Neonate Pain Management: What do Nurses Really Know?
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to determine knowledge, attitude, and performance vis-à-vis pain management in neonates by nurses working in neonatal units in Bandar Abbas University hospitals. METHOD: This descriptive and analytical study was executed from March-August 2011 in the neonatal units and NICU in Bandar Abbas educational hospitals. A total of 50 nurses and nurse assistants working in the neonatal units participated in the study. The data collection tool was a structured questionnaire investigating knowledge (28 items), attitude (20 items) and practices (5 items). Data was analyzed using descriptive statistical tests (Frequency, Mean and Standard deviation tables) and inferential statistic (T-test, Variance analysis). RESULTS: The knowledge scores of participants had a mean value of 13.51 (48.2%) out of 28. The mean score of attitude was 54.22 out of 60 and the mean score for the nurses' level of practices was found to be 4.22 out of 10. There was a significant relationship between nurses' knowledge scores and the level of education, i.e. nurses with more education had more knowledge. CONCLUSION: Results showed that the nurses had poor performance regarding the assessment, measurement, and relief of pain. However, they showed positive attitudes towards pain control in neonates.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".