Caregiver quality of life in advanced cancer: Qualitative results from a trial of early palliative care
Bibliographic record
Abstract
BACKGROUND: Early involvement of palliative care improves patient quality of life; however, quantitative studies have not yet demonstrated a similar effect for caregivers, for whom the construct of quality of life is less well developed. AIM: To conceptualise quality of life of caregivers from their own perspective and to explore differences in themes between those who did or did not receive an early palliative care intervention. DESIGN: Qualitative grounded theory study. SETTING: Tertiary comprehensive cancer centre. PARTICIPANTS: Following participation in a cluster-randomised trial of early palliative care, 23 caregivers (14 intervention and 9 control) of patients with advanced cancer participated in semi-structured interviews to discuss their quality of life. RESULTS: The core category was 'living in the patient's world'. Five related themes were 'burden of illness and caregiving', 'assuming the caregiver role', 'renegotiating relationships', 'confronting mortality' and 'maintaining resilience'. There was thematic consistency between trial arms, except for the last two themes, which had distinct differences. Participants in the intervention group engaged in open discussion about the end of life, balanced hope with realism and had increased confidence from a range of professional supports. Controls tended to engage in 'deliberate ignorance' about the future, felt uncertain about how they would cope and lacked knowledge of available supports. CONCLUSIONS: Caregiver quality of life is influenced profoundly by the interaction with the patient and should be measured with specific questionnaires that include content related to confronting mortality and professional supports. This would improve delineation of quality of life for caregivers and allow greater sensitivity to change. Registration: clinicaltrials.gov NCT01248624.
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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 | 0.034 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".