The CaregiverVoice Survey: A Pilot Study Surveying Bereaved Caregivers To Measure the Caregiver and Patient Experience at End of Life
Bibliographic record
Abstract
OBJECTIVE: To integrate patient and caregiver feedback into end-of-life (EOL) care improvement, we tested the feasibility of a standardized, common instrument to measure care experiences across multiple settings in the last three months of life. METHODS: We developed and tested a survey, called the CaregiverVoice survey, which combined two validated questionnaires, the FAMCARE-2 and VOICES-SF. A retrospective, observational design was used to survey bereaved caregivers of decedents who had received homecare services in Ontario, Canada. RESULTS: In total, 330 surveys were completed (overall response rate of 13%, regional rates ranged from 4% to 83%). There was less than 5% missing data. Most patients received care from multiple settings in the last three months of life, including 60% for which a hospital stay was reported. The overall mean of the 19 FAMCARE-2 items was 1.7 (SD 0.7), with 72% of ratings as 1 very satisfied to 2 satisfied. On VOICES-SF items, 6% of respondents rated "all end-of-life services" as fair or poor, 24% as good, and 70% as excellent or outstanding, with variation depending on care site rated. 13% of caregivers reported that pain management was fair or poor in the last week of life. CONCLUSIONS: This pilot study provides preliminary evidence that it is feasible to capture the patient and caregiver experience at EOL using a comprehensive survey, though survey distribution method greatly affected response rates. The majority of responses rated care as excellent or very good, although several specific areas for improvement were identified.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".