Measuring behavioral and social drivers of COVID-19 vaccination in health workers in Eastern and Southern Africa
Notice bibliographique
Résumé
BACKGROUND: In 2021, twenty out of twenty-one countries in the Eastern and Southern Africa (ESA) region introduced COVID-19 vaccines. With variable willingness to uptake vaccines across countries, the aim of the present study was to better understand factors that impact behavioral and social drivers of vaccination (BeSD). Using the theory-based "increasing vaccination model", the drivers Thinking & Feeling, Social Processes, Motivation, and Practical Issues were adapted to the COVID-19 context and utilized in a cross-country assessment. METHODS: Data was collected on 27.240 health workers in Kenya, Malawi, Mozambique, South Africa and South Sudan. This was done by administering a survey of seven target questions via the UNICEF Internet of Good Things (IoGT) online platform between February and August 2021. RESULTS: Findings showed a gap between perceived importance and trust in vaccines: Most health workers thought Covid-19 vaccination was very important for their health, while less than 30% trusted it very much. The pro-vaccination social and work norm was not well established since almost 66% of all respondents would take the vaccine if recommended to them, but only 49% thought most adults would, and only 48% thought their co-workers would. Access was highlighted as a crucial barrier, with less than a quarter reporting that accessing vaccination services for themselves would be very easy. Women exhibited slightly lower scores than men across the board. When testing the associations between drivers in Kenya and South Africa, it appears that when target interventions are developed for specific age groups, social norms become the main drivers of intention to get vaccinated. CONCLUSIONS: The present study revealed various key relations with demographic variables that would help immunization programmes and implementing partners to develop targeted interventions. First, there is a serious gap between perceived importance of COVID-19 vaccines and how much trust people in them. Second, problems with access are still rather serious and solving this would strongly benefit those who demand a vaccine, Third, the role of social norms is the most important predictor of willingness when considering age differences.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».