Hubungan Tingkat Pengetahuan dan Sikap Perawat Tentang Infeksi Nosokomial (INOS) Dengan Perilaku Pencegahan INOS Di Ruang Bedah RSUD DR. Moewardi Surakarta
Bibliographic record
Abstract
Abstract: Knowledge, Attitudes, Behaviors, Inos, Nurse. Nosocomial infections (inos) is an infection acquired during patient care in hospitals, infection is not in pain at the time of hospital admission and the patient is not within an incubation period of infectious diseases. The study aims to determine the relationship between the level of knowledge and attitudes to the behavior of nurses regarding the prevention of inos in the operating room of RSUD Dr. Moewardi Surakarta. Design used in this study was descriptive correlational cross-sectional approach. Sampling was carried out with total non-probability sampling, sample size of 30 respondents. There is a relationship between the level of the nurse’s knowledge about preventive behaviors inos with a probalility value of Spearman’s Rank correlation test for p = 0,024 is smaller than the probability p = 0,05. There is no relationship between nurse attitudes about preventive behaviors inos with a probability value of Spearman's Rank correlation test for p = 0.759 greater than the probability p = 0.05. There is a relationship between the nurse's knowledge about preventive behavior with inos. There is no relationship between attitudes to the behavior of nurses regarding the prevention of inos.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".