Health-related fake news during the COVID-19 pandemic: perceived trust and information search
研究利用保护行动决策模型，分析美国和中国互联网用户在新冠疫情期间对健康类假新闻的信任与搜索行为，发现疫情严重程度与假新闻搜索行为存在负向滞后关系，且信任起中介作用。
Purpose Health-related online fake news (HOFN) has become a major social problem. HOFN can lead to the spread of ineffective and even harmful remedies. The study aims to understand Internet users' responses to HOFN during the coronavirus (COVID-19) pandemic using the protective action decision model (PADM). Design/methodology/approach The authors collected pandemic severity data (regional number of confirmed cases) from government websites of the USA and China (Studies 1 and 2), search behavior from Google and Baidu search engines (Studies 1 and 2) and data regarding trust in two online fake news stories from two national surveys (Studies 2 and 3). All data were analyzed using a multi-level linear model. Findings The research detected negative time-lagged relationships between pandemic severity and regional HOFN search behavior by three actual fake news stories from the USA and China (Study 1). Importantly, trust in HOFN served as a mediator in the time-lagged relationship between pandemic severity and search behavior (Study 2). Additionally, the relationship between pandemic severity and trust in HOFN varied according to individuals' perceived control (Study 3). Originality/value The authors' results underscore the important role of PADM in understanding Internet users' trust in and search for HOFN. When people trust HOFN, they may seek more information to implement further protective actions. Importantly, it appears that trust in HOFN varies with environmental cues (regional pandemic severity) and with individuals' perceived control, providing insight into developing coping strategies during a pandemic.