Assessment of Predictable Productivity of Nurses Working in Kerman University of Medical Sciences’ Teaching Hospitals via the Dimensions of Quality of Work Life
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Bibliographic record
Abstract
INTRODUCTION: Despite the existence of a large community of nurses, specific mechanisms have not been developed yet to consider their needs and the quality of their work life. Moreover, few studies have been conducted to analyze the nature of nursing, nursing places or nurses' quality of work life. In this regard, the present study aimed to assess predictable productivity of nurses working in Kerman University of Medical Sciences' teaching hospitals via the dimensions of Quality of Work Life. METHODOLOGY: The present descriptive-correlational study was conducted to assess predictable productivity of nurses via the dimensions of Quality of Work Life. The study's population consisted of all nurses working in different wards of teaching hospitals associated with Kerman University of Medical Sciences. Out of the whole population, 266 nurses were selected based on the simple random sampling method. To collect data, the questionnaires of 'Quality of Nursing Work Life' and 'Productivity' were used after confirming their reliability (test-retest) and content validity. Finally, the collected data were analyzed through the SPSS software (version 16). RESULTS: Although the quality of work life for nurses was average and their productivity was low but the results showed that quality of life is directly related to nurses' productivity. Quality of life and its dimensions are predictive factors in the in the nurses' productivity. CONCLUSIONS: It can conclude that by recognizing the nurses' quality of work life situation, it can realize this group productivity and their values to the efficiency of the health system. For the quality of working life improvement and increasing nurses' productivity more efforts are needed by authorities. The findings can be applied by managers of hospitals and nursing services along with head nurses to enhance the quality of health services and nursing profession in general.
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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 | 0.021 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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