Building capacity for education research among clinical educators in the health professions: A BEME (Best Evidence Medical Education) Systematic Review of the outcomes of interventions: BEME Guide No. 34
Bibliographic record
Abstract
BACKGROUND/PURPOSE: There is a growing desire for health professions educators to generate high-quality education research; yet, few of them encounter the training to do so. In response, health professions faculties have increasingly been devoting resources to provide members with the skills necessary for education research. The form and impact of these efforts have not been reviewed, though such a synthesis could be useful for practice. The objectives of this systematic review were to (1) identify interventions aimed at building capacity for education research among health professions clinical educators and (2) review the outcomes of these interventions. METHODOLOGY: We developed a systematic review protocol based on our pilot scoping search. This protocol underwent peer review and was prospectively registered with the Best Evidence Medical Education Collaboration. Based on this protocol, we conducted a comprehensive search of health professions' databases and related grey literature. Systematic methods were applied: two independent reviewers completed title screening and full text review for inclusion, data extraction, and methodological quality assessment. Studies were included if they reported outcomes for interventions designed to increase capacity for health professions clinical educators to conduct education research. We conducted a qualitative synthesis of the evidence which included detailed reporting of intervention characteristics and outcomes. RESULTS: Our search returned 14, 149 results, 241 of which were retained after title and abstract screening, and 30 of which met inclusion criteria after full text review. Seven groups of interventions were identified, the most frequent being teaching scholars programs (n = 10), health professions education fellowships (n = 3) or master's programs (n = 4). The most commonly measured outcome was change related to enhanced scholarly outputs (grants, papers, abstracts, and presentations) post-intervention. Unfortunately, most of the included studies lacked detailed description of the intervention and were of low to moderate quality with post-test only design. DISCUSSION/CONCLUSIONS: This review demonstrates that various interventions can have a positive impact on the ability of health professions clinical educators to conduct education research. We note several key elements of the interventions including: (1) protected time, (2) mentorship and/or collaboration, (3) departmental and institutional commitment and leadership, and (4) financial support. Through our analysis we describe the complexities around evaluating clinical educators' health professions research activities and the interventions used to promote education research. While improved study quality would allow more detailed understanding and evaluation of these key features, we are able to provide recommendations for potential strategies for improving participation in and quality of health professions education research based on this analysis.
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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 | 0.099 | 0.493 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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; both teacher heads agree on what is shown here.
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".