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孟祥伟, 吴群红, 郝艳华, 李乐, 张敏, 孟楠, 许峤. 风险信息特征对公众新型冠状病毒肺炎风险认知影响[J]. 中国公共卫生, 2022, 38(2): 190-193. DOI: 10.11847/zgggws1131466
引用本文: 孟祥伟, 吴群红, 郝艳华, 李乐, 张敏, 孟楠, 许峤. 风险信息特征对公众新型冠状病毒肺炎风险认知影响[J]. 中国公共卫生, 2022, 38(2): 190-193. DOI: 10.11847/zgggws1131466
MENG Xiang-wei, WU Qun-hong, HAO Yan-hua, . Impact of risk information characteristics on risk perception of COVID-19 among the Chinese public[J]. Chinese Journal of Public Health, 2022, 38(2): 190-193. DOI: 10.11847/zgggws1131466
Citation: MENG Xiang-wei, WU Qun-hong, HAO Yan-hua, . Impact of risk information characteristics on risk perception of COVID-19 among the Chinese public[J]. Chinese Journal of Public Health, 2022, 38(2): 190-193. DOI: 10.11847/zgggws1131466

风险信息特征对公众新型冠状病毒肺炎风险认知影响

Impact of risk information characteristics on risk perception of COVID-19 among the Chinese public

  • 摘要:
      目的  了解风险信息特征对公众新型冠状病毒肺炎(新冠肺炎)风险认知的影响,为改善传染病事件的信息发布提出有针对性的建议。
      方法  于2020年6月15 — 18日采用滚雪球抽样方法在黑龙江省、吉林省、辽宁省、湖北省和北京市5个省、市抽取1292名社会公众进行风险信息特征对新冠肺炎风险认知影响的网络问卷调查。
      结果  个人具有传染病的经历或经验、政府部门发布的信息、专家或学者发布的信息、传统媒体发布的信息、网络或社交媒体发布的信息、邻居或朋友传播的信息、信息发布前后不一致或矛盾、专家或学者的不同意见或争论、网络大V或明星等意见领袖的讨论或争议、疫情期间接触大量新冠肺炎信息、疫情期间较少接触其他类型信息、信息提及发生过的传染病(如重症急性呼吸综合征、流感)、信息提及其他国家暴发的类似传染病、信息提及新冠肺炎引出的现象或问题、信息中包含危害严重的文字/图片/视频和信息中包含着恐慌或悲哀情绪对公众新冠肺炎风险认知影响的得分分别为(3.37 ± 0.98)、(3.81 ± 1.21)、(3.61 ± 0.79)、(3.48 ± 1.13)、(3.52 ± 0.90)、(2.92 ± 0.95)、(4.36 ± 0.59)、(4.35 ± 0.61)、(3.74 ± 0.87)、(3.99 ± 0.94)、(3.75 ± 1.00)、(3.53 ± 1.05)、(3.57 ± 0.94)、(2.50 ± 1.08)、(3.36 ± 0.98)和(3.48 ± 1.13)分。因子分析共得到信息来源、信息争执、信息数量、信息关联和信息情感倾向5个公因子,累计方差贡献率为67.897 %,各公因子方差贡献率依次为17.334 %、13.638 %、13.221 %、13.111 % 和10.593 %。
      结论  新冠疫情期间影响公众风险认知的信息特征包括信息来源、信息争执、信息数量、信息关联和信息情感倾向,其中信息来源是影响公众风险认知的首要因素。

     

    Abstract:
      Objective   To examine the impact of risk information characteristics on the Chinese public's risk perception of coronavirus disease 2019 (COVID-19) and to put forward targeted suggestions for improving infectious disease epidemic information release.
      Methods  Using a self-designed questionnaire, we conducted an online anonymous survey among 1 446 Chinese internet users recruited with snowball sampling in five provincial-level regions of China from June 15 to 18, 2020.
      Results   Valid information were collected from 1 292 participants (43.0% males and 56.0% females) averagely aged 30.4 ± 9.3 years. Evaluated by a scale with the highest score of 5 for the greatest impact, the scores for the impact of characteristics of COVID-19 related information on participants' the epidemic risk perception were 3.37 ± 0.98 for personal experience associated with infectious disease, 3.81 ± 1.21/3.61 ± 0.79/3.48 ± 1.13/3.52 ± 0.90/2.92 ± 0.95 for obtaining information disseminated by government departments/experts or scholars/traditional media/internet or social media/neighbors or friends, 4.36 ± 0.59 for inconsistent or contradictory information, 4.35 ± 0.61 for different or controversial information from experts or scholars, 3.74 ± 0.87 for hearing about discussions or disputes among opinion leaders such as very important Microblog users or stars, 3.99 ± 0.94 for exposed to a great amount of information about COVID-19 during the epidemic, 3.75 ± 1.00 for rarely accessing to information other than COVID-19 epidemic, 3.53 ± 1.05 for obtaining information about previous infectious disease epidemic such as severe acute respiratory syndrome and influenza, 3.57 ± 0.94 for accessing information about outbreaks of other infectious diseases in foreign countries, 2.50 ± 1.08 for obtaining information on phenomenon or problems induced by the epidemic, 3.36 ± 0.98 for accessing text descriptions/photographs/videos on severe harms caused by the epidemic, and 3.48 ± 1.13 for accessing the information on panic or sadness induced by the epidemic among the public. The 5 common factors identified through factor analysis were source, dispute, quantity, association, and sentiment tendency of information accessed, with the corresponding variance contribution rate of 17.334%, 13.638%, 13.221%, 13.111%, and 10.593%, respectively, and a cumulative variance contribution rate of 67.897% for the 5 common factors.
      Conclusion  The source, dispute, quantity, association, and sentiment tendency are main characteristics of COVID-19-related information affecting the public′s disease risk perception and information source is a primary factor among the five information characteristics.

     

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