Shared Treatment Decision Making: What Does It Mean to Physicians?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it