Predicting willingness to be vaccinated for Covid-19: Evidence from New Zealand

Governments around the world are seeking to slow the spread of Covid-19 and reduce hospitalisations by encouraging mass vaccinations for Covid-19. The success of this policy depends on most of the population accepting the vaccine and then being vaccinated. Understanding and predicting the motivation...

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Bibliographic Details
Published in:PloS one 2022-04, Vol.17 (4), p.e0266485
Main Authors: Kaine, Geoff, Wright, Vic, Greenhalgh, Suzie
Format: Article
Language:English
Subjects:
Analysis
Attitudes
Biology and Life Sciences
Computer and Information Sciences
COVID-19
COVID-19 - epidemiology
COVID-19 - prevention & control
COVID-19 vaccines
COVID-19 Vaccines - therapeutic use
Decision making
Health behavior
Humans
Immunization
Mass Vaccination
Medicine and Health Sciences
Motivation
New Zealand - epidemiology
People and places
SARS-CoV-2
Social Sciences
Vaccination
Vaccines
Viruses
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Summary:Governments around the world are seeking to slow the spread of Covid-19 and reduce hospitalisations by encouraging mass vaccinations for Covid-19. The success of this policy depends on most of the population accepting the vaccine and then being vaccinated. Understanding and predicting the motivation of individuals to be vaccinated is, therefore, critical in assessing the likely effectiveness of a mass vaccination programme in slowing the spread of the virus. In this paper we draw on the I3 Response Framework to understand and predict the willingness of New Zealanders to be vaccinated for Covid-19. The Framework differs from most studies predicting willingness to be vaccinated because it is based on the idea that the willingness to adopt a behaviour depends on both involvement (a measure of motivational strength) with the behaviour and attitudes towards the behaviour. We show that predictions of individuals' willingness to be vaccinated are improved using involvement and attitudes together, compared to attitudes alone. This result has important implications for the implementation of mass vaccination programmes for Covid-19.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0266485