Quality of life and religious-spiritual coping in palliative cancer care patients
Bibliographic record
Abstract
Objectives: to compare the quality of life and religious-spiritual coping of palliative cancer care patients with a group of healthy participants; assess whether the perceived quality of life is associated with the religious-spiritual coping strategies; identify the clinical and sociodemographic variables related to quality of life and religious-spiritual coping. Method: cross-sectional study involving 96 palliative outpatient care patient at a public hospital in the interior of the state of São Paulo and 96 healthy volunteers, using a sociodemographic questionnaire, the McGill Quality of Life Questionnaire and the Brief Religious-Spiritual Coping scale. Results: 192 participants were interviewed who presented good quality of life and high use of Religious-Spiritual Coping. Greater use of negative Religious-Spiritual Coping was found in Group A, as well as lesser physical and psychological wellbeing and quality of life. An association was observed between quality of life scores and Religious-Spiritual Coping (p<0.01) in both groups. Male sex, Catholic religion and the Brief Religious-Spiritual Coping score independently influenced the quality of life scores (p<0.01). Conclusion: both groups presented high quality of life and Religious-Spiritual Coping scores. Male participants who were active Catholics with higher Religious-Spiritual Coping scores presented a better perceived quality of life, suggesting that this coping strategy can be stimulated in palliative care patients.
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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 | 0.003 |
| 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) | 0.002 | 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".