Which Volunteering Settings Do Medical Students Prefer During a Novel Respiratory Virus Pandemic? A Cross-Sectional Study of Multiple Colleges in Central Saudi Arabia During the COVID-19 Pandemic.
Bibliographic record
Abstract
Purpose: Novel respiratory virus outbreaks are a recurring public health concern. Volunteering medical students can be a valuable asset during such times. This study investigated the willingness of medical students to volunteer during the coronavirus disease of 2019 (COVID-19) pandemic and the barriers to doing so, considering the possibility of exposure to COVID-19 and mode of contact. Patients and methods: This cross-sectional study was conducted using a self-administered online questionnaire adapted from the literature. The questionnaire comprised four parts: demographic variables, COVID-19-related variables, willingness scale, and barrier scale. The target population was medical students at four different colleges in Riyadh, Saudi Arabia. Results: A total of 802 students participated in the study. A small proportion of students (10.6%) were willing to participate in volunteering activities that could involve contact with patients with COVID-19 as compared to other settings (39.4-43.4%). More than one-quarter of students (26.8%) had risk factors for severe COVID-19. The main barrier to volunteering was the concern of transmitting the infection to family members (76.8%). Registration to receive the COVID-19 vaccine was positively associated with more willingness to volunteer (β=0.17, p <0.001), whereas residing in a household with an elderly person was negatively associated (β=-0.13, p <0.001). Female sex was positively associated with higher barrier score (β=0.12, p <0.001). Conclusion: Medical students were more willing to volunteer in activities that did not involve direct contact with patients with COVID-19. A considerable proportion of participants had risk factors for severe illness. Sharing a household with an elderly person or child was associated with lower willingness to volunteer. Organizers of volunteering activities should offer various volunteering options considering the risk of infection; and be mindful of barriers to volunteering, especially risk factors for severe illness and eldercare and childcare responsibilities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".