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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.
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.
  • Charles GK; Surgo Ventures, Washington, DC, USA.
  • Braunstein SP; Green River, Brattleboro, Vermont, USA.
  • Barker JL; Surgo Ventures, Washington, DC, USA.
  • Fung H; Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.
  • Coome L; Surgo Ventures, Washington, DC, USA.
  • Kumar R; Interacting Minds Centre, Aarhus University, Aarhus, Denmark.
  • Huang VS; Surgo Health, Washington, DC, USA.
  • Kemp H; Surgo Ventures, Washington, DC, USA.
  • Grant E; Surgo Health, Washington, DC, USA.
  • Bernard D; Surgo Ventures, Washington, DC, USA.
  • Barefoot D; Surgo Ventures, Washington, DC, USA.
  • Sgaier SK; Surgo Ventures, Washington, DC, USA.
BMJ Open ; 13(6): e066897, 2023 06 06.
Article in English | MEDLINE | ID: covidwho-20233982
ABSTRACT

OBJECTIVES:

To (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.

DESIGN:

Three surveys two on a probability-based household panel (NORC's AmeriSpeak) and one on Facebook.

SETTING:

The 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.

PARTICIPANTS:

All participants were aged 18+ and living in the USA. OUTCOME

MEASURES:

In 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.

RESULTS:

Only 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.

CONCLUSIONS:

Psychobehavioural 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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Media / COVID-19 Type of study: Observational study / Prognostic study Topics: Vaccines Limits: Adult / Humans Country/Region as subject: North America Language: English Journal: BMJ Open Year: 2023 Document Type: Article Affiliation country: Bmjopen-2022-066897

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Media / COVID-19 Type of study: Observational study / Prognostic study Topics: Vaccines Limits: Adult / Humans Country/Region as subject: North America Language: English Journal: BMJ Open Year: 2023 Document Type: Article Affiliation country: Bmjopen-2022-066897