Factors associated with shared decision making among primary care physicians: Findings from a multicentre cross‐sectional study
Bibliographic record
Abstract
BACKGROUND: Despite growing recognition that shared decision making (SDM) is central for patient-centred primary care, adoption by physicians remains limited in routine practice. OBJECTIVE: To examine the characteristics of physicians, patients and consultations associated with primary care physicians' SDM behaviours during routine care. METHODS: A multicentre cross-sectional survey study was conducted with 114 unique patient-physician dyads recruited from 17 primary care clinics in Quebec and Ontario, Canada. Physicians' SDM behaviours were assessed with the 12-item OPTION scale scored by third observers using audio-recordings of consultations. Independent variables included 21 physician, patient and consultation characteristics. We assessed factors associated with OPTION scores using multivariate linear regression models. RESULTS: On the OPTION scale, where higher scores indicated greater SDM behaviours, physicians earned an overall mean score of 25.7±9.8 of 100. In the final adjusted regression model, higher OPTION scores were associated with physicians' social participation (involvement in one committee β=5.75, P=.04; involvement in two or more committees β=7.74, P=.01), patients' status as employed (β=6.48, P=.02), clinically significant decisional conflict in patients (β=7.15, P=.002) and a longer duration of consultations (β=0.23, P=.002). CONCLUSION: Physicians' social participation, patients' employment status and decisional conflict and the duration of consultations were associated with primary care physicians' SDM behaviours in routine care. These factors should be considered when designing strategies to implement SDM and promote more patient-centred care in primary care.
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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 | 0.002 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".