Assessment of Nurses' Exposure to Chronic Diseases in Thi-Qar Governorate Hospitals
Bibliographic record
Abstract

 
 
 
 
 Objective: To assess nurses' exposure to hospitals chronic diseases hazards in Thi-Qar governorate, and to identify the association between nurses' socio-demographic characteristics of age, sex, marital status, place of work, the experience and educational attainment and their exposure to the hazards of chronic diseases. Methodology: A purposive "non-probability" sample of (433) nurses who were selected from four public hospitals in Thi-qar governorate for the period from November 4th 2013 to June 8th of 2014. Results: The study results indicated that that the vast majority of participants have mild chronic diseases and health problems (86.8%), nurses' age and years of working in nursing negatively correlate with occurrence of chronic disease, more than half of them are within 20-29 years-old, less than half of them have ≤ 5 years of working in nursing (45%), more than quarter of them work in emergency room, and less than half of those who have mild chronic diseases are preparatory nursing schools graduate (44.7%). Recommendations: Initiating a training program; especially; for newly working nurses that aim to prevent the occurrence of chronic diseases, Increase public awareness and education for Nurses workers in hospitals through posters, seminars, and medi
 
 
 
 
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".