Couples facing advanced cancer: examination of an interdependent relational system
Bibliographic record
Abstract
BACKGROUND: The relational impact of advanced cancer on both patients and spouse caregivers has rarely been examined simultaneously. This study describes a framework for understanding distress in each partner as a consequence of psychosocial characteristics, burden of disease or of caregiving, and the distress of the other person. A model focusing on the protective value of social relatedness was tested to illustrate the interdependence of patients and spouses in their mutual adaptation to disease. METHODS: A total of 278 advanced cancer patients and their spouse caregivers completed measures of psychological distress (e.g., depression), physical burden from cancer (e.g., symptom count), caregiving burden (i.e., time and task demand), and social relatedness (i.e., social support and attachment security). Structural equation modeling was used to extract latent factors associated with these constructs and to examine their interrelationships. RESULTS: The model fit was adequate. Patient distress was related to disease burden (standardized path coefficient = 0.52) and patient social relatedness (-0.32). Caregiver distress was related to caregiving burden (0.21) and caregiver social relatedness (-0.51). Caregiving burden was related to patient disease burden (0.43) and caregiver social relatedness (-0.37). Reciprocal pathways between patient and caregiver distress indicated that caregiver distress was influenced by patient distress (0.30) but not vice versa (0.12). CONCLUSIONS: These findings support the view that patients and caregivers constitute an interdependent relational system and interventions in this setting should take into account both interactions between patients and caregivers and the nature of their social relatedness.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".