End-of-life discussions in practice: survey among Canadian radiation oncologists
Bibliographic record
Abstract
BACKGROUND: Early end-of-life (EOL) discussions improve patient satisfaction, quality of care, and the cost-effectiveness of care. However, some US studies show that radiation oncologists (ROs) are unlikely to discuss EOL issues until the patients develop significant symptoms or the families initiate the discussion. There have been no prior studies describing the patterns of EOL discussions among Canadian ROs. The objectives of this study were: (I) to describe the patterns of EOL discussions among Canadian ROs; (II) to identify the barriers to EOL conversation among Canadian ROs; (III) to assess the attitudes of Canadian ROs toward Medical Assistance in Dying (MAiD). METHODS: The 22-question online survey was distributed to the members of Canadian Association of Radiation Oncologists (CARO). Demographics, EOL discussion patterns, perception of EOL discussions, barriers, and the impact of MAiD were evaluated. RESULTS: Sixty ROs responded out of 326. Prognosis (57%) and goals of care (58%) were routinely discussed, while advanced directive (40%) and planned site of death (12%) were not. More than 90% felt that early EOL discussions with palliative patients were important. The amount of palliative discussion training was correlated with confidence in EOL discussion (P <0.01), perceived importance of RO role in EOL (P=0.006), and the frequency of planned site of death discussion (P=0.041). The most frequently identified barriers were lack of time, uncertainty about prognosis, and concern for patient disappointment. Many ROs provided MAiD information upon request or case-by-case, but only 3% provided the information routinely. CONCLUSIONS: Canadian ROs recognize the importance of EOL discussions, but they do not routinely incorporate advanced directive or site of death in their discussions. ROs with more palliative discussion training were more confident in EOL discussion and likely to engage in them earlier. Short structured training may improve the confidence and quality of EOL discussion. Time constraint is the number one barrier that may be alleviated by delegation of tasks and patient education tools. Discussion about MAiD is supported but not routine among Canadian ROs.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".