Leadership training programs in graduate medical education: a systematic review
Bibliographic record
Abstract
BACKGROUND: With the increasing recognition that leadership skills can be acquired, there is a heightened focus on incorporating leadership training as a part of graduate medical education. However, there is considerable lack of agreement regarding how to facilitate acquisition of these skills to resident, chief resident, and fellow physicians. METHODS: Articles were identified through a search of Ovid MEDLINE, EMBASE, CINAHL, ERIC, PsycNet, Cochrane Systemic Reviews, and Cochrane Central Register of Controlled Trials from 1948 to 2019. Additional sources were identified through contacting authors and scanning references. We included articles that described and evaluated leadership training programs in the United States and Canada. Methodological quality was assessed via the MERSQI (Medical Education Research Study Quality Instrument). RESULTS: Fifteen studies, which collectively included 639 residents, chief residents, and fellows, met the eligibility criteria. The format, content, and duration of these programs varied considerably. The majority focused on conflict management, interpersonal skills, and stress management. Twelve were prospective case series and three were retrospective. Seven used pre- and post-test surveys, while seven used course evaluations. Only three had follow-up evaluations after 6 months to 1 year. MERSQI scores ranged from 6 to 9. CONCLUSIONS: Despite interest in incorporating structured leadership training into graduate medical education curricula, there is a lack of methodologically rigorous studies evaluating its effectiveness. High-quality well-designed studies, focusing particularly on the validity of content, internal structure, and relationship to other variables, are required in order to determine if these programs have a lasting effect on the acquisition of leadership skills.
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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 | 0.011 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".