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How the Health Rumor Misleads People’s Perception in a Public Health Emergency: Lessons from a Purchase Craze during the COVID-19 Outbreak in China

Author

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  • Liwei Zhang

    (School of Public Administration, Jilin University, Changchun 130012, China)

  • Kelin Chen

    (Institute of Urban Governance, Shenzhen University, Shenzhen 518060, China)

  • He Jiang

    (Department of Social Psychology, Nankai University, Tianjin 300350, China)

  • Ji Zhao

    (School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai 200030, China)

Abstract

Health rumors often mislead people and cause adverse health behaviors. Especially during a public health emergency, health rumors may result in severe consequences for people’s health and risk governance. Insight into how these rumors form and harm people’s health behavior is critical for assisting people in establishing scientific health cognition and to enhance public health emergency responses. Using the case study with interview data of a salient purchase craze led by a health rumor during the COVID-19 outbreak in China, this article aimed to illustrate the process of how a piece of information becomes a health rumor. Furthermore, we identify factors that cause people to believe rumors and conduct behavior that leads to a purchase craze. Results show that a public misunderstanding of the unique psychology of uncertainty, cultural and social cognition, and conformity behavior jointly informs people’s beliefs in rumors and further causes purchase craze behavior. We developed a simplified model to demonstrate how an ordinary news report can lead to a rumor. Based on this model, some implications of effective health communication are suggested for managing rumors.

Suggested Citation

  • Liwei Zhang & Kelin Chen & He Jiang & Ji Zhao, 2020. "How the Health Rumor Misleads People’s Perception in a Public Health Emergency: Lessons from a Purchase Craze during the COVID-19 Outbreak in China," IJERPH, MDPI, vol. 17(19), pages 1-15, October.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:19:p:7213-:d:422929
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    References listed on IDEAS

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    1. Kaler, Amy, 2009. "Health interventions and the persistence of rumour: The circulation of sterility stories in African public health campaigns," Social Science & Medicine, Elsevier, vol. 68(9), pages 1711-1719, May.
    2. Galam, Serge, 2003. "Modelling rumors: the no plane Pentagon French hoax case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 320(C), pages 571-580.
    3. Stanley K.K. Lam & Enid W.Y. Kwong & Maria S.Y. Hung & Wai-tong Chien, 2020. "Investigating the Strategies Adopted by Emergency Nurses to Address Uncertainty and Change in the Event of Emerging Infectious Diseases: A Grounded Theory Study," IJERPH, MDPI, vol. 17(7), pages 1-13, April.
    4. Viju Raghupathi & Jie Ren & Wullianallur Raghupathi, 2020. "Studying Public Perception about Vaccination: A Sentiment Analysis of Tweets," IJERPH, MDPI, vol. 17(10), pages 1-23, May.
    5. Åsa Boholm, 2019. "Risk Communication as Government Agency Organizational Practice," Risk Analysis, John Wiley & Sons, vol. 39(8), pages 1695-1707, August.
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    Cited by:

    1. Kai Li & Jie Li & Fen Zhou, 2022. "The Effects of Personality Traits on Online Rumor Sharing: The Mediating Role of Fear of COVID-19," IJERPH, MDPI, vol. 19(10), pages 1-13, May.
    2. Tinggui Chen & Yumei Jin & Bing Wang & Jianjun Yang, 2024. "The government intervention effects on panic buying behavior based on online comment data mining: a case study of COVID-19 in Hubei Province, China," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-20, December.
    3. Carlos de las Heras-Pedrosa & Carmen Jambrino-Maldonado & Dolores Rando-Cueto & Patricia P. Iglesias-Sánchez, 2022. "COVID-19 Study on Scientific Articles in Health Communication: A Science Mapping Analysis in Web of Science," IJERPH, MDPI, vol. 19(3), pages 1-29, February.
    4. Fredy S. Monge-Rodríguez & He Jiang & Liwei Zhang & Andy Alvarado-Yepez & Anahí Cardona-Rivero & Enma Huaman-Chulluncuy & Analy Torres-Mejía, 2021. "Psychological Factors Affecting Risk Perception of COVID-19: Evidence from Peru and China," IJERPH, MDPI, vol. 18(12), pages 1-16, June.

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