Vaccination Against COVID-19: A Longitudinal Trans-Theoretical Study to Determine Factors that Predict Intentions and Behavior

Shoshana Shiloh*, Shira Peleg, Gabriel Nudelman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

Background: Despite the clear benefits of vaccination, their uptake against common infectious diseases is suboptimal. In December 2020, vaccines against COVID-19 became available. Purpose: To determine factors that predict who will take the COVID-19 vaccine based on a conceptual model. Methods: An online survey was administered twice: prior to public vaccination, and after vaccinations were available. Participants were 309 Israelis with initial data and 240 at follow-up. Baseline questionnaires measured intentions to be vaccinated and hypothesized predictors clustered in four categories: background, COVID-19, vaccination, and social factors. Self-reported vaccination uptake was measured at follow-up. Results: Sixty-two percent of the sample reported having been vaccinated. Intentions were strongly associated with vaccination uptake and mediated the effects of other predictors on behavior. Eighty-six percent of the variance in vaccination intentions was explained by attitudes toward COVID-19 vaccination, regret for having declined vaccination, trust in vaccination, vaccination barriers, past flu vaccination, perceived social norms, and COVID-19 representations. Conclusions: Beliefs related directly to the COVID-19 vaccine explained most of the variance in intentions to vaccinate, which in turn predicted vaccination uptake.

Original languageEnglish
Pages (from-to)357-367
Number of pages11
JournalAnnals of Behavioral Medicine
Volume56
Issue number4
DOIs
StatePublished - 1 Apr 2022

Keywords

  • COVID-19
  • Intentions
  • Prediction
  • Vaccination

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