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Who Thinks COVID-19 is not a Crisis? Need for Cognition and Political Ideology Influence Perceptions of the Severity of COVID-19

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  • Meerza, Syed Imran Ali
  • Brooks, Kathleen R.
  • Gustafson, Christopher R.

    (University of Nebraska-Lincoln)

  • Yiannaka, Amalia

Abstract

The main objective of this study is to identify the role of the need for cognition (NFC) and political ideology in shaping perceptions of the severity of the COVID-19 pandemic using survey data collected from 1,223 individuals in the United States. Our results suggest that participants with a high NFC are more likely to perceive COVID-19 as a crisis than respondents with a low NFC. Moreover, empirical results indicate that conservatism is related to perceiving the COVID-19 pandemic as less severe. Specifically, individuals on the ‘right’ of the political spectrum (i.e., conservative) were less likely to perceive the COVID-19 pandemic as a crisis than individuals on the ‘left’ of the political spectrum (i.e., liberal). Overall, study findings show the psychological and political roots of individual differences in perceptions of the severity of the pandemic.

Suggested Citation

  • Meerza, Syed Imran Ali & Brooks, Kathleen R. & Gustafson, Christopher R. & Yiannaka, Amalia, 2023. "Who Thinks COVID-19 is not a Crisis? Need for Cognition and Political Ideology Influence Perceptions of the Severity of COVID-19," OSF Preprints 5xvaz, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:5xvaz
    DOI: 10.31219/osf.io/5xvaz
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    References listed on IDEAS

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    1. Arthur E. Attema & Han Bleichrodt & Olivier L'Haridon, 2018. "Ambiguity preferences for health," Health Economics, John Wiley & Sons, Ltd., vol. 27(11), pages 1699-1716, November.
    2. John M. Barrios & Yael Hochberg, 2020. "Risk Perception Through the Lens of Politics in the Time of the COVID-19 Pandemic," NBER Working Papers 27008, National Bureau of Economic Research, Inc.
    3. Nicholas Francis Havey, 2020. "Partisan public health: how does political ideology influence support for COVID-19 related misinformation?," Journal of Computational Social Science, Springer, vol. 3(2), pages 319-342, November.
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