Historical Perspectives on the Shared Decision Making Centered Medicine
Bibliographic record
Abstract
Shared Decision Making (SDM) is a medical decision-making approach in which healthcare providers and patients collaboratively determine the best treatment options by integrating medical evidence with patients’ values and preferences through a cooperative approach. This review aimed to examine the historical background and conceptual development of SDM to provide foundational knowledge for healthcare professionals who are new to SDM. First, the historical background of SDM emergence was reviewed in the series of the changes brought to the medical field in the United States since 1960s. This review examines the key articles that introduced and shaped the SDM concept from its initial emergence to its concrete development. The concept of SDM was first introduced as “sharing of decision-making” in 1972, and the term “shared decision-making” emerged in the 1982 U.S. Presidential Commission report. Through research from the late 1990s to early 2000s, core components were established, and practical implementation models were developed in the 2010s. Additionally, this review explores patient decision aids that have been developed for SDM implementation, including their standardization through the Ottawa Decision Support Framework and International Patient Decision Aid Standards. SDM is currently recognized as an essential component of patient-centered care, and there is a need for expanding understanding and application in domestic healthcare settings.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.024 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".