Caregiver Burden in Distance Caregivers of Patients with Cancer
Bibliographic record
Abstract
Distance caregivers (DCGs), those who live more than an hour away from the care recipient, often play a significant role in patients' care. While much is known about the experience and outcomes of local family caregivers of cancer patients, little is known about the experience and outcomes of distance caregiving upon DCGs. The purpose of this study was to identify the relationships among stressors (patient cancer stage, anxiety, and depression), mediators (DCG emotional support and self-efficacy), and burden in DCGs' of patients with cancer. This study was a descriptive cross-sectional study and involved a secondary data analysis from a randomized clinical trial. The study sample consisted of 314 cancer patient-DCG dyads. The results of this study were: (1) 26.1% of DCGs reported elevated levels of burden; (2) significant negative relationships were found between mediators (DCG emotional support and self-efficacy) and DCG burden; and (3) significant positive relationships were found between patient anxiety, depression, and DCG burden. The prevalence of burden in DCGs, and its related factors, were similar to those of local caregivers of cancer patients, which suggests that interventions to reduce burden in local caregivers could be effective for DCGs as well.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".