Nurses, physicians and patients’ knowledge and attitudes about nurse prescribing
Bibliographic record
Abstract
BACKGROUND: One of the roles that nurses have acquired in recent years is the role of prescribing. This study aimed to investigate the knowledge and attitudes of critical care nurses, physicians and patients about nurse prescribing. METHODS: A descriptive cross-sectional study with the participation of 152 nurses, 53 physicians and 75 patients was carried out. Participants were selected by stratified random sampling from the critical care units of six hospitals in Tabriz, Iran. Demographics and participants' knowledge and attitudes about nurse prescribing questionnaires were used to collect data. The collected data were analyzed using SPSS-22 software. RESULTS: The mean scores of total knowledge about nurse prescribing in nurses, patients and physicians' were 15.41 ± 1.85,16.45 ± 2.31, 14.74 ± 1.7 respectively (from a range of 10 -20), and the mean score of knowledge by physicians was significantly higher than others (P = 0.000) and they had more knowledge about nurse prescribing. The mean scores of the attitudes towards nurse prescribing in nurses, physicians and patients were 40.62 ± 3.68, 37.98 ± 5.92 and 39.38 ± 4.39 respectively (from a range of 10 -50). However, the total mean score of attitudes among nurses was significantly higher than others (P = 0.000) and nurses had more positive attitudes toward prescribing. CONCLUSION: The results showed that the participants have a good understanding and attitudes toward nurse prescribing. Nurse prescribing as a new duty and authority can be considered in providing more effective care by specialist nurses. The results of this study can also be used in the future planning of health policy for nurses to have the right to prescribe and ultimately improve the quality of patient care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".