JOURNAL ARTICLE

The Role of Information Uses and Trust in COVID-19 and Influenza Vaccine Hesitancy Among Undergraduate Students in the United States and Republic of Korea: A Cross-Sectional Study.

  • Published In: Journal of Transcultural Nursing, 2026, v. 37, n. 3. P. 514 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Jo, Soojung; Xu, Dongjuan; Cho, Yeseol 3 of 3

Abstract

This study examines how information source use and trust relate to COVID-19 and influenza vaccine hesitancy and influenza vaccine uptake among undergraduate students aged 18–25 in the United States and the Republic of Korea. Findings indicate that occasional Internet use and lower trust in health care providers and professional organizations are associated with higher COVID-19 vaccine hesitancy, while influenza vaccine hesitancy is linked to using family as an information source but lower trust in family. Influenza vaccine uptake was positively associated with frequent use of professional sources and social media, but negatively associated with frequent use of the Internet and friends or co-workers. Cross-national differences showed that Korean students reported higher COVID-19 vaccine hesitancy but greater influenza vaccine uptake compared to US students. These results suggest tailored public health strategies that strengthen professional communication channels, engage family networks, and optimize online platforms to address vaccine hesitancy and promote vaccination among young adults.

Additional Information

  • Source:Journal of Transcultural Nursing. 2026/05, Vol. 37, Issue 3, p514
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2026
  • ISSN:1043-6596
  • DOI:10.1177/10436596251411080
  • Accession Number:192851170
  • Copyright Statement:Copyright of Journal of Transcultural Nursing is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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