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Historical narratives about the COVID-19 pandemic are motivationally biased - Nature.com

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Abstract

How people recall the SARS-CoV-2 pandemic is likely to prove crucial in future societal debates on pandemic preparedness and appropriate political action. Beyond simple forgetting, previous research suggests that recall may be distorted by strong motivations and anchoring perceptions on the current situation1,2,3,4,5,6. Here, using 4 studies across 11 countries (total n = 10,776), we show that recall of perceived risk, trust in institutions and protective behaviours depended strongly on current evaluations. Although both vaccinated and unvaccinated individuals were affected by this bias, people who identified strongly with their vaccination status—whether vaccinated or unvaccinated—tended to exhibit greater and, notably, opposite distortions of recall. Biased recall was not reduced by providing information about common recall errors or small monetary incentives for accurate recall, but was partially reduced by high incentives. Thus, it seems that motivation and identity influence the direction in which the recall of the past is distorted. Biased recall was further related to the evaluation of past political action and future behavioural intent, including adhering to regulations during a future pandemic or punishing politicians and scientists. Together, the findings indicate that historical narratives about the COVID-19 pandemic are motivationally biased, sustain societal polarization and affect preparation for future pandemics. Consequently, future measures must look beyond immediate public-health implications to the longer-term consequences for societal cohesion and trust.

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Fig. 1: Biased recall of pandemic perceptions and behaviours in study 1.
Fig. 2: Effects of monetary incentives on reducing recall bias in study 3.
Fig. 3: Pandemic perceptions and behavioural intentions across countries in study 4.

Data availability

Data are available at https://doi.org/10.17605/OSF.IO/BXG7V. Study 2 (https://aspredicted.org/uw47f.pdf) and study 3 (https://aspredicted.org/kk33k.pdf) were preregistered.

Code availability

Data analysis scripts are available at https://doi.org/10.17605/OSF.IO/BXG7V.

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Acknowledgements

We thank J. Simmank and J. Schneider for discussions about the ex-post evaluation of the pandemic and for input for the items to assess the appropriateness of political action; S. Columbus, M. Müller and F. Zimmermann for comments and suggestions; and the COSMO teams at the University of Erfurt and the Bernhard Nocht Institute for Tropical Medicine for their continuous work, on which this paper builds. Financial support by the following institutions is acknowledged: Federal Centre for Health Education, Robert Koch Institute, Leibniz Institute of Psychology, Bernhard Nocht Institute for Tropical Medicine, Klaus Tschira Foundation, Thüringer Ministerium für Wirtschaft, Wissenschaft und digitale Gesellschaft, Thüringer Staatskanzlei, University of Erfurt and Deutsche Forschungsgemeinschaft (DFG; German Research Foundation). The project was partly funded by the DFG under Germany’s Excellence Strategy: EXC 2126/1–390838866. Support from the DFG through CRC TR 224 (project A01) is also acknowledged. C.B. was partly funded by the DFG (BE3970/12-1) and the Leibniz Foundation (P106/2020). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Authors and Affiliations

Authors

Contributions

All authors designed and performed the research. P.S. and L.H. performed the data analyses. All authors wrote and revised the manuscript.

Corresponding author

Correspondence to Philipp Sprengholz.

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The authors declare no competing interests.

Peer review

Peer review information

Nature thanks Dustin Calvillo and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Predictors of appropriateness of political action in study 1.

Results of a multiple linear regression with vaccination status and vaccination status identification predicting perceived appropriateness of political measures to contain the COVID-19 pandemic. Ribbons visualize 95% confidence intervals; R2 = 0.482.

Extended Data Fig. 2 Effects of interventions to reduce recall bias in study 2.

af, Linear regression predicting individual recall on the basis of past (December 2021) and present (January 2023) ratings and their interactions with vaccination status and experimental condition for infection probability (a), infection severity (b), trust in government (c), trust in science (d), mask wearing (e) and avoiding contacts (f) (n = 3,105). Each line visualizes directional bias and how past and present perceptions affect recall (at recall = 4) for a given vaccination status and experimental condition (see the Fig. 1 legend for details on how to read the figure).

Extended Data Table 1 Recall in study 1
Extended Data Table 2 Prediction of population estimates in study 1
Extended Data Table 3 Recall in study 2
Extended Data Table 4 Recall in study 3
Extended Data Table 5 Mixed-effects regression of recall in study 3
Extended Data Table 6 Recall of participation time in study 3
Extended Data Table 7 Biases in population estimates and their correlation with appropriateness of political action ratings in study 4
Extended Data Table 8 Correlates of appropriateness of political action ratings in study 4
Extended Data Table 9 Predictors of appropriateness of political action in study 4

Supplementary information

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Sprengholz, P., Henkel, L., Böhm, R. et al. Historical narratives about the COVID-19 pandemic are motivationally biased. Nature (2023). https://ift.tt/LGupYl6

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