Kazan State Medical University Survey after the Use of CyberPatient<sup>TM</sup> during COVID-19
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
The COVID-19 pandemic created challenges for medical education, particularly for the acquisition of clinical skills. At Kazan State Medical University (KSMU), we used an online simulation platform called CyberPatientTM (CP) to provide a clinical environment in a virtual space with a variety of patients for students to practice their clinical skills. In this study, we surveyed 59 students who used CP in the 2020 spring semester. This survey’s objectives were to gather the students’ opinion on usability, value, efficacy and impact of the CP platform. Survey results revealed that CP is used significantly (P 0.0001) more when it is an integral part of the curriculum, it was not difficult to operate the system (96.6%); the students were satisfied with the number, quality and variety of the cases in CP platform (93.3%); over 90% of students identified CP valuable; a significant number of students (p 0.001) believed that CP was effective and 89.9% of students believed that CP had a measurably high impact on their knowledge and experience. This study concludes that the use of virtual clinical environments such as CP is perceived by students to be valuable and effective in learning clinical skills particularly during this pandemic and in the post-pandemic period when the access of students to clinical environments remains limited.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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