Healthcare Workers at Dialysis Centers and Students Studying in Dialysis Departments: Behavioural Assessment
Bibliographic record
Abstract
Purpose The purpose of this study was to determine the behaviours of students studying dialysis and health personnel working at dialysis centers and the influencing factors. Methods Students studying dialysis department at Turgut Özal University (n=70) and healthcare personnel working at eight Dialysis Centers located in the center of Ankara (n=83) were recruited. Data was collected from personal information forms and Healthy Life Style Behaviours (HLSB)-II scale. Data were analysed Student's t test, Man Whitney U test, Kruskal Wallis Test and Pearson correlation analysis;p<0.05 or p<0.01 were considered statistically significant. Findings The majority (n=52; 74.3%) of the students participating the research were female, with an average age of 22.09±2.17 years and 55.7% (n=39) were in 2nd year. Similarly, the majority of the healthcare personnel were female (n=73; 88%) with an average of age of 35.37±8.29 years and 30.1% had a Bachelor's degree. Total HLSB II point of the students' was 128.06±22.00 and health responsibility, one of scale sub-scores, was significantly higher in female than male students (p<0.05), and there was no statistically significant difference between smoking, age and scale sub-dimensions (p>0.05). Total HLSB II point of the healthcare personnel was 115.61±14.26, and physical activity, one of scale sub-scores, was significantly lower in females compared to males (p<0.01). Conclusion It was determined that total HLSB II point of the students is medium and significantly higher compared with healthcare personnel. Continuing education for protecting and improving health should be provided for healthcare personnel.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".