Knowledge and Application of Nursing Ethical Principles by Nurses at an Intermediate Hospital, Namibia
Bibliographic record
Abstract
BACKGROUND: Nurses are to possess the knowledge and dutifully apply nursing ethical principles of respect for person, beneficence, non-maleficence and justice in caring for clients. Incidents that portray poor knowledge and application of nursing ethical principles have been previously reported at health facilities in Namibia. AIM: To assess the knowledge and application of ethical principles of nursing by nurses in rendering care to patients at Onandjokwe Intermediate Hospital, Oshikoto region in Namibia. METHODS: A Cross-sectional descriptive, and analytical methodology was applied to describe the knowledge and application of nursing ethical principles by nurses, among a study population of 257 nurses, of which 107 were registered nurses and 150 were enrolled nurses- a subcategory of qualified nurses and out of which 37 declined to participate in the study. The data were collected from the remaining all population sample of 220 all nurses. Descriptive statistics on the respondents’ knowledge and applications of ethical principles, and the relationship of the respondents’ demographic characteristics as independent variables and the knowledge and applications of ethical principles as dependent variables were analyzed. RESULTS: The findings revealed poor knowledge and poor application of ethical principle of respect for person or autonomy (42%; 27,9%), non-maleficence (45.4%; 54.8%), beneficence (48.8%; 38.8%) and justice (40.5%; 43.4%) among the respondents. A significance association was found between good knowledge of non-maleficence and being a registered nurse with p-value =0.01, as well as of good knowledge and working experience of five years and more with a p=0.01 and p=0.02 respectively. Male nurses were also more knowledgeable about justice (p-value=0.03) than the female counterparts. CONCLUSION: The study revealed poor knowledge and poor application of all four ethical principles among the respondents.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".