare worker's lives and this paper wishes to pay them tribute.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".