The Relationship Between Quality of Life With Marital Satisfaction in Nurses in Social Security Hospital in Zahedan
Bibliographic record
Abstract
BACKGROUND: Marital satisfaction is one of the most important determinative factors of healthy function in family and can be affected by some factors. AIM: This study was conducted aimed to determine the relationship between quality of life and marital satisfaction in nurses in Social Security hospital in Zahedan. METHOD: In this descriptive and correlational study, the population was the all of the nurses in various wards in Social Security hospital in Zahedan. The sample size was 103 and data collection was done through quality of life questionnaire (War and Sherborn) and Enrich Marital Satisfaction Scale. Data analysis was done through SPSS15 and using pearsons' correlation coefficient and stepwise regression. RESULTS: The aspects of physical functioning, role limitations due to physical health problems, role limitation due to emotional problems had a significant positive correlation and the bodily pain had a significant reverse correlation with aspects of marital satisfaction. The aspects of role limitations due to physical health problems and bodily pain were predictors of marital satisfaction. CONCLUSION: The results of study demonstrated the importance of pay attention to family issues and marital satisfaction and in this regard, the promotion of all aspects of quality of life is essential.
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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 | 0.000 |
| 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) | 0.001 | 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".