Recommendations to Leverage the Palliative Nursing Role During COVID-19 and Future Public Health Crises
Bibliographic record
Abstract
With the daily number of confirmed COVID-19 cases and associated deaths rising exponentially, social fabrics on a global scale are being worn by panic, uncertainty, fear, and other consequences of the health care crisis. Comprising more than half of the global health care workforce and the highest proportion of direct patient care time than any other health professional, nurses are at the forefront of this crisis. Throughout the evolving COVID-19 pandemic, palliative nurses will increasingly exercise their expertise in symptom management, ethics, communication, and end-of-life care, among other crucial skills. The literature addressing the palliative care response to COVID-19 has surged, and yet, there is a critical gap regarding the unique contributions of palliative nurses and their essential role in mitigating the sequelae of this crisis. Thus, the primary aim herein is to provide recommendations for palliative nurses and other health care stakeholders to ensure their optimal value is realized and to promote their well-being and resilience during COVID-19 and, by extension, in anticipation of future public health crises.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".