Correlation between coping style and quality of life among hemodialysis patients from a low‐income area in Brazil
Bibliographic record
Abstract
Quality of life (QOL) is an important outcome among end-stage renal disease patients and can be associated with modifiable behaviors. We analyzed the correlation between coping style and QOL among hemodialysis patients. We studied 166 end-stage renal disease patients undergoing hemodialysis. They were older than 18 years, under hemodialysis for at least 3 months, and had never received a transplant. Quality of life was assessed by SF-36 and coping style was scored by the Jalowiec Coping Scale. Emotion-oriented coping and problem-oriented coping scores were compared according to sex, comorbidity, and socioeconomic status by the Mann-Whitney test. Correlations between QOL and 2 coping styles (emotion-oriented coping and problem-oriented coping) were adjusted for age, time on dialysis, hemoglobin, creatinine, albumin, calcium-phosphorus product, and Kt/V by backward stepwise linear regression. There was no difference between coping scores according to sex, comorbidity, and socioeconomic status. Emotion-oriented coping was independently and negatively associated with 4 QOL dimensions: physical functioning, role-physical, role-emotional, and mental health. Our results indicate that patients with high emotion-oriented coping scores should be seen at risk for poor QOL. Patient education in coping skills may be used to change the risk of poor QOL.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".