Is shared <scp>decision‐making</scp> to blame for the provision of <scp>ethically inappropriate</scp> treatment? Results of a multi‐site study exploring physician understanding of the “shared” model of decision making
Bibliographic record
Abstract
Support for the concept of respect for first-person informed consent and patient autonomy, including the negative right of patients to refuse unwanted interventions has grown, but does not generally include a positive right of patients to receive whatever treatment they request or demand without constraint. Despite this, health-care providers in both Canada and the United States are guilty of providing, in their own opinions, futile or probably futile treatments at the request of patients or their substitute decision-makers. The purpose of this study was to examine whether physicians' understanding of the shared model of medical decision-making - shared decision-making, (SDM) - may be among the reasons why some patients receive treatment understood as ethically inappropriate, including those deemed futile, treatments that are not medically indicated, or those that are not in the patient's best interests to receive. A secondary question asked to study participants was whether they believed their professional college allowed, or further, required them to use shared decision-making in their practice. The initial hypothesis of the researcher in this study was that SDM is not well understood by physicians, and that this lack of understanding, combined with other factors to be discussed in the full text, may result in patients receiving ethically-inappropriate treatment. Results suggest support for this hypothesis, and that SDM should be more closely examined if it is to be pursued as a method of decision making.
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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 | 0.043 | 0.166 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".