Feasibility of a randomised trial of a continuing medical education program in shared decision-making on the use of antibiotics for acute respiratory infections in primary care: the DECISION+ pilot trial
Bibliographic record
Abstract
BACKGROUND: The misuse and limited effectiveness of antibiotics for acute respiratory infections (ARIs) are well documented, and current approaches targeting physicians or patients to improve appropriate use have had limited effect. Shared decision-making could be a promising strategy to improve appropriate antibiotic use for ARIs, but very little is known about its implementation processes and outcomes in clinical settings. In this matter, pilot studies have played a key role in health science research over the past years in providing information for the planning, justification, and/or refinement of larger studies. The objective of our study was to assess the feasibility and acceptability of the study design, procedures, and intervention of the DECISION+ program, a continuing medical education program in shared decision-making among family physicians and their patients on the optimal use of antibiotics for treating ARIs in primary care. METHODS: A pilot clustered randomised trial was conducted. Family medicine groups (FMGs) were randomly assigned, to either the DECISION+ program, which included three 3-hour workshops over a four- to six-month period, or a control group that had a delayed exposure to the program. RESULTS: Among 21 FMGs contacted, 5 (24%) agreed to participate in the pilot study. A total of 39 family physicians (18 in the two experimental and 21 in the three control FMGs) and their 544 patients consulting for an ARI were recruited. The proportion of recruited family physicians who participated in all three workshops was 46% (50% for the experimental group and 43% for the control group), and the overall mean level of satisfaction regarding the workshops was 94%. CONCLUSIONS: This trial, while aiming to demonstrate the feasibility and acceptability of conducting a larger study, has identified important opportunities for improving the design of a definitive trial. This pilot trial is informative for researchers and clinicians interested in designing and/or conducting studies with FMGs regarding training of physicians in shared decision-making. TRIAL REGISTRATION: Clinicaltrials.Gov NCT00354315.
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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 | 0.020 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".