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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

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 predi...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10255149/
https://www.ncbi.nlm.nih.gov/pubmed/37280023
http://dx.doi.org/10.1136/bmjopen-2022-066897
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author 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
author_facet 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
author_sort Charles, Grace K
collection PubMed
description 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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spelling pubmed-102551492023-06-10 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 BMJ Open Public Health 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. BMJ Publishing Group 2023-06-06 /pmc/articles/PMC10255149/ /pubmed/37280023 http://dx.doi.org/10.1136/bmjopen-2022-066897 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Public Health
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
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10255149/
https://www.ncbi.nlm.nih.gov/pubmed/37280023
http://dx.doi.org/10.1136/bmjopen-2022-066897
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