Impact of the Ottawa Decision Support Framework on the Agreement and the Difference between Patients' and Physicians' Decisional Conflict
Bibliographic record
Abstract
BACKGROUND: The Ottawa Decision Support Framework (ODSF) provides a process that facilitates shared decision making. OBJECTIVE: To assess the impact of implementing the ODSF on the agreement and the difference between patients' and physicians' decisional conflict scores. DESIGN: In total, 120 physicians and 903 patients enrolled in this before-and-after study. Implementation of the ODSF was composed of an interactive workshop, feedback, and a reminder at the point of care. The Decisional Conflict Scale (DCS) was completed by physicians and patients after a clinical encounter. RESULTS: The intraclass correlation coefficient was-0.205 +/- 0.096 (95% confidence interval [CI]= - 0.224 to -0.186) before implementing the ODSF and- 0.013 +/- 0.114 (95% CI = - 0.036 to 0.009) after. At the patient level, the following factors were significantly associated with the difference between the patients' and physicians' DCS: unemployed (P = 0.023), implementing the ODSF (P = 0.008), high school degree (P = 0.04), male (P = 0.03), and unilateral role in decision making (P = 0.03). At the physician level, provincial committee (P = 0.001), national committee (P = 0.045), clinical site (P = 0.016), reluctance to share uncertainty (P = 0.023), and anxiety due to uncertainty (P = 0.017) were significantly associated with this outcome. CONCLUSION: After implementing the ODSF, there was less dissimilarity between patients' and physicians' DSC than expected by chance than before. Implementing the ODSF was also found to be associated with the difference between patients' and physicians' DSC. The physician level explained a significant amount of the variance in this outcome, thus emphasizing the importance of an intervention at this level.
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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 | 0.192 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".