Department of Communication, University at Buffalo, State University of New York, Buffalo, NY, USA.
Department of Communication, Georgia State University, Atlanta, GA, USA.
J Health Commun. 2021 Mar 4;26(3):161-173. doi: 10.1080/10810730.2021.1899344. Epub 2021 Mar 31.
Media framing of epidemics was found to influence public perceptions and behaviors in experiments, yet no research has been conducted on real-world behaviors during public health crises. We examined the relationship between Italian news media coverage of COVID-19 and compliance with stay-at-home orders, which could impact the spread of epidemics. We used a computational method for framing analysis (ANTMN) and combined it with Google's Community Mobility data. A time-series analysis using vector autoregressive models showed that the Italian media used media frames that were largely congruent with ones used by journalists in other countries: A focusing on symptoms and health effects, a focusing on attempts to ameliorate risks, and a , focusing on political and social impact. The prominence of different media frames over time was associated with changes in Italians' mobility patterns. Specifically, we found that the was associated with increased mobility, whereas the was associated with decreased mobility. The results demonstrate that the ways the news media discuss epidemics can influence changes in community mobility, above and beyond the effect of the number of deaths per day.
媒体对疫情的报道方式被发现会影响实验中的公众认知和行为，但在公共卫生危机期间，针对真实世界行为的研究尚未开展。我们研究了意大利新闻媒体对 COVID-19 的报道与遵守居家令之间的关系，这可能会影响疫情的传播。我们使用了一种用于框架分析的计算方法（ANTMN），并将其与谷歌的社区流动性数据相结合。使用向量自回归模型的时间序列分析表明，意大利媒体使用的媒体框架与其他国家记者使用的框架基本一致：一个框架侧重于症状和健康影响，一个框架侧重于试图减轻风险，一个框架侧重于政治和社会影响。不同媒体框架随时间的突出程度与意大利人流动性模式的变化有关。具体来说，我们发现，“症状和健康影响”框架与流动性增加有关，而“风险减轻”框架与流动性减少有关。研究结果表明，新闻媒体讨论疫情的方式会影响社区流动性的变化，这超出了每天死亡人数的影响。
