Factors influencing fatigue in Chinese 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
Factors predicting fatigue in Chinese nurses were examined in a descriptive, correlational study. The participants were 581 nurses working in general hospitals in Chengdu City, China. The study instruments included the Occupational Fatigue Exhaustion Recovery Scale, the Job Content Questionnaire, the Exposure to Hazards in Hospital Work Environments Scale, the Pittsburgh Sleep Quality Index, the Job Dissatisfaction Scale, the Beck Anxiety Inventory, and the Beck Depression Inventory. The data were analyzed by using descriptive statistics, Pearson's correlation, F statistics, and multiple regression. The findings revealed that 61.7% of the variance in chronic fatigue and 54.9% of the variance in acute fatigue were explained by the independent variables. Intershift recovery was the most important variable in the explanation of acute fatigue, while acute fatigue was the most important variable in the explanation of chronic fatigue. Different intervention strategies should be implemented regarding the different influencing factors of acute and chronic fatigue.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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