Nurses’ experiences of ethical responsibilities of care during the COVID-19 pandemic
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has forced rapid and widespread change to standards of patient care and nursing practice, inevitably leading to unprecedented shifts in the moral conditions of nursing work. Less is known about how these challenges have affected nurses' capacity to meet their ethical responsibilities and what has helped to sustain their efforts to continue to care. RESEARCH OBJECTIVES: 1) To explore nurses' experiences of striving to fulfill their ethical responsibilities of care during the COVID-19 pandemic and 2) to explore what has fostered nurses' capacity to fulfill these responsibilities. RESEARCH DESIGN: A generic qualitative approach was used incorporating concepts coming from fundamental features of care. PARTICIPANTS: Twenty-four Canadian Registered Nurses from a variety of practice settings were interviewed. ETHICAL CONSIDERATIONS: After receiving ethics approval, signed informed consent was obtained before participants were interviewed. FINDINGS: Four themes were identified. 1) Challenges providing good care in response to sudden changes in practice. 2) Tensions in juggling the responsibility to prevent COVID-19 infections with other competing moral responsibilities. 3) Supports to foster nurses' capacity to meet their caring responsibilities. 4) The preservation of nurses' moral identity through expressions of gratitude and health improvement. DISCUSSION: Infection control measures and priorities set in response to the pandemic made at distant population and organizational levels impacted nurses who continued to try to meet the ideals of care in close proximity to patients and their families. Despite the challenges that nurses encountered, the care they received themselves enabled them to continue to care for others. Nurses benefited most from the moral communities they had with their colleagues and occasionally nurse leaders, especially when they were supported in a face-to-face manner.Conclusion: Moral community can only be sustained if nurses are afforded the working conditions that make it possible for them to support each other.
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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 | 0.019 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.020 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".