Infection prevention and control curriculum in undergraduate nursing program: Internship nursing students’ perspectives
Bibliographic record
Abstract
Undergraduate nursing education plays a vital role in acquiring the necessary competency for patient safety. Infection prevention and control is a very critical topic for providing patient safety so, undergraduate and graduate nursing students should be competent in infection prevention and control. The aim of this study was to measure the undergraduate nursing program effectiveness in improving knowledge and practice of infection prevention and control of internship nursing students and to identify their learning needs. A descriptive research design was used. Students were selected using convenience sampling which included 400 internship nurses. Data was collected using a self-reported questionnaire. The results of the current study displayed that more than half (59.5%) of the intern nurses had poor knowledge and also 43.2% of them had poor practice. In addition, it was found that more than half of them reported that infection control program is neither irrelevant nor meaningful, and 48.5% of the students suggested that participation in infection prevention and control training is most important for the improvement of nursing program. This study concluded that infection prevention and control topics in undergraduate nursing education may be insufficient and need to be updated, as well as the need for reviewing the intended learning outcomes of nursing program to ensure the addition and implementation of infection control guidelines in all undergraduate in the last academic year of nursing program as well as internship. The students also are in need for continued training and education regarding guidelines of infection prevention and control practice.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".