Resilience, Self-Efficacy, and Psychological Burden in Palliative Care: A Cross-Sectional Observational Study
Bibliographic record
Abstract
Aims: This study explores the relationship between resilience and self-efficacy in palliative care patients and caregivers, focusing on gender differences in emotional expression and the impact of patient-caregiver dynamics on distress and coping. Methods: A cross-sectional study involved 160 palliative patients and 123 caregivers. Validated tools assessed resilience (Resilience Scale-14), self-efficacy (General Self-Efficacy Scale), distress (Integrated Palliative Care Outcome Scale), emotional expressivity (Toronto Alexithymia Scale), and caregiving burden (Caregiver Inventory). Regression and mediation analyses identified predictors of distress and burden. Results: Higher resilience correlated with lower patient distress ( p = .004) but increased caregiver burden ( p < .001). Resilience mediated the relationship between self-efficacy and burden. Male patients had more difficulty identifying emotions ( p < .001). The patient-caregiver relationship type did not significantly affect distress. Conclusions: While resilience is a protective factor for patients, it may unintentionally heighten the burden on caregivers. Gender-sensitive psychological interventions are needed to improve emotional processing and coping strategies.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".