The use of thoracoscopy to enhance medical students′ interest and understanding of thoracic anatomy
Bibliographic record
Abstract
AIM: To develop a video-based educational tool designed for teaching thoracic anatomy and to examine whether this tool would increase students' stimulation and motivation for learning anatomy. METHODS: Our video-based tool was developed by recording different thoracoscopic procedures focusing on intraoperative live thoracic anatomy. The tool was then integrated into a pre-existing program for first year medical students (n = 150), and included cadaver dissection of the thorax and review of clinical problem scenarios of the respiratory system. Students were guided through a viewing of the videotape that demonstrated live anatomy of the thorax (15 minutes) and then asked to complete a 5-point Likert-type questionnaire assessing the video's usefulness. Apart from this, a small group of entirely different set of students was divided into two groups, one group to view the 15-minute video presentation of thoracoscopy and chest anatomy and the other group to attend a 15-minute lecture of chest anatomy using radiological images. Both groups took a 10-item pretest and post-test multiple choice questions examination to assess short-term knowledge gained. RESULTS: Of 150 medical students, 119 completed the questionnaires, 88.6% were satisfied with the thoracoscopic video as a teaching tool, 86.4% were satisfied with the quality of the images, 69.2% perceived it to be beneficial in learning anatomy, 96.2% increased their interest in learning anatomy, and 88.5% wanted this new teaching tool to be implemented to the curriculum. Majority (80.7%) of the students increased their interest in surgery as a future career. Post-test scores were significantly higher in the thoracoscopy group (P = 0.0175). CONCLUSION: Incorporating live surgery using thoracoscopic video presentation in the gross anatomy teaching curriculum had high acceptance and satisfaction scores from first year medical students. The video increased students' interest in learning, in clinically applying anatomic fact, and in surgery as a future career.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| 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) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".