The Effect of an Education-Based Intervention on Self-Reported Awareness and Practice of Iranian Nurses in Observing Patients’ Rights
Bibliographic record
Abstract
BACKGROUND: For patients' rights to be observed, first patients and health care providers should be aware of these rights. Nurses' lack of awareness of these rights leads to their inability to recognize patients' legal and ethical issues, and reduces the quality of provided services. This study was conducted to determine the effect of an education-based intervention on self-reported awareness and practice of nurses in observing patients' rights. METHODS: In this quasi-experimental study, awareness and practice of 90 nurses on Patient's Bill of Rights were examined in case and control groups, before, 2 and 4 weeks after an educational intervention program on. Participants were selected from teaching hospitals of Mazandaran University of Medical Sciences, Iran. Data was gathered using the valid and reliable 21-item questionnaire in a 3-point Likert scale during a 5-month period from October 2013 to March 2014. For data analysis, descriptive statistical methods, paired t-test, and repeated measure analysis of variance at significant level P<0.05 were used. RESULTS: Participants' mean age and work experience were found 37.1 ± 5.71 years and 11.76 ± 5.99 years respectively. Mean scores of nurses' awareness and practice before intervention were 15.12 ± 2.19 and 9.13 ± 2.36, accordingly. Repeated measure analysis of variance test showed a significant difference in awareness and practice of nurses before and after intervention (P<0.001). CONCLUSION: Enhancing nurses' awareness on Patient's Bill of Rights through revision of educational curriculum in nursing schools, together with considering appropriate relevant content in continuous education programs in health systems can lead to improved quality of nursing care services.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".