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COVID-19 and influenza vaccine-hesitancy subgroups

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Listed:
  • Karl O Mäki
  • Linda C Karlsson
  • Johanna K Kaakinen
  • Philipp Schmid
  • Stephan Lewandowsky
  • Jan Antfolk
  • Anna Soveri

Abstract

Health communicators are faced with the challenge that people can hesitate vaccines for different reasons. Our aim was to identify and describe the qualities of distinct COVID-19 and influenza vaccine-hesitancy subgroups to facilitate the development of tailored vaccine-hesitancy communication. In two studies, we used agglomerative hierarchical cluster analysis to identify COVID-19 (N = 554) and influenza (N = 539) vaccine-hesitancy subgroups in the general population based on nine vaccine hesitancy-related variables (intent to get vaccinated, perceived vaccine safety, perceived vaccine efficacy, perceived disease threat, perceived vaccination responsibility, perceived vaccination convenience, distrust in authorities, conspiracy mentality, and reliance on anecdotal testimonies). We identified and described six distinct COVID-19 vaccine-hesitancy subgroups (the Vaccination Positive, the Ambivalent, the Fearing Skeptic, the Unconvinced, the Constrained Skeptic, and the Vaccination Opponent), and three influenza vaccine-hesitancy subgroups (the Vaccination Positive, the Complacent, and the Vaccination Opponent), with different levels of hesitancy. We discuss the implications of the results for health communicators. Our results shed light on the (dis)similarities between people who hesitate COVID-19 and influenza vaccines and suggest that there is greater variety in hesitancy concerning COVID-19 vaccinations than influenza vaccinations. These findings can be used to design and test tailored vaccination messages.

Suggested Citation

  • Karl O Mäki & Linda C Karlsson & Johanna K Kaakinen & Philipp Schmid & Stephan Lewandowsky & Jan Antfolk & Anna Soveri, 2024. "COVID-19 and influenza vaccine-hesitancy subgroups," PLOS ONE, Public Library of Science, vol. 19(7), pages 1-21, July.
    • Handle: RePEc:plo:pone00:0308159
    DOI: 10.1371/journal.pone.0308159
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    References listed on IDEAS

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    1. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
    2. Angelo Fasce & Philipp Schmid & Dawn L. Holford & Luke Bates & Iryna Gurevych & Stephan Lewandowsky, 2023. "A taxonomy of anti-vaccination arguments from a systematic literature review and text modelling," Nature Human Behaviour, Nature, vol. 7(9), pages 1462-1480, September.
    3. repec:plo:pone00:0208601 is not listed on IDEAS
    4. Karl O Mäki & Linda C Karlsson & Johanna K Kaakinen & Philipp Schmid & Stephan Lewandowsky & Jan Antfolk & Anna Soveri, 2023. "Tailoring interventions to suit self-reported format preference does not decrease vaccine hesitancy," PLOS ONE, Public Library of Science, vol. 18(3), pages 1-23, March.
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