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

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.

Management of infodemics in outbreaks or health crises: a systematic review

“…Also those in topics tangential to health and infodemics, such as climate change misinformation, and misinformation during elections, cybersecurity, or health equity. Consequently, the studies that were included in this review do not cover the complex online-offline information environments ( 45 , 46 ), and focus on social media and text messaging instead of social relationships, designed environments, and differentials of impact of content in different communities ( 47–49 ), and miss the person-centric understanding of what kind of information did they have ( 13 , 50 ).…”

“…Based on that, to tackle infodemics during the COVID-19 pandemic, the WHO infodemic management team conducted global online consultations and conferences on various aspects of prioritizing infodemiological research, sharing experiences and tools, developing capacities and competency framework for infodemic management, to advance metrics and frameworks (12)(13)(14)(15). Operationally, WHO developed partnerships with search, social, and digital companies like Facebook, Google, Tencent, Baidu, Twitter, TikTok, Weibo, Pinterest, and YouTube to promote distribution of WHO's health content.…”

Online health information behaviour and its association with statin adherence in patients with high cardiovascular risk: A prospective cohort study

“…Future research could consider improvements and automation in the research instruments used to capture online health information behaviour by considering passive data acquisition of health information exposure using technology. 36 Fourth, we did not critically appraise the quality of the online health information that participants encountered, but this may be a useful way to better understand differences in the quality of the sources of information. Fifth, our proposed model has a low explanatory power, which may be due to the sample size and the number of variables included in the model.…”

“…An information diary tool was developed and tested to capture the health information that participants encountered either by actively searching or inadvertently while doing other things. 35 , 36 In this study, participants were asked to use the information diary tool to record relevant health information they encountered for a period of 2 months. Health information in this study included information specific to statin use, information about lifestyle modification to improve cardiovascular health such as exercise and diet, information related to medications and complementary alternative medicine to improve cardiovascular health or treat dyslipidemia.…”