How do psychobehavioural variables shed light on heterogeneity in COVID-19 vaccine acceptance? Evidence from United States general population surveys on a probability panel and social media

• Published in: BMJ open Vol. 13; no. 6; p. e066897
• Main Authors: Charles, Grace K, Braunstein, Sofia P, Barker, Jessica L, Fung, Henry, Coome, Lindsay, Kumar, Rohan, Huang, Vincent S, Kemp, Hannah, Grant, Eli, Bernard, Drew, Barefoot, Darren, Sgaier, Sema K
• Format: Journal Article
• Language: English
• Published: England British Medical Journal Publishing Group 06-06-2023; BMJ Publishing Group LTD; BMJ Publishing Group
• Series: Original research
• Subjects: Adult; Behavior; COVID-19; COVID-19 - epidemiology; COVID-19 - prevention & control; COVID-19 vaccines; COVID-19 Vaccines - therapeutic use; Humans; Immunization; infectious diseases; Intention; Pandemics; Population; Probability; Public Health; Self Report; Social Media; social medicine; Social networks; Social norms; Sociodemographics; statistics & research methods; Trends; United States - epidemiology; Vaccination; United States; United States > US; COVID-19; social medicine; statistics & research methods; public health; infectious diseases
• ISSN: 2044-6055; 2044-6055
• DOI: 10.1136/bmjopen-2022-066897

ObjectivesTo (1) understand what behaviours, beliefs, demographics and structural factors predict US adults’ intention to get a COVID-19 vaccination, (2) identify segments of the population (‘personas’) who share similar factors predicting vaccination intention, (3) create a ‘typing tool’ to predict which persona people belong to and (4) track changes in the distribution of personas over time and across the USA.DesignThree surveys: two on a probability-based household panel (NORC’s AmeriSpeak) and one on Facebook.SettingThe first two surveys were conducted in January 2021 and March 2021 when the COVID-19 vaccine had just been made available in the USA. The Facebook survey ran from May 2021 to February 2022.ParticipantsAll participants were aged 18+ and living in the USA.Outcome measuresIn our predictive model, the outcome variable was self-reported vaccination intention (0–10 scale). In our typing tool model, the outcome variable was the five personas identified by our clustering algorithm.ResultsOnly 1% of variation in vaccination intention was explained by demographics, with about 70% explained by psychobehavioural factors. We identified five personas with distinct psychobehavioural profiles: COVID Sceptics (believe at least two COVID-19 conspiracy theories), System Distrusters (believe people of their race/ethnicity do not receive fair healthcare treatment), Cost Anxious (concerns about time and finances), Watchful (prefer to wait and see) and Enthusiasts (want to get vaccinated as soon as possible). The distribution of personas varies at the state level. Over time, we saw an increase in the proportion of personas who are less willing to get vaccinated.ConclusionsPsychobehavioural segmentation allows us to identify why people are unvaccinated, not just who is unvaccinated. It can help practitioners tailor the right intervention to the right person at the right time to optimally influence behaviour.