Pilot Study on Integrating 3D-Printed Models Into Undergraduate Medical Education for Congenital Heart Disease
Bibliographic record
Abstract
Background This study aimed to assess the feasibility and effectiveness of implementing 3D-printed heart models in the education of medical students in a Canadian Medical School. Methods Three types of 3D-printed models – normal, unrepaired Tetralogy of Fallot (TOF) and surgically repaired adult TOF – were provided for medical students in their 2nd year of training after a 30-minute lecture. The repaired TOF model depicted a transannular patch, ventricular septal defect closure, and right ventricular outflow tract resection. Knowledge acquisition was measured by comparing pre-and post-session tests consisting of 5 questions. Learner satisfaction ratings were measured with questionnaires completed after the session. A statistical analysis was performed using the t-test. Results Twenty-two medical students participated in the study with 20 students submitting complete data for analysis. The students' score on 5 questions improved after the 3D-printed model session. The average number of correct answers in the test was 2.1 ± 1.0 pre-session and 4.3 ± 0.9 post-session (P < 0.001) out of the possible total of 5. Participants reported a high level of satisfaction (86.4%), understanding (86.4%), and usefulness (90.9%) with the incorporation of 3D-printed models in the educational session. Conclusions An educational session which integrated 3D-printed anatomic models to teach congenital heart disease anatomy significantly enhanced knowledge outcomes. Learner assessment of the impact of the use of the 3D models was highly favourable.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".