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Cluster analysis of adults unvaccinated for COVID-19 based on behavioral and social factors, National Immunization Survey-Adult COVID Module, United States.

Authors :
Meng L
Masters NB
Lu PJ
Singleton JA
Kriss JL
Zhou T
Weiss D
Black CL
Source :
Preventive medicine [Prev Med] 2023 Feb; Vol. 167, pp. 107415. Date of Electronic Publication: 2022 Dec 31.
Publication Year :
2023

Abstract

By the end of 2021, approximately 15% of U.S. adults remained unvaccinated against COVID-19, and vaccination initiation rates had stagnated. We used unsupervised machine learning (K-means clustering) to identify clusters of unvaccinated respondents based on Behavioral and Social Drivers (BeSD) of COVID-19 vaccination and compared these clusters to vaccinated participants to better understand social/behavioral factors of non-vaccination. The National Immunization Survey Adult COVID Module collects data on U.S. adults from September 26-December 31,2021 (n = 187,756). Among all participants, 51.6% were male, with a mean age of 61 years, and the majority were non-Hispanic White (62.2%), followed by Hispanic (17.2%), Black (11.9%), and others (8.7%). K-means clustering procedure was used to classify unvaccinated participants into three clusters based on 9 survey BeSD items, including items assessing COVID-19 risk perception, social norms, vaccine confidence, and practical issues. Among unvaccinated adults (N = 23,397), 3 clusters were identified: the "Reachable" (23%), "Less reachable" (27%), and the "Least reachable" (50%). The least reachable cluster reported the lowest concern about COVID-19, mask-wearing behavior, perceived vaccine confidence, and were more likely to be male, non-Hispanic White, with no health conditions, from rural counties, have previously had COVID-19, and have not received a COVID-19 vaccine recommendation from a healthcare provider. This study identified, described, and compared the characteristics of the three unvaccinated subgroups. Public health practitioners, healthcare providers and community leaders can use these characteristics to better tailor messaging for each sub-population. Our findings may also help inform decisionmakers exploring possible policy interventions.<br />Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Published by Elsevier Inc.)

Details

Language :
English
ISSN :
1096-0260
Volume :
167
Database :
MEDLINE
Journal :
Preventive medicine
Publication Type :
Academic Journal
Accession number :
36596324
Full Text :
https://doi.org/10.1016/j.ypmed.2022.107415