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Public Trust During a Public Health Crisis: Evaluating the Immediate Effects of the Pandemic on Institutional Trust

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Abstract

Institutional trust is pivotal in facilitating targeted policy implementation and fostering appropriate preventative behavior amid public health crises. This study examines the immediate effects of the pandemic on institutional trust, investigating whether public trust in responding institutions underwent substantial changes pre and post the early outbreak of the pandemic. Leveraging data from two large-scale online surveys administered before and after the outbreak of the pandemic, our findings highlight a marked erosion of public trust toward the government in the aftermath of the outbreak. This effect is more pronounced at the local government level compared to the central government. Conversely, there was a significant increase in trust in medical institutions. Additionally, shifts in public trust in the government were found to be closely tied to evaluations of the government’s pandemic-handling measures, with this relationship moderated by diverse media consumption.

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Notes

  1. In the existing literature, political trust in China mainly refers to people’s trust in central and local government (e.g., [25, 67]). In public health crises, however, the government is not the only responding institution, as medical institutions are also crucial agencies. Therefore, in the analysis of COVID-19 influence, it is reasonable to consider public trust not only in governments but also in medical institutions (hospitals). In order to differentiate it from political trust traditionally defined in the existing literature, this article uses the concept of “institutional trust” to refer to public trust in governments and hospitals.

  2. for a review article, see [13].

  3. For more details, please refer to the social media article in Bingdian Weekly titled “Commentary: Why Was Pandemic Reporting at Early Stage in Wuhan Interrupted?”. The article can be accessed via the following link: https://mp.weixin.qq.com/s/69pdSrjNH_4qN3RrQ-Yk0Q.

  4. For more information, please refer to the China Newsweek report titled “Why Did Director GAO Fu’s China CDC Suffer an Institutional Trust Crisis?” published on March 2, 2020. The report can be accessed through the following link: https://www.sohu.com/a/376158102_220095.

  5. Please refer to details of the report on caixin.com, “Tracing Genome Sequencing of the Novel Coronavirus: When Was the Alarm Sounded?” Feb. 27, 2020. please refer to http://fm.caixin.com/m/2020-02-27/101521256.html.

  6. For a detailed analysis of officials’ blame shifting, please refer to https://news.tianyancha.com/ll_285lyoq7th.html.

  7. This data was collected from December 31, 2019 to January 31, 2020. For a detailed introduction to this project, see [19].

  8. This survey took some steps to ensure data quality. First, each user was only able to answer the survey one time. Second, data from users who took less than seven minutes to complete the survey were deleted, with the assumption that they were not taking the questions seriously. Last, responses were also deleted from those who did not carefully answer the questions and had high proportions of missing data.

  9. On January 20, 2020, the academic Nanshan Zhong confirmed human-to-human transmission of COVID-19 in a CCTV interview, drawing public attention. Media reports soared following this report. Soon after, Wuhan was locked down, bringing public attention and media reports to a new peak. Therefore, by late January, COVID-19 had already become a public health emergency that captured the attention of Chinese society and the world.

  10. When pooling the two rounds of the survey, we applied unified coding rules to all relevant variables to make them comparable.

  11. We divided respondents into nine distinct age groups, labeled from 1 to 9, which are as follows: 18–24, 25–29, 30–34, …, and 60 years old and above.

  12. Regarding education level, we grouped respondents based on their highest level of education attained. The categories are: “junior high school or lower,” “senior high school,” “two-year college and undergraduate,” or “master’s or doctoral degree.”

  13. For annual family income, we broke it down into the subsequent categories: “below 50,000 yuan,” “50,000–100,000 yuan,” “100,001–200,000 yuan,” “200,001–400,000 yuan,” and “400,001 yuan and above.”

  14. It is important to note that, in absolute terms, the adjusted score of 4.09 on a 1–5 scale still reflects a relatively high level of trust in the central government among the Chinese public. This is consistent with a longstanding pattern where trust in China’s central government has typically been higher than that in other countries (e.g., [79]). However, within the short-term context of this study, the significant decline observed is notable, especially considering the concurrent substantial decrease in trust in local government.

  15. This study mainly used ordinary least squares models for estimation. Thus, we could directly calculate the marginal effects from the coefficients. We also used ordered probit models for similar analyses, which found no significant changes in the core independent variables and most independent variables.

  16. In comparative terms, while the drop in trust in the central government is statistically significant, the actual reduction is relatively small. And importantly, we further highlight that the erosion of trust was more severe for local government compared to the central government.

  17. For a more detailed methodological introduction, see [22].

  18. There might potentially exist an endogeneity issue wherein the trust in government could reciprocally influence the attitudes towards the pandemic. The constraints of our current research methodology arise from the absence of spatial data about the sample, preventing us from using instrumental variables such as the number of infections in a respondent’s region to mirror their attitude towards the pandemic. This methodological limitation hinders us from capturing a more comprehensive and nuanced understanding of this complex interaction. Moving forward, we intend to refine our approach in subsequent research to delve deeper into and better understand this intricate and critical relationship.

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  1. School of Public Affairs, Xiamen University, Xiamen, 361005, China

    Yu You

  2. School of Government, Shenzhen University, Shenzhen, 518060, China

    Deyong Ma

  3. School of International and Public Affairs, Institute of Political Economy, Shanghai Research Centre for Innovation Policy Evaluation, Shanghai Jiao Tong University, Shanghai, 200020, China

    Chao Chen

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You, Y., Ma, D. & Chen, C. Public Trust During a Public Health Crisis: Evaluating the Immediate Effects of the Pandemic on Institutional Trust. J OF CHIN POLIT SCI 29, 1–29 (2024). https://doi.org/10.1007/s11366-023-09874-y

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