The burden of grief: A scoping review of nurses’ and physicians’ experiences throughout the COVID-19 pandemic
Bibliographic record
Abstract
Coping with loss is an unfortunate reality faced by healthcare professionals, and the COVID-19 pandemic exacerbated this challenge for those who worked on the frontlines. Our scoping review aimed to comprehensively map the existing literature pertaining to the experiences of grief among nurses and physicians in the context of the pandemic. Six bibliographic databases were searched in 2022, and a targeted search of gray literature and citation chasing was also performed. After screening a total of 2920 records, we included 173 evidence sources in this review. Data was both analyzed descriptively (e.g., frequency counts and percentages) and using a qualitative content analysis approach. Our findings illuminate the myriad losses experienced by nurses and physicians throughout the pandemic. While the literature portrays the coping mechanisms healthcare professionals have developed personally, there is a pronounced need for increased institutional support to alleviate the burdens they carry.
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How this classification was reachedexpand
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) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".