What Causes Health Information Avoidance Behavior under Normalized COVID-19 Pandemic? A Research from Fuzzy Set Qualitative Comparative Analysis

• Published in: Healthcare (Basel) Vol. 10; no. 8; p. 1381
• Main Authors: Ding, Qingxiu, Gu, Yadi, Zhang, Gongrang, Li, Xingguo, Zhao, Qin, Gu, Dongxiao, Yang, Xuejie, Wang, Xiaoyu
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 25.07.2022; MDPI
• Subjects: Access to information; Avoidance behavior; Coronaviruses; COVID-19; Emotions; Epidemics; Forecasts and trends; Health behavior; Influence; Medical advice systems; Public opinion; China; health information; fuzzy-set qualitative comparative analysis; normalized COVID-19 pandemic; information avoidance behavior
• ISSN: 2227-9032; 2227-9032
• DOI: 10.3390/healthcare10081381

Affected by the normalization of the COVID-19 pandemic, people’s lives are subject to many restrictions, and they are under enormous psychological and physical pressure. In this situation, health information may be a burden and cause of anxiety for people; thus, the refusal of health information occurs frequently. Health-information-avoidance behavior has produced potential impacts and harms on people’s lives. Based on more than 120,000 words of textual data obtained from semi-structured interviews, summarizing a case collection of 55 events, this paper explores the factors and how they combine to lead to avoidance of health information. First, the influencing factors are constructed according to the existing research, and then the fuzzy set qualitative comparative analysis (fsQCA) method is used to discover the configuration relationship of health-information-avoidance behavior. The results show that the occurrence of health-information avoidance is not the result of a single factor but the result of a configuration of health-information literacy, negative emotions, perceived information, health-information presentation, cross-platform distribution, and the network information environment. These findings provide inspiration for reducing the adverse consequences of avoiding health information and improving the construction of health-information service systems.