Public Risk Perception Attribution Model and Governance Path in COVID-19: A Perspective Based on Risk Information
Risk Management and Healthcare Policy, ISSN: 1179-1594, Vol: 15, Page: 2097-2113
2022
- 3Citations
- 90Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Background: Risk perception is a key factor influencing the public’s behavioral response to major public health events. The research on public risk perception promotes the emergency management system to adapt to the needs of modern development. This article is based on a risk information perspective, using the COVID-19 event as an example. From the micro and macro perspectives, the influencing factors of public risk perception in major public health events in China are extracted, and the attribution model and index system of public risk perception are established. Methods: In this paper, the five-level Likert scale is used to collect and measure the risk perception variable questionnaire through the combination of online and offline methods (a total of 550 questionnaires, the overall Alpha coefficient of the questionnaire is 0.955, and the KMO test coefficient t=0.941), and through independent samples t-test, correlation analysis, multiple regression analysis and other methods to draw relevant conclusions. Results: The results showed that gender and age were significantly associated with risk perception (p<0.005), and education level was significantly negatively associated with risk perception (p <0 0.005). Risk information attention and risk perception were significantly positively correlated (p<0.005), media credibility was significantly positively correlated with risk perception (p<0.005), while risk information identification and media exposure had no significant interaction with risk perception (p=0.125, p=0.352). Conclusion: Factors such as gender, age, education level, place of residence, media exposure, media credibility, risk information attention, and recognition lead to different levels of risk perception. This conclusion helps to provide a basis for relevant departments to conduct public risk management of major public health events based on differences in risk perceptions.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85141420593&origin=inward; http://dx.doi.org/10.2147/rmhp.s379426; http://www.ncbi.nlm.nih.gov/pubmed/36386558; https://www.dovepress.com/public-risk-perception-attribution-model-and-governance-path-in-covid--peer-reviewed-fulltext-article-RMHP; https://dx.doi.org/10.2147/rmhp.s379426
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