Vaccine hesitancy educational interventions for medical students: A systematic narrative review in western countries
Bibliographic record
Abstract
Physician recommendations can reduce vaccine hesitancy (VH) and improve uptake yet are often done poorly and can be improved by early-career training. We examined educational interventions for medical students in Western countries to explore what is being taught, identify effective elements, and review the quality of evidence. A mixed methods systematic narrative review, guided by the JBI framework, assessed the study quality using MERSQI and Cote & Turgeon frameworks. Data were extracted to analyze content and framing, with effectiveness graded using value-based judgment. Among the 33 studies with 30 unique interventions, effective studies used multiple methods grounded in educational theory to teach knowledge, skills, and attitudes. Most interventions reinforced a deficit-based approach (assuming VH stems from misinformation) which can be counterproductive. Effective interventions used hands-on, interactive methods emulating real practice, with short- and long-term follow-ups. Evidence-based approaches like motivational interviewing should frame interventions instead of the deficit model.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".