Vaccine intention and hesitancy among Australian women who are currently pregnant or have recently given birth: the Birth in the Time of COVID-19 (BITTOC) national online survey
Notice bibliographique
Résumé
OBJECTIVE: To examine the prevalence of COVID-19 vaccination, and factors associated with vaccination intention and hesitancy in pregnant and postnatal women in Australia. DESIGN AND SETTING: A national online survey was conducted over 6 months between 31 August 2021 and 1 March 2022 and responses to vaccination status were categorised as: 'vaccinated', 'vaccine intended' and 'vaccine hesitant'. The data were weighted to reflect the proportion of women of reproductive age. Potential confounding variables were examined using multinomial logistic regression analyses, and all comparisons were made against vaccinated pregnant and postnatal women. PARTICIPANTS: 2140 women responded to the survey (838 pregnant; 1302 recently post partum). RESULTS: Amongst pregnant women, 586 (69.9%) were vaccinated, 166 (19.8%) indicated intention and 86 (10.3%) were hesitant. In postnatal women, this was 1060 (81.4%), 143 (11.0%) and 99 (7.6%), respectively. Only 52 (6.2%) of pregnant women stated never wanting a COVID-19 vaccine. Vaccine hesitancy increased over time, and for pregnant women was associated with: living in a state other than New South Wales (NSW) (Adjusted Relative Risk (ARR) 2.77, 95%CI: 1.68-4.56 for vaccine intention and ARR=3.31, 95%CI: 1.52-7.20 for vaccine hesitancy), younger age <30 years, not having a university education, income <80K AUD, gestation <28 weeks, having no pregnancy risk factors, and being less satisfied with life (ARR=2.20, 95%CI: 1.04-4.65 for vaccine intention and ARR=2.53, 95%CI: 1.02-6.25 for vaccine hesitancy) . For postnatal women: living in a state other than NSW or Victoria, income <80K AUD and having private obstetric care (ARR=2.06, 95%CI: 1.23-3.46) were significantly associated with vaccine hesitancy. CONCLUSIONS: Around 1 in 10 pregnant women and just over 1 in 13 postnatal women reported vaccine hesitancy in this Australian survey, and hesitancy was higher in the latter 3-month period. Tailored messages to younger mothers and those from lower-middle socioeconomic groups, alongside advice from midwives and obstetricians, could help to reduce hesitancy among pregnant and postnatal women. Financial incentives may help to facilitate COVID-19 vaccine uptake. A real-time surveillance system and additional pregnancy fields added to the Australian immunisation register would support the safety monitoring of multiple vaccines in pregnancy and may build confidence.
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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 | 0,006 | 0,007 |
| 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 | 0,000 | 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 ».