Determinants of Covid-19 Vaccine Acceptance among Students: A Web-Based Global Survey
Notice bibliographique
Résumé
Background: Acceptance of a COVID-19 vaccine is crucial to achieve sufficient immunization coverage to end the pandemic. After initially focusing on adults, the emphasis of vaccination is now being geared towards the younger generation. In order to mandate vaccines in schools and attain widespread vaccine uptake, it is important to understand the key determinants that influence students’ willingness to receive a COVID-19 vaccine. Hence, this study was designed to explore students’ willingness to receive a vaccine, their concerns regarding vaccination, and additional factors influencing COVID-19 vaccine acceptance. Method: Descriptive analytic cross-sectional study using snowball and convenience sample technique was conducted from July - September 2021. Social media networks such as Twitter, WhatsApp and Instagram were used. Data from the student population of both genders receiving secondary and post-secondary education was collected from the Asia-Pacific, Middle East, Europe, and America (26-countries from all over the world). Descriptive statistics and Chi square tests were used. Multivariate logistic regression analysis was used to determine significant predictors for vaccine acceptance. Results: A total of 201 participants completed the questionnaire (response rate 53%). We found considerably higher willingness (85%) to take a COVID-19 vaccine in the sample; highest among students in the West (95.0%), followed by Asia-Pacific region (84.0%) and the least among Middle East (80.0%). A statistically significant association (p = 0.000) was found between the female gender and the willingness for vaccine receival. Preserving health [OR 18.82, 95%CI 2.88-122.80], understanding the importance of vaccinations for protection against COVID 19 [OR 34.28, 95%CI 3.72-315.95], concerns about vaccine safety [OR 1.77, 95%CI1.21-28.78] and worry about potential side effects [OR 0.027, 95%CI 0.004-0.213] were significant predictors for vaccine acceptance. Conclusion: The majority of students were willing to get the COVID-19 vaccine to protect their health; but there were concerns about safety and side effects. Greater understanding about the importance of the vaccine, for protection against COVID-19 was predictive of willingness to receive the vaccine. This study provided evidence for health authorities to provide clear information, reduce misinformation and design measures to address the fears and worries about the effects of the vaccine. Future qualitative studies should be directed towards understanding differences in students’ perspectives in depth.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,037 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».