What Can We Learn From the Past? Pandemic Health Care Workers’ Fears, Concerns, and Needs: A Review
Bibliographic record
Abstract
BACKGROUND: Health care workers (HCWs) have been engaged in fighting dangerous epidemics for hundreds of years, more recently in severe acute respiratory syndrome, H1N1, Middle East respiratory syndrome, and now coronavirus disease 2019. A consistent feature of epidemic disease results is that health care systems and HCWs are placed under immense strain. METHODS: A focused narrative review was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to examine the main concerns and anxieties faced by HCWs during recent epidemics and to determine the supports deemed most important to those HCWs to keep them at the frontline. PubMed, Web of Science, and the Cochrane Library were searched in March 2020 using terms "Healthcare" OR "Medical" AND "Staff" OR "Workers" OR "Front line" AND "Concerns" OR "Anxiety" OR "Stress" AND "Pandemic" Or "Epidemic." RESULTS: Twenty-five studies that reported the concerns and expectations of an estimated 13,793 HCWs in 10 countries (Canada, China, Greece, Hong Kong, Japan, Liberia, Netherlands, Saudi Arabia, Singapore and Taiwan) during pandemic situations were identified. Health care workers identified personal and family safety, appreciation, and the provision of personal protective equipment and adequate rest as primary concerns. Informal psychological supports were favored over formal employment-based group interventions. DISCUSSION: Despite being hailed by the media as heroes, HCWs face social stigmatization and experienced high levels of anxiety and fear regarding personal safety and the health of their colleagues and family. Health care workers are more likely to seek peer-to-peer psychological support but also benefit from knowing that formal psychological supports are available to them.
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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 | 0.007 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".