Quality of life and mental health in caregivers of outpatients with advanced cancer
Bibliographic record
Abstract
OBJECTIVE: This study evaluates the quality of life (QOL) and mental health (MH) of caregivers of patients with advanced cancer who are receiving ambulatory oncology care and associations with patient, caregiver and care-related characteristics. METHODS: Patients with advanced gastrointestinal, genitourinary, breast, lung or gynaecologic cancer, and their caregivers, were recruited from 24 medical oncology clinics for a cluster-randomized trial of early palliative care. Caregivers completed the Caregiver QOL--Cancer scale and the Medical Outcomes Study Short Form, version 2, and a questionnaire including care-related factors such as hours/day providing care and change in work situation. Patients completed a demographic questionnaire and measures of their QOL and symptom severity. Associations of these factors with caregiver QOL and MH were examined using linear regression analyses. RESULTS: Of the 191 caregivers, 84% were spouses/partners, 90% cohabited with the patient, half were working and 25% had a change in work situation since the patient's diagnosis. On multiple regression analysis, better caregiver QOL was associated with better caregiver MH and patient physical well-being and with not providing care for other dependents. Worse caregiver MH was associated with female caregiver sex, worse patient emotional well-being, more hours spent caregiving and change in the caregiver's work situation. CONCLUSIONS: Caregivers of ambulatory patients with advanced cancer may have compromised QOL and MH associated with worse patient physical and emotional well-being and with simultaneously caring for others and working outside the home. Early palliative care interventions directed at patient symptoms and caregiver support may improve QOL in this population.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".