Comparison of a Silicon Skin Pad and a Tea Towel as Models for Learning a Simple Interrupted Suture
Why this work is in the frame
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Bibliographic record
Abstract
There has been rapid growth in the range of models available for teaching veterinary clinical skills. To promote further uptake, particularly in lower-income settings and for students to practice at home, factors to consider include cost, availability of materials and ease of construction of the model. Two models were developed to teach suturing: a silicon skin pad, and a tea towel (with a check pattern) folded and stapled to represent an incision. The models were reviewed by seven veterinarians, all of whom considered both suitable for teaching, with silicon rated as more realistic. The learning outcome of each model was compared after students trained to perform a simple interrupted suture. Thirty-two second-year veterinary students with no prior suturing experience were randomly assigned to three training groups: silicon skin pad or tea towel (both self-directed with an instruction booklet), or watching a video. Following training, all students undertook an Objective Structured Clinical Examination (OSCE), placing a simple interrupted suture in piglet cadaver skin. The OSCE pass rates of the three groups were silicon skin pad, 10/11; tea towel, 9/10; and video, 1/11. There was no significant difference between the model groups, but the model groups were significantly different from the video group ( p < .017). In conclusion, the tea towel was as effective as the silicon skin pad, but it was cheaper, simpler to make, and the materials were more readily available. In addition, both models were used effectively with an instruction booklet illustrating the value of self-directed learning to complement taught classes.
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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 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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