Factors Related To Nurses' Hospital Management And Work Engagement In The Radiology Department
Why this work is in the frame
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Bibliographic record
Abstract
Background: Work engagement is critical for nurse performance and well-being, particularly in specialized areas such as radiology, where occupational hazards like radiation exposure and high-stress environments are prevalent. Despite the increasing demand for radiological nursing care, many nurses express reluctance to work in radiology due to health concerns and limited support systems. Methods: This study was conducted among nurses working in radiology departments of cancer care hospitals . Data were collected using a demographic questionnaire, the Utrecht Work Engagement Scale (UWES), and a survey assessing perceptions of radiation safety. Descriptive and multiple regression analyses were performed to identify factors influencing work engagement. Results: Out of 200 participants, the mean UWES score was 54.3 (SD = 18.4), reflecting moderate work engagement. Absorption scored slightly higher than vigor and dedication. Key predictors of engagement included nurses’ preference for radiology assignments and the availability of radiation exposure consultation services. While nurses reported confidence in workplace safety measures, gaps in consultation services and education about long-term risks were noted. Demographic factors, such as age and professional position, also played a role in engagement levels. Conclusion: Work engagement among radiology nurses is influenced by a complex interplay of individual preferences and organizational factors. Enhancing consultation services, providing targeted training, and implementing specialized support programs are essential strategies for fostering engagement in high-stress environments. Further research is needed to develop tailored interventions to address these challenges and improve outcomes in radiology nursing.
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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 it