Knowledge, Attitude, and Performance of Nurses toward Hand Hygiene in Hospitals
Bibliographic record
Abstract
INTRODUCTION: The proper hand hygiene is one of the foremost techniques to reduce Nosocomial infections. The hand hygiene is deemed as the simplest method for control of Nosocomial infections if it is done properly it may prevent from a lot of costs and fatalities. Due to constant relationship with patients, nurses play paramount role in proper execution of hand hygiene among clinical personnel. The current study was carried out in order to analyze knowledge, attitude, and performance of nurses regarding hand hygiene. MATERIALS & METHODOLOGY: A cross-sectional study was conducted on 200 (of 240) nurses from three hospitals in Kerman city at east of Iran in 2015. The standardized questionnaire was the tool for data collection. These data entered in SPSS (V.22). The frequency and percentage of frequency in descriptive statistics was employed for data analysis. The confidence interval was considered as 95%. RESULTS: The results showed that the majority of participants were male173 (86.5%), had BA degree 161 (80.5%) and were married 155 (70.5%). Most of nurses 77 (38.5%) had working experience (5-10years). The majority of nurses had good knowledge 149 (74.5%), positive attitude 141 (70.5%) and good performance 175 (87.5%). DISCUSSION & CONCLUSION: The nurses are good level in terms of knowledge, attitude, and performance but improvement of their knowledge and knowledge seems to be more necessary by holding educational classes and courses in cases where they have less knowledge.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".