End User Comparison of Anatomically Matched 3‐Dimensional Printed and Virtual Haptic Temporal Bone Simulation
Bibliographic record
Abstract
OBJECTIVE: Simulation has assumed a prominent role in education. It is important to explore the effectiveness of different modalities. In this article, we directly compare surgical resident impression of 2 distinct temporal bone simulations (physical and haptic). STUDY DESIGN: Research Ethics Board-approved prospective cohort study. SETTING: A haptic voxel-based virtual model (VM) and a physical 3-dimensional printed temporal bone model (PBM) were developed. Participants rated each construct on a number of parameters and performed a direct comparison of the simulations using a survey instrument that employed a 7-point Likert scale and rank lists. SUBJECTS AND METHODS: Ten otolaryngology residents dissected anatomically identical, matched physical and virtual models. Data for both simulations originated from 10 unique cadaveric micro-computed tomography images. RESULTS: Subjects rated the PBM drill quality as being more similar to cadaveric temporal bone than the VM (cortical bone mean: 5.5 vs 3.2, P = .011; trabecular bone mean: 5.2 vs 2.8, P = .004) and with better air cell system representation (mean: 5.4 vs 4.5, P = .003). Subjects strongly agreed that both simulations are effective educational tools, but they rated the PBM higher (mean: 6.7 vs 5.4, P = .019). Notably, subjects agreed that both modalities should be integrated into training, but they were more favorably inclined toward the PBM (mean: 7.0 vs 5.5, P = .002). In direct comparison, the PBM was the preferred simulation in 7 of 9 educational domains. CONCLUSIONS: Appraisal of a PBM and a VM found both to have perceived educational benefit. However, the PBM was considered to have more realistic physical properties and was considered the preferred training instrument.
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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 | 0.000 |
| 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".