Increasing Scholarly Activity Productivity During Residency: A Systematic Review
Bibliographic record
Abstract
PURPOSE: Although resident participation in scholarly activity is mandated by the Accreditation Council for Graduate Medical Education, programmatic factors associated with success are not defined. This systematic review's objective was to determine which interventions are effective in increasing resident scholarly activity productivity (RSAP), as measured by participation in scholarly activity, presentations, or publications. METHOD: The PubMed, MEDLINE, Cochrane Library of Systematic Reviews, PsycINFO, CINAHL, and ERIC databases were searched through October 2013. English-language articles evaluating interventions to increase RSAP in U.S. or Canadian residency programs were included, without date limits. Two independent reviewers selected articles for inclusion and extracted data. Discrepancies were resolved by consensus. RESULTS: Of the 6,248 records screened, 80 studies underwent data abstraction. Twenty-six described outcomes without a comparison group, leaving 54 studies representing 13 medical and surgical specialties. Interventions included required scholarly activity participation, protected research time, research curricula, research directors, dedicated research days, and research tracks. Focusing on the 35 studies reporting statistical analysis, RSAP was associated with all interventions. There were some differences in intervention effectiveness between medical and surgical specialties. CONCLUSIONS: Interventions, including protected time, research curricula, or specialized research tracks, generally result in increased participation in scholarly activity in residency programs, with mixed effects on resident presentations or publications. In many studies, interventions were bundled, suggesting that programs may need to provide increased structure and rigor through multiple pathways. The findings highlight the need for a clear definition of resident scholarly activity success aligned specifically to individual program and resident aims.
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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 | 0.015 | 0.074 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".