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Psychological predictors of COVID-19 vaccination in New Zealand

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dcterms:created language:enDate created language:enDate Created

2022-04-25

dcterms:dateAccepted language:enDate Accepted language:enDate accepted

2022-08-01

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2022

dcterms:dateSubmitted language:enDate Submitted language:enDate submitted

2022-04-25

dcterms:description language:enDescription

Is it possible to predict COVID-19 vaccination status prior to the existence and availability of COVID-19 vaccines? Here, we present a logistic model by regressing decisions to vaccinate in late 2021 on lagged sociodemographic, health, social, and political indicators from 2019 in a sample of New Zealand adults aged between 18 and 94 (Mage = 52.92, SD = 14.10; 62.21% women; N = 5324). We explain 31% of the variance in decision making across New Zealand. Significant predictors of being unvaccinated were being younger, more deprived, reporting less satisfaction with general practitioners, lower levels of neuroticism, greater levels of subjective health and meaning in life, higher distrust in science and in the police, lower satisfaction in the government, as well as political conservatism. Additional cross-sectional models specified using the same, and additional COVID-19-specific factors are also presented. These findings reveal that vaccination decisions are neither artefacts of context nor chance, but rather can be predicted in advance of the availability of vaccines.

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Psychological predictors of COVID-19 vaccination in New Zealand

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Aotearoa New Zealand

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vaccination

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Danny Osborne

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dcterms:identifier language:enIdentifier: https://orcid.org/0000-0002-8513-4125
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foaf:name name language:enName: Danny Osborne
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Carol Lee

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foaf:name language:enName name: Carol Lee

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dcterms:description language:enDescription: The data described in the paper are part of the New Zealand Attitudes and Values Study (NZAVS). Full copies of the NZAVS data files are held by all members of the NZAVS management team and advisory board. A de-identified dataset containing the variables analyzed in this manuscript is available upon request from the corresponding author, or any member of the NZAVS advisory board for the purposes of replication or checking of any published study using NZAVS data. The Mplus syntax used to test all models reported in this manuscript are available on the Open Science Framework.
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