The Application of Low-fidelity Chest Tube Insertion Using Remote Telesimulation in Training Healthcare Professionals
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Healthcare professionals practicing in rural, remote, or resource-restricted areas have little opportunity to practice "high stakes low-frequency" clinical procedures, despite having higher rates of injury-related death than city inhabitants. Availability of clinical skills instructors, the expense of practicing skills, lack of educational sessions, and distance to simulation centres can be a barrier to teaching and skill maintenance, particularly in rural settings. Telesimulation has the potential to overcome these challenges using audio-visual technology to connect rural learners with instructors in simulation centres. Using low-fidelity simulation models allows learners to acquire clinical skills through hands-on practice without risk or fear of harming real patients. Although not as realistic as high-fidelity models, the low-fidelity three-dimensional (3D) printed model for chest tube insertion is cost-effective and easy to set up and use and is a valid tool for teaching the clinical procedure. The purpose of this technical report was to describe the application of low-cost telesimulation to facilitate teaching chest tube insertion to medical students, emergency medicine residents, and doctors working in remote and rural environments.
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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 | 0.000 |
| 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 it