The Impact of the COVID-19 Pandemic on Research and Volunteering Activities among Medical Students: A Cross-Sectional Study among Romanian and International Students from One Medical Faculty from Romania
Bibliographic record
Abstract
INTRODUCTION: This study focuses on the influence of the COVID-19 pandemic on medical students in their last year of study at the Faculty of Medicine of the University of Medicine and Pharmacy in Cluj-Napoca, Romania. It analyzes the impact of social distance limits on the conduct of research activities required for the development of the graduation thesis, as well as assesses sixth-year students' attitudes and behaviors toward volunteer activities during the COVID-19 pandemic. METHODS: = 606). The response rate was 38.28%, resulting in a final sample of 232 students from both Romanian and international sections. RESULTS: The findings demonstrate that two-thirds of the students in the survey agreed that the COVID-19 pandemic had a substantial impact on their research. Some of the students had to choose another subject for their graduation thesis, while about a quarter of the students gave up collecting personal data, 25% of respondents stated that it was difficult to contact research participants, one-third of them linked the difficulty of doing activities at the hospital to the present outbreak, and almost 30% of the students had difficulty communicating with the coordinator. The disturbance of the research activity seems to be higher among international students in comparison with the Romanian students, while there are limited gender differences. One out of five medical students has been involved in volunteer activities during the pandemic. Most have opted to volunteer at hospitals (especially international students) and contribute to health education activities (especially women). CONCLUSIONS: This is the first study from Romania and one of the few from Europe that presents data regarding the influence of the COVID-19 pandemic on research and volunteering activities among medical students.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".