Shared Treatment Decision Making: What Does It Mean to Physicians?
Bibliographic record
Abstract
PURPOSE: Physicians are urged to practice shared treatment decision making (STDM), yet this concept is poorly understood. We developed a conceptual framework describing essential characteristics of a shared approach. This study assessed the degree of congruence in the meanings of STDM as described in the framework and as perceived by practicing physicians. METHODS: A cross-sectional survey questionnaire was mailed to eligible Ontario medical and radiation oncologists and surgeons treating women with early-stage breast cancer. Open-ended and structured questions elicited physicians' perceptions of shared decision making. RESULTS: Most study physicians spontaneously described STDM using characteristics identified in the framework as essential to this concept. When presented with clinical examples in which the decision-making roles of physicians and patients were systematically varied, study physicians overwhelmingly identified example 4 as illustrating a shared approach. This example was deliberately constructed to depict STDM as defined in the framework. In addition, more than 85.0% of physicians identified as important to STDM specific patient and physician roles derived from the framework. These included the following: the physician gives information to the patient on treatment benefits and risks; the patient gives information to the physician about her values; the patient and physician discuss treatment options; both agree on the treatment to implement. CONCLUSION: Substantial congruence was found between the meaning of STDM as described in the framework and as perceived by study physicians. This supports use of the framework as a conceptual tool to guide research, compare different treatment decision-making approaches, clarify the meaning of STDM, and enhance its translation into practice.
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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 | 0.039 | 0.123 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.026 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.007 |
| 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".