Exploring the global impact of the COVID-19 pandemic on medical education: an international cross-sectional study of medical learners
Bibliographic record
Abstract
Abstract To broadly explore the extent that COVID-19 has initially impacted medical learners around the world and examine global trends and patterns across geographic regions and levels of training, a cross-sectional survey of medical learners was conducted between March 25-June 14 th , 2020, shortly after the World Health Organization declared concurrent COVID-19 a pandemic. 6492 medical learners completed the survey from 140 countries, Students were concerned about the quality of their learning, training progression, and milestone fulfillment. Most trainees felt under-utilized and wanted to be engaged clinically in meaningful ways; however, some trainees felt that contributing to healthcare during a pandemic was beyond the scope of a medical learner. Statistically significant differences were detected between levels of training and geographic regions for satisfaction with organizational responses, the impact of COVID-19 on wellness, and state-trait anxiety. Overall, the initial disruption to medical training has been perceived by learners across all levels and geographic regions to have negatively affected their training and well-being, particularly amongst postgraduate trainees. These results provide initial insights into the areas that warrant future research as well as consideration for current and future policy planning, such as the policies for clinical utilization of medical learners during public health emergencies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".