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Do COVID-19 Conspiracy Theory Beliefs Form a Monological Belief System?

Published online by Cambridge University Press:  21 May 2020

Joanne M. Miller*
Affiliation:
Political Science and International Relations, University of Delaware, 347 Smith Hall, 18 Amstel Ave., Newark, Delaware19716, USA
*
*Corresponding author. Email: jomiller@udel.edu
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Extract

Along with criticisms of the U.S. government's response to the COVID-19 pandemic, the disruptions to home, work, and school life resulting from social distancing orders recommended by public health experts, as well as the uncertainty about how long the disruptions will be necessary and when (if ever) we will have a vaccine, have come COVID-19 conspiracy theories (CTs).

Information

Type
Research Note/Notes de recherche
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © Canadian Political Science Association (l'Association canadienne de science politique) and/et la Société québécoise de science politique 2020
Figure 0

Table 1 COVID-19 conspiracy theories

Figure 1

Figure 1 Distribution of COVID-19 CT beliefs.

Figure 2

Figure 2 The unweighted percentages of people who endorse multiple CTs, combining the probably and definitely response options.

Figure 3

Table 2 Correlations between the conspiracy theories

Figure 4

Figure 3 The unstandardized regression coefficients from ordinary least squares models that include controls for age, education, income, gender, race, and ethnicity. The dots represent the coefficients and the lines represent the 95 per cent confidence intervals. See Appendix C, available online, for the full models.

Figure 5

Figure 4 Personal uncertainty moderating the effect of AccChina and BioChina on AccUS. Predicted values for the left panel are derived from Model 1 in online Appendix C. The interaction and the effects of AccChina at the lowest and highest quartiles of uncertainty are all statistically significant (b = .45, p < .001; b = .08, p = .05; and b = .33, p < .001, respectively). Predicted values for the right panel are derived from Model 2 in online Appendix C. The interaction and the effect of BioChina at the highest quartile of uncertainty are statistically significant (b = .39, p < .001; b = .31, p < .001). The effect of BioChina at the lowest quartile of uncertainty is not significant (b = .06, n.s.).

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