Complexities of Continuing Professional Development in Context: Physician Engagement in Clinical Coaching.
Bibliographic record
Abstract
INTRODUCTION: Effective continuing professional development (CPD) is critical for safe and effective health care. Recent shifts have called for a move away from didactic CPD, which often fails to affect practice, toward workplace learning such as clinical coaching. Unfortunately, coaching programs are complex, and adoption does not guarantee effectiveness. To resolve this problem, thus ensuring resources are well spent, there is a critical need to understand what physicians try to achieve and how they engage. Therefore, we examined the types of change physicians pursue through clinical coaching and the impact of context on their desired changes. METHODS: In the context of two clinical coaching programs for rural physicians, we applied a generic qualitative approach. Coachees (N = 15) participated in semistructured interviews. Analysis involved iterative cycles of initial, focused, and theoretical coding. RESULTS: Coachees articulated desired practice changes along a spectrum, ranging from honing their current practice to making larger changes that involved new skills outside their current practice; changes also ranged from those focused on individual physicians to those focused on the practice system. Desired changes were affected by factors in the learning/practice environment, including those related to the individual coachee, coach, and learning/practice context. DISCUSSION: These results suggest that the current focus on acquiring new knowledge through CPD may miss important learning that involves subtle shifts in practice as well as learning that focusses on systems change. Moreover, an appreciation of the contextual nature of CPD can ensure that contextual affordances are leveraged and barriers are acknowledged.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".