Effectiveness of digital health interventions against COVID-19 misinformation: a systematic realist review of intervention trials

Misinformation is a growing concern worldwide, particularly in public health following the COVID-19 pandemic in which misinformation has been attributed to tens of thousands of unnecessary deaths. Therefore a search for effective interventions against misinformation is underway, with widely varying proposed interventions, measures of efficacy, and groups targeted for intervention. This realist systematic review of proposed interventions against COVID-19 misinformation assesses the studies themselves, the characteristics and effectiveness of the interventions proposed, the durability of effect, and the circumstances and contexts within which these interventions function. We searched several databases for studies testing interventions published from 2020 onwards. The search results were sorted by eligibility, with eligible studies then being coded by themes and assessed for quality. Twenty-six studies were included, representing eight types of intervention. The results are promising to the advantages of game-type interventions, with other types scoring poorly on either scalability or impact. Backfire effects and effects on subgroups were reported on intermittently in the included studies, showing the advantages of certain interventions for subgroups or contexts. No one intervention appears sufficient by itself, therefore this study recommends the creation of packages of interventions by policymakers, who can tailor the package for contexts and targeted groups. There was high heterogeneity in outcome measures and methods, making comparisons between studies difficult; this should be a focus in future studies. Additionally, the theoretical and intervention literatures need connecting for greater understanding of the mechanisms at work in the interventions. Lastly, there is a need for work more explicitly addressing political polarisation and its role in the belief and spread of misinformation. This study contributes toward the expansion of realist review approaches, understandings of COVID-19 misinformation interventions, and broader debates around the nature of politicisation in contemporary misinformation. Author SummaryMisinformation is increasingly seen as a danger to public health and society at large. In the case of COVID-19, it is associated with high levels of unnecessary death among the public. There have been many interventions proposed to counter misinformation, yet little taking a meta-analytical perspective. These interventions vary greatly and are not measured for effect in the same ways, making traditional comparisons difficult. Instead, we categorised the interventions by type and assessed them by impact, scalability, durability, and which groups of people and contexts in which they best work. With this information for each type of intervention, policymakers can then make packages of multiple interventions that best work in their circumstances. Although game-type interventions stood out from the rest, no one intervention seems capable of effectively countering misinformation by itself. Many interventions were found to work differently on different groups of people, which reaffirms suggestions by some authors that political ideology is relevant to how people respond to these interventions. In future research there is a need to more deeply investigate the role of politicisation in misinformation and interventions against it, as well as bringing in more theory to understand how these interventions function.