Dyadic coping and its association with emotional functioning in couples confronted with advanced cancer: Results of the multicenter observational eQuiPe study
Bibliographic record
Abstract
OBJECTIVE: How patients and their partners cope with advanced cancer as a couple, may impact their emotional functioning (EF). The aim of this study was to assess dyadic coping (DC) of couples confronted with advanced cancer and its association with EF. METHODS: Actor-partner interdependence models were used to analyze baseline data of 566 couples facing advanced cancer participating in an observational study on quality of care and life. Measures included the DC Inventory and the European Organization for Research and Treatment of Cancer quality of life questionnaire (EOQLQ-C30). RESULTS: Negative DC (mean 86-88) was most often used and common DC (both mean 66) was least often used. We found small to moderate interdependence (r = 0.27-0.56) between patients' and partners' DC perceptions. Compared to partners, patients were more satisfied with their DC (p < 0.001). Partners' satisfaction with DC was positively associated with their own (B = 0.40, p < 0.001) and patients' (B = 0.23, p = 0.04) EF. We found positive actor (patients B = 0.37 B = 0.13, p = 0.04) and partner (both B = 0.17, p < 0.05) associations for negative DC in patients and partners. Partners' supportive DC was negatively associated with patients (B = -0.31, p = 0.03) and partners' EF (B = -0.34, p = 0.003). CONCLUSIONS: This study highlight the importance of DC (especially from the partners' perspective) for EF in advanced cancer but also identifies differences in the experience of patients and their partners. Future research is needed to understand the mechanisms of such relations and the common and unique support options that may facilitate adjustment in patients with advanced cancer and their partners.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".