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

• Published in: Annals of behavioral medicine 2022-04, Vol.56 (4), p.357-367
• Main Authors: Shiloh, Shoshana, Peleg, Shira, Nudelman, Gabriel
• Format: Article
• Language: English
• Subjects: COVID-19 - prevention & control; COVID-19 Vaccines; Humans; Influenza Vaccines; Intention; Models, Theoretical; Vaccination
• ISSN: 0883-6612; 1532-4796
• DOI: 10.1093/abm/kaab101

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. Vaccination uptake (62% of the sample) was predicted by vaccination-related beliefs and feelings better than by disease-related beliefs or background and social factors.