The Calgary Audit and Feedback Framework: a practical, evidence-informed approach for the design and implementation of socially constructed learning interventions using audit and group feedback
Bibliographic record
Abstract
BACKGROUND: Audit and feedback interventions may be strengthened using social interaction. The Calgary office of the Alberta Physician Learning Program (CPLP) developed a process for audit and group feedback for physicians. This paper extends previous work in which we developed a conceptual model of physician responses to audit and group feedback based on a qualitative analysis of six audit and group feedback sessions. The present study explored the mediating factors for successfully engaging physician groups in change planning through audit and group feedback. METHODS: To understand why some groups were more interactive than others, we completed a comparative case analysis of the six audit and group feedback projects from the prior study. We used framework analysis to build the case studies, triangulated our observations across data sources to validate findings, compared the case studies for similarities and differences that influenced social interaction (mediating factors), and thematically categorized mediating factors into an organizing framework. RESULTS: Mediating factors for socially interactive AGFS were a pre-existing relationship between the program team and the physician group, projects addressing important, actionable questions, easily interpretable data visualization in the reports, and facilitation of the groups that included reflective questioning. When these factors were in place (cases 1, 2A, 3), the audit and group feedback sessions were dynamic, with physicians sharing and comparing practices, and raising change cues (such as declaring commitments to de-prescribing, planning educational interventions, and improving documentation). In cases 2C-D, the mediating factors were less well established and in these cases, the sessions showed little physician reflection or change planning. We organized the mediating factors into a framework linking the factors for successful sessions to the conceptual model of physician behaviors which these mediating factors drive. CONCLUSIONS: We propose the Calgary Audit and Feedback Framework as a practical tool to help foster socially constructed learning in audit and group feedback sessions. Ensuring that the four factors, relationship, question choice, data visualization, and facilitation, are considered for design and implementation of audit and group feedback will help physicians move from reactions to their data towards planning for change.
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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 | 0.334 | 0.216 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.020 | 0.010 |
| Science and technology studies | 0.011 | 0.022 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.010 | 0.015 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".