Residents’ Perceptions of a Novel Virtual Livestream Cadaveric Teaching Series for Musculoskeletal Anatomy Education
Bibliographic record
Abstract
ABSTRACT: Musculoskeletal anatomy education is essential to many healthcare providers but has consistently been considered difficult for various reasons. Traditional methods have focused on in-person cadaveric teaching, which became inaccessible during the COVID-19 pandemic; therefore, new teaching methods were developed to address this gap in education. This project implemented novel virtual livestream musculoskeletal anatomy teaching methodology with cadaveric prosections and evaluated the efficacy of this modality compared with traditional in-person cadaveric teaching. A targeted musculoskeletal anatomy curriculum was developed and delivered via livestream to 12 Canadian physiatry residents. Upon completing the virtual curriculum, residents completed an anonymous survey assessing this new virtual livestream cadaveric methodology compared with previous experiences with traditional in-person anatomy teaching. The survey response rate was 92%. Most participants (73%) rated the virtual livestream sessions as better than traditional in-person teaching. Reasons included better visualization of cadaveric anatomy and easy discussion among the group. T test analysis comparing both methods demonstrated the livestream method was equivalent or better across several domains. Virtual livestream teaching is a viable method for teaching the important subject of musculoskeletal anatomy. Educators should consider how to best integrate this approach into future anatomy curricula.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".