Practitioners’ perceptions of acceptability of a question prompt list about palliative care for advance care planning with people living with dementia and their family caregivers: a mixed-methods evaluation study
Bibliographic record
Abstract
OBJECTIVES: In oncology and palliative care, patient question prompt lists (QPLs) with sample questions for patient and family increased patients' involvement in decision-making and improved outcomes if physicians actively endorsed asking questions. Therefore, we aim to evaluate practitioners' perceptions of acceptability and possible use of a QPL about palliative and end-of-life care in dementia. DESIGN: Mixed-methods evaluation study of a QPL developed with family caregivers and experts comprising a survey and interviews with practitioners. SETTING: Two academic medical training centres for primary and long-term care in the Netherlands. PARTICIPANTS: Practitioners (n=66; 73% woman; mean of 21 (SD 11) years of experience) who were mostly general practitioners and elderly care physicians. OUTCOMES: The main survey outcome was acceptability measured with a 15-75 acceptability scale with ≥45 meaning 'acceptable'. RESULTS: The survey response rate was 21% (66 of 320 participated). The QPL was regarded as acceptable (mean 51, SD 10) but 64% felt it was too long. Thirty-five per cent would want training to be able to answer the questions. Those who felt unable to answer (31%) found the QPL less acceptable (mean 46 vs 54 for others; p=0.015). We identified three themes from nine interviews: (1) enhancing conversations through discussing difficult topics, (2) proactively engaging in end-of-life conversations and (3) possible implementation. CONCLUSION: Acceptability of the QPL was adequate, but physicians feeling confident to be able to address questions about end-of-life care is crucial when implementing it in practice, and may require training. To facilitate discussions of advance care planning and palliative care, families and persons with dementia should also be empowered to access the QPL themselves.
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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 | 0.109 | 0.117 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".