Hand Hygiene Training and Its Impact on the Knowledge of Undergraduate Nursing Students in Kosovo
Bibliographic record
Abstract
BACKGROUND: Hand hygiene (HH) performing is a must in health care settings because it affects the human lives. Health Care Workers (HCW) must be aware and be trained continuously as regards hand hygiene.AIM: The aim of this article was to evaluate and compare the knowledge before and after an educational training of undergraduate nursing students at an educational institution in Pristine, Kosovo.METHODS: A pre- post survey was conducted in February 2016 at an educational institution in Pristine, Kosovo. The World Health Organization (WHO) questionnaire for hand hygiene knowledge of Health Care Workers (HCW) was used to collect the data.RESULTS: From a total of 100 students, only 13 (13 %) were men and 87 (87%) were women. Their ages ranged between 18-23 years old. Only 55 (55 %) had poor knowledge level, 42 (42%) had moderate knowledge level and only 3 (3%) had good knowledge about HH practices before the training and after the training only 1 (1%) participant was found with poor knowledge, 61 (61%) moderate knowledge and 38 (38 %) good knowledge. The training had a significant impact on the acquisition of HH’ knowledge. This was shown by the significant difference between the total points before and after the training (p <0.001).CONCLUCION: The training should be done consistently and be part of the nursing school curriculum, maintaining a satisfactory level of knowledge about hand hygiene as these students in a near future will face with Hand Hygiene (HH) issues in their daily clinical work.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".