Organizational Traits, Care Processes, and Burnout Among Chronic Hemodialysis Nurses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In light of evidence linking registered nurse (RN) staffing levels to patient outcomes in chronic hemodialysis facilities, U.S. government regulations have set minimum RN staffing requirements during dialysis. Consequently, facility administrators are focused on decreasing nurse attrition in this crucial practice setting. This study used a cross-sectional, correlational design to investigate the effects of workload, practice environment, and care processes on burnout among nurses in U.S. chronic hemodialysis centers and to determine the association between burnout and nurses' intentions to leave their jobs. Findings indicate that predictors were associated with an increased likelihood of nurse burnout and that nurses experiencing burnout were more likely to be planning to leave their jobs. Findings have important implications for retention of nurses, enhancement of patient safety, and adherence to new federal staffing requirements in chronic hemodialysis units.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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