Bibliographic record
Abstract
AIMS AND OBJECTIVES: To study quality of life (QOL) and its important correlates among family caregivers of terminally ill patients receiving in-home hospice care. BACKGROUND: Caregiver QOL has been identified as a core outcome variable in studies of dying patients and their families, but few studies have assessed QOL among caregivers of patients with terminal illness, particularly those in hospice care. DESIGN: For this cross-sectional correlational study, 60 caregivers were recruited from two local in-home hospice programmes in the Midwestern United States. METHODS: Self-report data were provided by caregivers using the Caregiver Quality of Life Index - Cancer, Spiritual Well-Being Scale, American Pain Society Patient Outcomes Questionnaire, Eastern Cooperative Oncology Group Performance Status Rating and Medical Outcome Study Social Support Survey to measure their QOL, spirituality, health status and social support. RESULTS: Caregivers' educational status, physical health status, spirituality and qualitative and quantitative social support, as a set, explained 42% of the variance in their QOL. Caregivers with higher education, better physical health status, greater spirituality and more qualitative and quantitative social support, had a significantly better QOL. CONCLUSIONS: QOL for this sample of hospice caregivers was significantly predicted only by physical health status and spirituality, likely because of collinearity among the independent variables. Additional research is needed to explore the factors that sustain or promote caregivers' QOL over time. RELEVANCE TO CLINICAL PRACTICE: In the delivery of hospice services, the family caregiver is both a vital member of the health care team and a recipient of care. Health care providers should therefore pay more attention to the health status and spirituality of major caregivers, thus helping them maintain and improve 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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".