ArticleFrontiers in public health2022
Knowledge and beliefs about vaccination in pregnant women before and during the COVID-19 pandemic.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Factors influencing vaccine uptake during pregnancy: A systematic literature review.Human vaccines & immunotherapeutics · 2026Pooled it
- Maternal Vaccine Acceptance and Attitudes Before and After the COVID-19 Pandemic: A Narrative Literature Review.Vaccines · 2026Review
- Do Pregnant Persons Want Influenza Vaccines? Knowledge, Attitudes, Perceptions, and Practices Toward Influenza Vaccines in 8 Low- and Middle-Income Countries.The Journal of infectious diseases · 2025Article
- Review
- Spillover effects of the COVID-19 pandemic on attitudes to influenza and childhood vaccines.BMC public health · 2023Article
- Acceptance of recommended vaccinations during pregnancy: a cross-sectional study in Southern Italy.Frontiers in public health · 2023Article
- Protecting pregnant people & infants against influenza: A landscape review of influenza vaccine hesitancy during pregnancy and strategies for vaccine promotion.Human vaccines & immunotherapeutics · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Vaccine hesitancy threatens the health of populations and challenges Public Health professionals. Strategies to reduce it aim to improve people's risk perception about vaccine-preventable diseases, fill knowledge gaps about vaccines and increase trust in healthcare providers. During pregnancy, educational interventions can provide a proper knowledge about safety and efficacy of maternal and childhood vaccinations. Fighting hesitancy and clarifying doubts is fundamental during the COVID-19 pandemic, which may have affected people's knowledge and beliefs toward vaccination. This study aimed at assessing if the advent of the pandemic was associated with changes in pregnant women's knowledge and beliefs toward vaccination, and trust in healthcare services. Methods: A repeated cross-sectional study was conducted through self-reported questionnaires in a Roman teaching hospital, where educational classes about vaccinations are routinely held as part of a birthing preparation course. Data were collected on a sample of pregnant women before and during the pandemic. Free-of-charge flu vaccinations were offered to all course participants and adherence to flu vaccination was assessed. Results: The proportion of pregnant women reporting that vaccines have mild side effects and that are sufficiently tested increased from 78.6 to 92.0% ( Conclusions: The pandemic may have positively affected pregnant women's knowledge and opinions about vaccinations and trust in HCWs, despite a possible negative impact on their perceptions about NHS operators. This should inspire Public Health professionals to rethink their role as health communicators.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.