Qu Yan, Saffer Adam J, Austin Lucinda
Hubbard School of Journalism and Mass Communication, University of Minnesota.
Hussman School of Journalism and Media, University of North Carolina.
Health Commun. 2023 Feb;38(2):216-227. doi: 10.1080/10410236.2021.1944457. Epub 2021 Jun 30.
The pervasive of COVID-19 information has driven some to escape daily conversations or media coverage. A rich set of theoretical discussions and empirical studies help explain why individuals avoid health risk information, but few studies have explored social network antecedents to information avoidance. This study investigates how personal discussion networks about COVID-19 shape individuals' information avoidance behaviors. Using a nationally representative sample ( = 1,304), we examined the effects of network size, heterogeneity, ego-alter dissimilarity, and social norms. Our results suggest that the four network variables had varying effects on different forms of information avoidance. Notably, social norms significantly predicted individuals' information avoidance. The theoretical and methodological implications of our findings are discussed.
新冠疫情信息的广泛传播使得一些人回避日常对话或媒体报道。一系列丰富的理论探讨和实证研究有助于解释个人为何回避健康风险信息，但很少有研究探究信息回避的社交网络 antecedents。本研究调查了关于新冠疫情的个人讨论网络如何塑造个体的信息回避行为。我们使用具有全国代表性的样本（n = 1304），考察了网络规模、异质性、自我与他人差异以及社会规范的影响。我们的结果表明，这四个网络变量对不同形式的信息回避有不同影响。值得注意的是，社会规范显著预测了个体的信息回避。我们讨论了研究结果的理论和方法学意义。
原文中“antecedents”未翻译完整，推测可能是“antecedents of information avoidance”（信息回避的前因），但按照要求未添加解释，直接保留了未完整翻译的状态。
