Training family physicians in shared decision making for the use of antibiotics for acute respiratory infections: a pilot clustered randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Experts estimate that the prevalence of antibiotics use exceeds the prevalence of bacterial acute respiratory infections (ARIs). OBJECTIVE: To develop, adapt and validate DECISION+ and estimate its impact on the decision of family physicians (FPs) and their patients on whether to use antibiotics for ARIs. DESIGN: Two-arm parallel clustered pilot randomized controlled trial. SETTING AND PARTICIPANTS: Four family medicine groups were randomized to immediate DECISION+ participation (the experimental group) or delayed DECISION+ participation (the control group). Thirty-three FPs and 459 patients participated. INTERVENTION: DECISION+ is a multiple-component, continuing professional development program in shared decision making that addresses the use of antibiotics for ARIs. MAIN OUTCOME MEASURES: Throughout the pilot trial, DECISION+ was adapted in response to participant feedback. After the consultation, patients and FPs independently self-reported the decision (immediate use, delayed use, or no use of antibiotics) and its quality. Agreement between their decisional conflict was assessed. Two weeks later, patients assessed their decisional regret and health status. RESULTS: Compared to the control group, the experimental group reduced its immediate use of antibiotics (49 vs. 33% absolute difference = 16%; P = 0.08). Decisional conflict agreement was stronger in the experimental group (absolute difference of Pearson's r = 0.26; P = 0.06). Decisional regret and perceptions of the quality of the decision and of health status in the two groups were similar. DISCUSSION AND CONCLUSIONS: DECISION+ was developed successfully and appears to reduce the use of antibiotics for ARIs without affecting patients' outcomes. A larger trial is needed to confirm this observation.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".