Measuring the burden of infodemics with a research toolkit for connecting information exposure, trust, and health behaviours

Abstract

Abstract Background During a public health emergency, accurate and useful information can be drowned out by questions, concerns, information voids, conflicting information, and misinformation. Very few studies connect information exposure and trust to health behaviours, which limits available evidence to inform when and where to act to mitigate the burden of infodemics, especially in low resource settings. This research describes the features of a toolkit that can support studies linking information exposure to health behaviours at the individual level. Methods To meet the needs of the research community, we determined the functional and non-functional requirements of a research toolkit that can be used in studies measuring topic-specific information exposure and health behaviours. Most data-driven infodemiology research is designed to characterise content rather than measure associations between information exposure and health behaviours. Studies also tend to be limited to specific social media platforms, are unable to capture the breadth of individual information exposure that occur online and offline, and cannot measure differences in trust by information source or content. Studies are also designed very differently, limiting synthesis of results. Results We demonstrate a way to address these requirements via a web-based study platform that includes an app that participants use to record topic-specific information exposure, a browser plugin for tracking access to relevant webpages, questionnaires that can be delivered at any time during a study, and app-based incentives for participation such as visual analytics to compare trust levels with other participants. Other features of the platform include the ability to tailor studies to local contexts, ease of use for participants, and frictionless sharing of de-identified data for aggregating individual participant data in international meta-analyses. Conclusions Our proposed solution will be able to capture detailed data about information exposure and health behaviour data, standardise study design while simultaneously supporting localisation, and make it easy to synthesise individual participant data across studies. Future research will need to evaluate the toolkit in realistic scenarios to understand the usability of the toolkit for both participants and investigators.

Keywords

• Infodemic
• Infodemiology
• Health behaviours
• Misinformation