Ethical issues experienced by healthcare workers in nursing homes
Bibliographic record
Abstract
BACKGROUND: Ethical issues are increasingly being reported by care-providers; however, little is known about the nature of these issues within the nursing home. Ethical issues are unavoidable in healthcare and can result in opportunities for improving work and care conditions; however, they are also associated with detrimental outcomes including staff burnout and moral distress. OBJECTIVES: The purpose of this review was to identify prior research which focuses on ethical issues in the nursing home and to explore staffs' experiences of ethical issues. METHODS: Using a systematic approach based on Aveyard (2014), a literature review was conducted which focused on ethical and moral issues, nurses and nursing assistants, and the nursing home. FINDINGS: The most salient themes identified in the review included clashing ethical principles, issues related to communication, lack of resources and quality of care provision. The review also identified solutions for overcoming the ethical issues that were identified and revealed the definitional challenges that permeate this area of work. CONCLUSIONS: The review highlighted a need for improved ethics education for care-providers.
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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 | 0.021 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".