The Resource Costs of Maintaining Learner Utilization of a Simulation Center During the COVID-19 Pandemic
Bibliographic record
Abstract
BACKGROUND: Despite advances in online education during the COVID-19 pandemic, its impact on surgical simulation remains unclear. The aim of this study was to compare the costs and resources required to maintain simulation training in the pandemic and to evaluate how it affected exposure of medical students to simulation during their surgical clerkship. METHODS: The number of learners, contact hours, staff hours, and costs were collected from a multi-departmental simulation center of a single academic institution in a retrospective fashion. Utilization and expenditure metrics were compared between the first quarter of academic years 2018-2020. Statistical analysis was performed to evaluate potential differences between overall resource utilization before and during the pandemic, and subgroup analysis was performed for the resources required for the training of the third-year medical students. RESULTS: The overall number of learners and contact hours decreased during the first quarter of the academic year 2020 in comparison with 2019 and 2018. However, the staff hours increased. In addition, the costs for PPE increased for the same periods of time. In the subgroup analysis of the third-year medical students, there was an increase in the number of learners, as well as in the staff hours and in the space required to perform the simulation training. DISCUSSION: Despite an increase in costs and resources spent on surgical simulation during the pandemic, the utilization by academic entities has remained unaffected. Further studies are required to identify potential solutions to lower simulation resources without a negative impact on the quality of surgical simulation.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".