Middle East Respiratory Syndrome-Corona Virus (MERS-CoV) associated stress among medical students at a university teaching hospital in Saudi Arabia
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Middle East Respiratory Syndrome Corona Virus (MERS-CoV) outbreak in 2014 was associated with high public anxiety in the affected countries. Media speculations may have increased this psychological distress. The healthcare community was the most distressed because they were at the highest risk of infection. This study is the first to explore MERS-CoV epidemic impact on medical students' perception and determinants of their psychological distress during this outbreak. METHODS: We randomly selected and surveyed 200 students from the College of Medicine at King Saud University, Riyadh, Saudi Arabia. A predesigned questionnaire was answered by participants, and the collected data were statistically analyzed. RESULTS: One hundred and seventy-four (87%) responded. Female students had a significantly higher mean stress level than males (P < 0.001). Participants had a mean GAD score of 2.7 ± 3.1 and a median of 2. Perceived sufficiency of information score was the highest mean and median (17.4 ± 4.2 and 18 respectively). College and hospital announcements were the most common source of information (25.4%). One hundred and thirty-four (77%) reported minimal anxiety, thirty-two (18.4%) reported mild anxiety, 8 (4.6%) reported moderate anxiety, and none of them reported severe anxiety (score >14). The stress level (as reported on 1-10 scale) shows significant correlation with Generalized Anxiety Disorder (GAD-7) score. We found in this study that significant predictors in our model, in terms of more significant to the least, were: an increased self-report on hygienic habits, self-reported social avoidance, the generalized anxiety score and finally being female gander while other variables including numbers of resources access, agreeing with public fear and knowledge score on MERS-CoV all were found to be non-significant. However, the number of accessed resources, as per students, has borderline significant correlation with higher self-reported anxiety from MERS-CoV. CONCLUSIONS: Medical students' psychological needs during the MERS-CoV outbreak should be addressed appropriately. Our results highlight the need to establish psychological support programs for medical students during an infectious disease outbreak.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".