Systematic Literature Review on the Spread of Health-related Misinformation on Social Media

Abstract

Contemporary commentators describe the current period as "an era of fake news" in which misinformation, generated intentionally or unintentionally, spreads rapidly. Although affecting all areas of life, it poses particular problems in the health arena, where it can delay or prevent effective care, in some cases threatening the lives of individuals. While examples of the rapid spread of misinformation date back to the earliest days of scientific medicine, the internet, by allowing instantaneous communication and powerful amplification has brought about a quantum change. In democracies where ideas compete in the marketplace for attention, accurate scientific information, which may be difficult to comprehend and even dull, is easily crowded out by sensationalized news. In order to uncover the current evidence and better understand the mechanism of misinformation spread, we report a systematic review of the nature and potential drivers of health-related misinformation. We searched PubMed, Cochrane, Web of Science, Scopus and Google databases to identify relevant methodological and empirical articles published between 2012 and 2018. A total of 57 articles were included for full-text analysis. Overall, we observe an increasing trend in published articles on health-related misinformation and the role of social media in its propagation. The most extensively studied topics involving misinformation relate to vaccination, Ebola and Zika Virus, although others, such as nutrition, cancer, fluoridation of water and smoking also featured. Studies adopted theoretical frameworks from psychology and network science, while co-citation analysis revealed potential for greater collaboration across fields. Most studies employed content analysis, social network analysis or experiments, drawing on disparate disciplinary paradigms. Future research should examine susceptibility of different sociodemographic groups to misinformation and understand the role of belief systems on the intention to spread misinformation. Further interdisciplinary research is also warranted to identify effective and tailored interventions to counter the spread of health-related misinformation online.

Keywords: Fake news; Health; Misinformation; Social media.

Fig. 1

PRISMA flow diagram.

Fig. 2

Numbers of potentially eligible articles.

Fig. 3

Topic categories.

Fig. 4

Co-citation analysis. We extracted citation data from Scopus and analysed citation patterns using network-clustering algorithms in VOSviewer 1.6.8. The network map shows co-citation patterns of 121 journals cited at least 5 times within the studies that are potentially eligible. The node size represents the number of citations, and the lines represent the presence of citation in either direction. We restricted the minimum cluster size to 20, which resulted in 4 disciplinary clusters and 2367 links. We were not able to identify 10 articles because they were not indexed on Scopus, we therefore exclude them for the co-citation analysis.