Impact of specialty on attitudes of Australian medical practitioners to end‐of‐life decisions
Bibliographic record
Abstract
OBJECTIVE: To compare attitudes and practices of Australian medical practitioners, by specialty, to a range of medical decisions at the end of life. DESIGN, SETTING AND PARTICIPANTS: As part of an international study, in 2003, a structured questionnaire was mailed to 2964 medical practitioners drawn from membership registers of Australian and Australasian professional colleges. Data from 1478 questionnaires were statistically analysed using validated instruments. MAIN OUTCOME MEASURES: Practitioners' willingness to comply with requests from patients and/or their relatives for symptom relief which might also hasten death; provision of terminal sedation and euthanasia, or willingness to provide these on their own initiative. RESULTS: Respondents reported being much more willing to comply with a patient's request for increasing symptom relief, even at risk of hastening death, than for terminal sedation. Over a quarter of respondents would provide terminal sedation to competent patients on their own initiative. A small number of respondents would intentionally hasten death. There were significant differences by specialty for all three actions. Oncologists, palliative care physicians and geriatricians were least likely to actively hasten death, and more likely to act unilaterally to relieve symptoms as a medical necessity. CONCLUSIONS: Perceptions about the causation of death and aspects of medical culture appear to influence physicians' attitudes towards medical decisions at the end of life. Our findings have implications for medical education, interprofessional communication and discussion between the medical profession and the community.
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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 | 0.007 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".