General practitioners and palliative care practices: a better knowledge of specific services is still needed
Bibliographic record
Abstract
Abstract Background France allows deep sedation for pain relief, but not for euthanasia. In anticipation of an increase in home-based palliative care, the role of general practitioners is central to the design of outpatient palliative care services. This study aimed to describe the knowledge, attitudes, and practices of general practitioners in mainland France regarding palliative and end of life care. Methods This was a national descriptive cross-sectional study within the Sentinelles network. Self-report questionnaires were distributed to general practitioners between November 2020 and November 2021. A descriptive analysis was carried out. Results Out of the 123 participating general practitioners, 84% had received academic training in palliative care (n = 104). While a significant majority (69%) expressed comfort in pain management, only a quarter (25%) declared that they were competent at indicating deep and continuous sedation for pain relief. Awareness of outpatient palliative care facilities close to their place of practice such as hospitalization at home was over 97% (n = 117/120). Awareness of hospital facilities, including identified palliative care beds on hospital wards and palliative care units, was lower (75% (n = 59/79) and 86% (n = 86/100), respectively). Conclusions Our results suggest that French general practitioners are reasonably aware of palliative care resources available. However, there is room for improvement, particularly in understanding hospital-based facilities. Furthermore, a quarter of the general practitioners expressed discomfort with deep and continuous sedation for pain relief, highlighting the need for increased training in this specific aspect of palliative and end of life care.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".