“A wise man is never confused”: reasoning ability and anxiety in COVID-19 pandemic

ABSTRACT

This paper investigates the impact of reasoning ability on anxiety through an information intervention experiment. Our analysis reveals that conflicting information can elevate anxiety, whereas stronger reasoning ability can help people alleviate anxiety. When individuals encounter information with diverging opinions about COVID-19, stronger reasoning ability enables them to accurately comprehend the information, update their beliefs, and generate distinct emotional responses compared to those who lack reasoning skills. Information is a double-edged sword, and the discrepancies in individuals’ reasoning abilities should be taken into account in the dissemination of information and the implementation of public policies.

KEYWORDS:

• Reasoning ability
• anxiety
• information intervention
• belief

JEL CLASSIFICATION:

• D83
• D91
• I12
• I18

Acknowledgements

The authors acknowledge the financial support from National Social Science Foundation of China (Grant numbers: 20&ZD057), National Natural Science Foundation of China (Grant numbers: 71873076), Shandong Province Higher Education Youth Innovation Technology Plan (Grant numbers: 2019RWE005), Natural Science Foundation of Shandong Province (Grant numbers: ZR2021MG024), and Taishan Scholar Foundation of Shandong Province (Grant numbers: tsqn20213022).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/13504851.2024.2334445

Notes

¹ ‘A wise man is never confused’ is quoted from the Analects that collects the ideas of the ancient philosopher Confucius.

² Data description is shown in Appendix B.

³ Equation (1)(1) $\mathit{anxiet}{y}_i={\theta }_0+{\theta }_1\mathit{R}{A}_i+{\theta }_3{X}_i+{\nu }_i+{\lambda }_i+{\epsilon }_i$(1) is the model for OLS and Equation (2)(2) $\mathit{anxiet}{y}_i={\gamma }_1+{\eta }_1\mathit{R}{A}_i+{\eta }_2{X}_i+{\mu }_1$(2) to (5) are the model for mediation analysis.

⁴ The results by Bootstrap are shown in the appendix Table C2 which is consistent with Table 2.

Additional information

Funding

The work was supported by the National Natural Science Foundation of China [71873076]; National Social Science Fund of China [20&ZD057]; Natural Science Foundation of Shandong Province [ZR2021MG024]; Shandong Province Higher Education Youth Innovation Technology Plan [2019RWE005]; Taishan Scholar Foundation of Shandong Province [tsqn20213022].