Toward Shared Decision Making: Using the OPTION Scale to Analyze Resident–Patient Consultations in Family Medicine
Bibliographic record
Abstract
PURPOSE: Do residents in family medicine practice share decision making with patients during consultations? This study used a validated scale to score family medicine residents' shared decision-making (SDM) skills in primary care consultations and to determine whether residents' demographic characteristics were correlated with their scores. METHOD: Between January 2009 and April 2010 at two Canadian academic health centers, the authors recruited unique dyads of patients consulting in primary care and family medicine residents. They recorded, transcribed, and assessed consultations using the Observing Patient Involvement in Decision Making (OPTION) scale, which measures 12 SDM-specific behaviors on a scale of 0% to 100% (high score = better SDM). They calculated descriptive and inferential statistics for the scores. RESULTS: From 212 eligible residents, the authors recruited 152 unique patient-resident dyads (participation rate = 75%): 68 dyads from 13 clinics in London, Ontario, and 84 from six family medicine units in Quebec City, Quebec. The mean global OPTION score was 24% ± 8%; the mean score for each of the 12 items ranged from 4% to 37%. Five of the 12 behaviors obtained a mean score below "a minimal attempt is made to exhibit the behavior" (i.e., <25%). There was a positive correlation between the score and the duration of the consultation (r = 0.24, P = .003), with longer consultations producing higher scores. CONCLUSIONS: Participating family medicine residents have not integrated SDM behaviors, which may also pertain to residencies elsewhere. Interventions are required to foster family medicine residents' practice of SDM.
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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 | 0.005 | 0.021 |
| 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 | 0.000 | 0.000 |
| 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 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".