Peaceful End of Life Theory: A Critical Analysis of Its Use to Improve Nursing Practice
Bibliographic record
Abstract
Background: Provision of empathetic palliative care in agreement with patient's favorites is an indispensable attitude of healthcare providers. A Peaceful End of Life Theory was designed by Ruland and Moore (1998), to provide theoretical framework for nurses who care for patients at end stage of their life. Methods: Chinn and Kramer theory analysis guideline was used to analyse this theory to suggest its improvement. Results: Five major concepts and sub-concepts are identified. This theory informs the nursing profession on the relieving interventions at the end of life. It provides a guidance to supportively manage terminally ill patients in collaboration with their families. Conclusion: This theory is important to guide nursing practice, research, and education. However, there is a lack of an instrument to measure the desired outcomes, some subconcepts do not cleary specify the nursing interventions, and it lacks the spiritual comfort to the terminally ill patients who believe in eternal life.
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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 | 0.085 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.015 | 0.009 |
| Science and technology studies | 0.009 | 0.029 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| 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".