COVID-19 Vaccine Hesitancy, Protective Behaviors, and Risk Perception among University Students in Alexandria
Bibliographic record
Abstract
Background: Quick vaccine rollouts and compliance with preventive strategies are crucial for acountry recovery from COVID-19, but vaccine hesitancy could prolong the pandemic and the needfor physical distancing and lockdowns. Aim of the study: was to assess the levels of COVID-19vaccine hesitancy, protective behaviors and risk perception among university students inAlexandria. Study design: An online cross-sectional exploratory survey research design was usedin this study. Setting: This study was conducted in all faculties affiliated to Alexandria University.Subjects: Convenient sample of 1000 university students were selected by equal allocation method.Tools of data collection: Three tools were used for data collection. The first tool was “VaccineHesitancy Scale” to assess the students’ hesitancy toward COVID-19 vaccines. The second tool was“The Protective behavior against COVID-19 Scale” to measure the protective behaviors againstCOVID-19. While, the third tool was “Risk Perception Scale” to measure the public risk perceptionfor public health emergencies. Results: The results of this study showed that more than one quarterof them had a high level of vaccine hesitancy, while less than half of them had a good level ofprotective behaviors against COVID 19. On the other hand, less than one quarter of the studiedstudents had high level of risk perception. Conclusion: The study concluded that universitystudents, are among the population at risk of being infected with COVID‐19 and transmitting theinfection to others owing to the sense of invulnerability and their poor compliance with protectivebehaviors, including administration of vaccination against Covid-19. Recommendations: It isessential to raise awareness among university students about Covid-19 to change negative vaccineattitudes and increase the acceptance and uptake of Covid-19 vaccines
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".