Barriers and facilitators to the cultivation of communities of practice for faculty development in medical education: A scoping review
Bibliographic record
Abstract
BACKGROUND: Communities of practice (CoPs) have been promoted as a strategy to foster the professional development of faculty. In recent years, there have been a rising number of publications in the field of medical education that report on the impact of CoPs in faculty development (FD), as well as the factors that influence their cultivation. The objective of this scoping review was to comprehensively map the reported barriers and facilitators to cultivating CoPs for FD in medical education. METHODS: The authors searched five electronic databases on 15 January 2022, and in a final update search on 4 August 2024. The authors used the updated Consolidated Framework for Implementation Research as an a priori coding framework to guide coding. The authors applied a quasi-statistical content analysis to quantify and draw meaning from the factors that constrain and support CoP formation, implementation and sustainability. RESULTS: The authors generated 359 codes for barriers and facilitators from 25 included empirical and non-empirical articles, of which 295 codes (82%) were relevant to forming and implementing a CoP, and 64 (18%) relevant to sustaining a CoP. The main barriers and facilitators were related to: the sufficiency of structural, cultural and resource support; the availability and fit of required stakeholders; relevance to member needs; planning; member attraction and engagement; and reflection and evaluation of the CoP. CONCLUSIONS: This review highlights the key patterns and gaps in the emerging publications on CoP cultivation for FD in medical education, from their formation to their sustainability. There remain key unresolved problems and gaps in the evidence concerning how to create long-term participation successfully to sustain CoPs for FD in medical education. Although hybrid and virtual CoPs appear to be the way forward, there is still a need to account for individual member capabilities and needs, and the nature of the medical education context on CoP sustainability.
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How this classification was reachedexpand
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 | 0.006 | 0.106 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".