Predictors of Change in Vaccination Decisions Among the Vaccine Hesitant: Examining the Roles of Age and Intolerance of Uncertainty.

Abstract

BACKGROUND Vaccine hesitancy and resistance pose significant threats to controlling pandemics and preventing infectious diseases. In a group of individuals unvaccinated against the disease caused by the SARS-CoV-2 coronavirus (COVID-19), we investigated how age, intolerance of uncertainty (IU), and their interaction affected the likelihood of having changed one's vaccination decision a year later. We hypothesized that higher IU would increase the likelihood of becoming vaccinated, particularly among individuals of younger age. We predicted that this effect would remain significant, even after controlling for delay discounting and trust in science. PURPOSE The goal of this research was to understand the factors influencing changes in vaccination decisions among the vaccine hesitant. METHODS In a larger longitudinal study, ~7,500 participants from Prolific.co completed demographic and vaccination status questions, a delay discounting task, and the Intolerance of Uncertainty Scale in June-August 2021. Approximately 3,200 participants completed a follow-up survey in July-August 2022, answering questions about vaccination status, reasons for vaccination decision, and trust in science. We analyzed data from 251 participants who initially had no intention of getting vaccinated and completed the follow-up survey; 38% reported becoming vaccinated in the intervening year. RESULTS Data were analyzed using multilevel logistic regression. Over and above other factors related to vaccination decisions (delay discounting, trust in science), younger participants were more likely to change their decision and become vaccinated a year later, especially if they had higher IU, confirming our predictions. Primary reasons for becoming vaccinated were necessity and seeking protection against the virus. CONCLUSIONS These findings highlight the complex interplay between age, uncertainty, and vaccination decisions, and inform health policies by suggesting the need for tailoring interventions to specific concerns in different age groups.