Cancer-Related Debt and Mental-Health-Related Quality of Life among Rural Cancer Survivors: Do Family/Friend Informal Caregiver Networks Moderate the Relationship?
Bibliographic record
Abstract
Social connectedness generally buffers the effects of stressors on quality of life. Is this the case for cancer-related debt among rural cancer survivors? Drawing on a sample of 135 rural cancer survivors, we leverage family/friend informal caregiver network data to determine if informal cancer caregivers buffer or exacerbate the effect of cancer-related debt on mental-health-related quality of life (MHQOL). Using data from the Illinois Rural Cancer Assessment, a survey of cancer survivors in rural Illinois, we estimate the association between cancer-related debt and MHQOL and whether informal caregiver network size and characteristics moderate this association. Over a quarter of survivors (27%) reported cancer-related debt, and those who did reported worse MHQOL. However, this association only held for survivors who had an informal caregiver network. These findings supplement what is already known about the role of social connectedness in cancer survivors’ health outcomes. We offer possible explanations for these findings.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".