Relative effectiveness of high‐ versus low‐fidelity simulation in learning heart sounds
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Bibliographic record
Abstract
CONTEXT: Although there are increasing numbers of studies of outcomes of high-fidelity patient simulators, few contrast their instruction with that provided by equivalent low-fidelity, inexpensive simulators. Further, examination of decays in learning and application (transfer) to real patient problems is rare. In this study, we compared the effects of training using a high-fidelity heart sound simulator (Harvey) and a low-fidelity simulator (a CD) on recognition of both simulated heart sounds and those in actual patients. METHODS: A pilot study with 10 students was conducted to show the feasibility of the methods and some evidence of modality-specific learning (the Harvey-trained group scored 72% correct on Harvey and 36% correct on CD test examples; the CD-trained group scored 60% correct on both CD and Harvey test examples). A main study was then initiated involving 37 Year 3 medical students from the University of Leeds. They received 1 hour of common instruction, after which one group received 3 hours of specific instruction on Harvey. The second group received 3 hours of instruction using a CD. Six weeks later, both groups were tested blind with real patients with stable heart sounds. Stations were observed by an examiner who scored communication skills and examination skills using 5-point scales. RESULTS: The Harvey-trained group was slightly but not significantly better than the CD-trained group at identifying heart sounds (3.11 versus 2.47, respectively; P = 0.06). However, there was no difference between the Harvey and CD-trained groups in diagnosis (2.94 versus 2.84, respectively), communication skills (18.9 versus 19.6, respectively) or examination skills (17.4 versus 17.5, respectively). CONCLUSIONS: The study found little evidence that students trained with a high-fidelity simulator were more able to transfer skills to real patients than a control group. Although there was some suggestion that the Harvey-trained group was better at recognising heart sounds, there was no difference between groups in diagnostic accuracy or clinical skills.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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