Rethinking Context in Continuing Professional Development: From Identifying Barriers to Understanding Social Dynamics
Bibliographic record
Abstract
INTRODUCTION: For continuing professional development (CPD) to reach its potential to improve outcomes requires an understanding of the role of context and the influencing conditions that enable interventions to succeed. We argue that the heuristic use of frameworks to design and implement interventions tends to conceptualize context as defined lists of barriers, which may obscure consideration of how different contextual factors interact with and intersect with each other. METHODS: We suggest a framework approach that would benefit from postmodernist theory that explores how ideologies, meanings, and social structures in health care settings shape social practices. As an illustrative example, we conducted a Foucauldian discourse analysis of diabetes care to make visible how the social, historical, and political conditions in which clinicians experience, practice, and shape possibilities for behavior change. RESULTS: The discursive construction of continuing education as a knowledge translation mechanism assumes and is contingent on family physicians to implement guidelines. However, they enact other discursively constituted roles that may run in opposition. This paradoxical position creates a tension that must be navigated by family physicians, who may perceive it possible to provide good care without necessarily implementing guidelines. DISCUSSION: We suggest marrying "framework" thinking with postmodernist theory that explores how ideologies, meanings, and social structures shape practice behavior change. Such a proposed reconceptualization of context in the design of continuing professional development interventions could provide a more robust and nuanced understanding of how the dynamic relationships and interactions between clinicians, patients, and their work environments shape educational effectiveness.
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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 | 0.061 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.018 | 0.112 |
| Scholarly communication | 0.023 | 0.038 |
| Open science | 0.005 | 0.024 |
| Research integrity | 0.006 | 0.011 |
| 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".