Evidence map›Paper›PMID 40088513›Full record

ArticleVaccine2025

Applying the health belief model (HBM) to understand COVID-19 vaccine uptake among youth and young adults: Findings from a 6-month follow-up study in the United States.

Jiayi Xu, Shahin Davoudpour, Gregory Phillips

Abstract read
In one paragraph

Article in Vaccine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Jiayi XuDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA. Electronic address: Jackie.xu@northwestern.edu.
Shahin DavoudpourDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Gregory PhillipsDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.

Funding

Supporting COVID-19 prevention and testing for marginalized and minoritized youth and young adultsR01AA024409 · NIAAA · NORTHWESTERN UNIVERSITY AT CHICAGO · PI PHILLIPS, GREGORY L. · 2016 to 2021
$2.7M
NIAAA NIH HHS R01 AA024409
6 · The paper itself

Abstract

backgroundVaccination is one of the most effective strategies for COVID-19 prevention. Monitoring and increasing vaccine uptake among youth and young adults (YYA) not only prevents the spread of the disease but also protects their health and well-being from serious COVID-19 illness. This study applied the health belief model (HBM) to understand the predictors of COVID-19 vaccine uptake among YYA in the United States.

methodsIn early 2021, we conducted a national, online survey among diverse YYA aged 14 to 24 years in the United States. Between July 2021 and September 2022, this study followed participants who were not vaccinated for six months to learn about their vaccine status and prevention behaviors (N = 245). We explored the prevalence of COVID-19 vaccination among YYA by age, race/ethnicity, and sexual and gender identities. Multivariable logistic regression models were performed to estimate associations between HBM constructs and COVID-19 vaccination.

resultsThe majority of participants had received a vaccine. (80.8 %). We observed significant differences in COVID-19 vaccination uptake by age; those aged 18 to 21 years were over 3 times as likely to report receiving a vaccine. Regarding the HBM constructs, we found that health motivation, perceived benefits, and protection self-efficacy were significantly associated with vaccine uptake among YYA.

conclusionThis study highlights the effectiveness of HBM in understanding COVID-19 vaccine uptake among YYA in the United States. The findings suggest that health motivation, perceived benefits of vaccination, and protection self-efficacy are key factors driving vaccine uptake in this demographic. Significant age differences in vaccination rates indicate that targeted interventions for younger age groups, particularly those aged 14 to 17 years, may be necessary to increase vaccination coverage. These insights can inform future public health strategies to improve vaccine acceptance and uptake, ensuring better health outcomes and protection against future public health crises in YYA populations.

Indexed as

COVID-19COVID-19 VaccinesHealth Belief ModelPatient Acceptance of Health CareVaccinationAdolescentFemaleFollow-Up StudiesHealth Knowledge, Attitudes, PracticeHumansMaleSARS-CoV-2Surveys and QuestionnairesUnited StatesVaccination HesitancyYoung AdultCOVID-19 VaccinesAdolescentsCOVID-19 vaccineHealth belief modelPrevention

Identifiers

PMID40088513
PMCPMC12128853

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Registered trials

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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.