Dyadic effects of perceived burden and psychological distress on quality of life among Chinese advanced cancer patients and their caregivers
Bibliographic record
Abstract
This study aims to explore the mediating role of psychological distress in the association between perceived burden and quality of life (QoL) in advanced cancer patient-caregiver dyads. 241 dyads in five tertiary hospitals in a province were investigated by using the Edmonton Symptom Assessment System, Zarit Burden Interview, the Patient Health Questionnaire-4, the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 15 Palliative scores, and the Short Form Health Survey 8. The actor-partner interdependence mediation model (APIMeM), which assesses both individual (actor) and interdependent (partner) effects within dyadic relationships, was employed to analyze how burden and psychological distress interact across dyad members. Analysis was conducted using Mplus v8.0. Regarding the actor effects, the mediating role of psychological distress between perceived burden and QoL was confirmed in advanced cancer patients (B = -0.223, p = 0.001) and their caregivers (B = -0.168, p < 0.001). Regarding the partner effects, there were no significant correlations between caregiver burden and patients' psychological distress (B = 0.015, p = 0.199), patients' QoL (B = 0.113, p = 0.278), or the indirect association of caregiver burden with patients' QoL through psychological distress (B = -0.034, p = 0.259). However, caregivers' psychological distress was positively correlated with patients' symptom burden and mediated the association between patients' symptom burden and caregivers' QoL (B = -0.090, p = 0.001). The study highlights the importance of taking a dyadic perspective in the context of advanced cancer. Dyadic interventions targeting their perceived burden and psychological distress may be beneficial to their 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".