Knowledge, Attitudes, and Practice Toward Isolation Precautions Amongst Nurses and Auxiliary Nurses in Nemazee Hospital, Shiraz, Iran
Bibliographic record
Abstract
Background: Understanding the factors influencing nurses’ compliance with infection prevention strategies can assist in reducing occupational infections. Objectives: We surveyed nurses and auxiliary nurses in Shiraz, Iran, to evaluate their knowledge, attitudes, and practice (KAP) towards isolation precautions (IP). Methods: A cross-sectional study was conducted in a teaching hospital in Shiraz, Iran, in 2019. A five-part self-administered questionnaire was used, addressing demographics and infection prevention knowledge; nine items on KAP towards standard precautions, five items on droplet precautions, six items about airborne precautions, and eight items about contact precautions. The independent sample t-test and Pearson correlation were performed. Results: The mean score of practice was lower than that of knowledge and attitude in all IP domains. Droplet precautions acquired lower KAP scores than other domains. There were significant positive correlations between KAP scores in all IP domains in nurses (P < 0.001) and auxiliary nurses, except for the correlation between knowledge and practice in terms of standard precautions (P = 0.099). In nurses, age significantly correlated with knowledge towards airborne precautions (P < 0.001) and with attitude regarding droplet precautions (P = 0.003). Nurses had significantly higher scores regarding knowledge (P = 0.037) and attitude (P = 0.009) towards standard precautions than auxiliary nurses. The persons who had previous training sessions presented a higher score of the practice dimension for droplet (P = 0.001), airborne (P = 0.011), and contact (P = 0.004) precautions. Conclusions: This study revealed a gap in Nemazee hospital nurses’ KAP towards IPs. Those responsible for infection prevention and control programs in Shiraz University of Medical Sciences must address this poor practice of nurses towards patient safety.
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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 | 0.001 | 0.011 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".