THE RELATIONSHIP BETWEEN WORK EXPERIENCE WITH SELF-EFFICIANCY IN CONDUCTING CPR ACTION AT CIBINONG HOSPITAL, BOGOR
Bibliographic record
Abstract
Background: Cardio Pulmonary Resusitation (CPR) is a set of interventions aimed at restoring and maintaining vital organs for the victims of cardiac arrest and stopping breathing. According to Depkas, cardiovascular disease is the number one cause of death, 39% of all deaths in the world where according to WHO 60% of which is ischemic heart disease. In Indonesia alone has not obtained a clear data about the number of prevalence of cardiac arrest event but estimated about 10,000 people per year who have cardiac arrest. Objective: To know the relation of long experience of nurse work with self efficacy in doing CPR action at Cibinong Hospital of Bogor District Method: Correlational descriptive research design with cross sectional approach. Sampling technique total sampling. This research was conducted at Cibinong Hospital of Bogor District of 2018 in April with a sample of 30 nurses. The instruments used are 1 open question on independent variable and GSE (General Self Efficacy) questionnaire on dependent variable. While the technique of data analysis using univariate and bivariate analysis with cramer statsitic test. Result : From 30 respondents, as many as 20 respondents (66,7%) have log worked > 3 years old category and 17 respondents (56,7%) have high self efficacy. In the cramer statistical test the p value 0,037 which means Ha is accepted and Ho is rejected. And the calculation of the odds ratio obtained an OR value of 5,444. Shows that the length of time of working for the old category > 3 years has a high self efficacy potential 5 times greater than the length of work for the new category ≤ 3 years. Conclusion:There is correlation between long working nurse and self efficacy in performing the act of cpr at Cibinong Hospital of Bogor District.
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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 | 0.004 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".