Evaluation of an evidence-based medicine educational intervention in a regional medical campus
Bibliographic record
Abstract
BACKGROUND: Enhanced educational activities were developed by a regional medical campus (RMC) in order to incorporate evidence-based medicine (EBM) practice in the learning process of medical students. This study aimed to measure the effectiveness of these activities. METHODS: The experimental group was made up of third-year students from the RMC. The comparison group included students from the main campus of the medical school and another of its RMCs. The experimental group received additional training on EBM: one additional hour in class, plus skills development exercises throughout the semester. During the regular academic sessions, clinical questions requiring EBM literature searching skills were incorporated in the curriculum. Tests on knowledge and self-assessment of competencies were administered to all participants at the beginning and at the end of the semester. Data were analyzed using repeated measures analysis of variance and post hoc tests for within and between groups comparison. RESULTS: The Friedman test demonstrated a statistically significant effect of the intervention on knowledge (p <0.0001). The score of the knowledge test was significantly higher for the experimental group, when compared with baseline testing and with the comparison group (p <0.0001). Repeated measures analysis of variance demonstrated a statistically significant effect of the intervention on the score of the self-assessment of competencies (p=0.032). The score for the self-assessment of competencies was significantly higher for the experimental group when compared to baseline score (p <0.0001), but not with respect to the comparison group. CONCLUSION: Our study demonstrated the effectiveness of additional training and longitudinal integrated skills development leading to an increase in medical student knowledge and self-perception of competencies in EBM practice.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".