Uncertainty Stress, and Its Impact on Disease Fear and Prevention Behavior during the COVID-19 Epidemic in China: A Panel Study

  1. Sihui Peng
  2. Xiaozhao Yousef Yang
  3. Tingzhong Yang
  4. Weifang Zhang
  5. Randall R. Cottrell

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Abstract

Objectives: We examined changing trends of uncertainty stress, and its impact on disease fear and prevention behaviors during the Chinese COVID-19 epidemic, using a prospective observational study. Methods: We employed a longitudinal design. We recruited participants for an online panel survey from chat groups on social media platforms. There were 5 waves of interviews. Information on uncertainty stress and related variables were collected via the online survey. Descriptive statistics and the GIM program were used for data analysis. Results: Participants numbered 150 for the linkable baseline survey and 102 (68%) for the final survey. Uncertainty stress (β = -.047, SE = .118, p > .05) did not show a statistically significant temporal change trend over the observation period. Disease fear manifested a statistically significant downwards trend (β = -.342, SE = .157, p < .05), and prevention behaviors indicated an upwards trend (β = .048, SE = .021, p < .05) during the observation period. Uncertainty stress was positively associated with disease fear (β = .45046, SE = .05964, p < .001), and negatively associated with self-efficacy (β = -.6698, SE = .01035, p < .001), and prevention behaviors (β = -.02029, SE = .00876, p =.021). Conclusion: This study yielded new information about uncertainty stress among Chinese people during the COVID-19 epidemic. Policy changes and public education are essential for minimizing the negative effects of uncertainty stress in disease prevention.

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  1. Version published to 10.5993/ajhb.45.2.12
  2. ScreenIT

    SciScore for 10.1101/2020.06.24.20139626: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by the ethics committee of Zhejiang University.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data analysis: All data were entered into a database using Microsoft Excel.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    The GIM program was used to conduct repeated measures analysis of variance to determine changing trends across the five observation points, and to examine the association between uncertainty stress and the disease fear, self efficacy, and the prevention behavior using the Armitage linear test (SAS Institute Inc, 2011).
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.06.24.20139626v1 on medRxiv