How do physicians behave when they participate in audit and feedback activities in a group with their peers?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Audit and feedback interventions may be strengthened using social interaction. With this in mind, the Calgary office of the Alberta Physician Learning Program developed a process for audit and group feedback for physician groups. As a part of a larger project to develop a practical approach to the design and implementation of audit and group feedback projects, we explored patterns of physician behavior during facilitated audit and group feedback sessions. METHODS: Six audit and group feedback sessions were recorded, transcribed, and analyzed thematically to derive a conceptual model of physicians' behaviors during audit and group feedback sessions. RESULTS: A predictable cycle of behaviors emerged from audit and group feedback sessions. This cycle would repeat with discussion of each new data element: reacting to the data, questioning and understanding the data, justifying and contextualizing, sharing and reflecting on the data and relevant guidelines, and planning for change. "Change cues" that emerged within groups reliably pivoted the discussion towards action planning. CONCLUSIONS: In audit and group feedback sessions, physicians display a predictable series of behaviors as they move towards commitment to change. Establishing the meaning and credibility of the data is a necessary precursor to reflection. Group reflection leads to "change cues" triggered by group members, which stimulate action planning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it