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      Fighting the infodemic: the 4 i Framework for Advancing Communication and Trust

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          Abstract

          Background

          The proliferation of false and misleading health claims poses a major threat to public health. This ongoing “infodemic” has prompted numerous organizations to develop tools and approaches to manage the spread of falsehoods and communicate more effectively in an environment of mistrust and misleading information. However, these tools and approaches have not been systematically characterized, limiting their utility. This analysis provides a characterization of the current ecosystem of infodemic management strategies, allowing public health practitioners, communicators, researchers, and policy makers to gain an understanding of the tools at their disposal.

          Methods

          A multi-pronged search strategy was used to identify tools and approaches for combatting health-related misinformation and disinformation. The search strategy included a scoping review of academic literature; a review of gray literature from organizations involved in public health communications and misinformation/disinformation management; and a review of policies and infodemic management approaches from all U.S. state health departments and select local health departments. A team of annotators labelled the main feature(s) of each tool or approach using an iteratively developed list of tags.

          Results

          We identified over 350 infodemic management tools and approaches. We introduce the 4 i Framework for Advancing Communication and Trust (4 i FACT), a modified social-ecological model, to characterize different levels of infodemic intervention: informational, individual, interpersonal, and institutional. Information-level strategies included those designed to amplify factual information, fill information voids, debunk false information, track circulating information, and verify, detect, or rate the credibility of information. Individual-level strategies included those designed to enhance information literacy and prebunking/inoculation tools. Strategies at the interpersonal/community level included resources for public health communicators and community engagement approaches. Institutional and structural approaches included resources for journalists and fact checkers, tools for managing academic/scientific literature, resources for infodemic researchers/research, resources for infodemic managers, social media regulation, and policy/legislation.

          Conclusions

          The 4 i FACT provides a useful way to characterize the current ecosystem of infodemic management strategies. Recognizing the complex and multifaceted nature of the ongoing infodemic, efforts should be taken to utilize and integrate strategies across all four levels of the modified social-ecological model.

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          Most cited references40

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          • Article: not found

          Judgment under Uncertainty: Heuristics and Biases.

          This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty.
            • Record: found
            • Abstract: found
            • Article: not found

            The spread of true and false news online

            We investigated the differential diffusion of all of the verified true and false news stories distributed on Twitter from 2006 to 2017. The data comprise ~126,000 stories tweeted by ~3 million people more than 4.5 million times. We classified news as true or false using information from six independent fact-checking organizations that exhibited 95 to 98% agreement on the classifications. Falsehood diffused significantly farther, faster, deeper, and more broadly than the truth in all categories of information, and the effects were more pronounced for false political news than for false news about terrorism, natural disasters, science, urban legends, or financial information. We found that false news was more novel than true news, which suggests that people were more likely to share novel information. Whereas false stories inspired fear, disgust, and surprise in replies, true stories inspired anticipation, sadness, joy, and trust. Contrary to conventional wisdom, robots accelerated the spread of true and false news at the same rate, implying that false news spreads more than the truth because humans, not robots, are more likely to spread it.
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              Confirmation bias: A ubiquitous phenomenon in many guises.

                Author and article information

                Contributors
                asundel1@jhu.edu
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                30 August 2023
                30 August 2023
                2023
                : 23
                : 1662
                Affiliations
                [1 ]GRID grid.512538.8, Johns Hopkins Center for Health Security, ; 700 E. Pratt Street, Suite 900, Baltimore, MD 21202 USA
                [2 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Department of Environmental Health and Engineering, , Johns Hopkins Bloomberg School of Public Health, ; 615 N. Wolfe Street, Room E7527, Baltimore, MD 21205 USA
                [3 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Department of Health, Behavior and Society, , Johns Hopkins Bloomberg School of Public Health, ; 615 N. Wolfe Street, Baltimore, MD 21205 USA
                [4 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Department of International Health, , Johns Hopkins Bloomberg School of Public Health, ; 615 N. Wolfe Street, Baltimore, MD 21205 USA
                Article
                16612
                10.1186/s12889-023-16612-9
                10466697
                37644563
                f3badf84-e1f8-4339-8936-a03d790b3c65
                © BioMed Central Ltd., part of Springer Nature 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 12 April 2023
                : 24 August 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000030, Centers for Disease Control and Prevention;
                Award ID: 75D30122C14281
                Award ID: 75D30122C14281
                Award ID: 75D30122C14281
                Award ID: 75D30122C14281
                Award ID: 75D30122C14281
                Award Recipient :
                Funded by: Catalyst Grant
                Award ID: No ID number (internal funding)
                Award ID: No ID number (internal funding)
                Award ID: No ID number (internal funding)
                Award ID: No ID number (internal funding)
                Award ID: No ID number (internal funding)
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100009643, National Academies of Sciences, Engineering, and Medicine;
                Award ID: 2000015005
                Award ID: 2000015005
                Award ID: 2000015005
                Award ID: 2000015005
                Award ID: 2000015005
                Award Recipient :
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2023

                Public health
                misinformation,disinformation,infodemic,fact check,social media,social-ecological model
                Public health
                misinformation, disinformation, infodemic, fact check, social media, social-ecological model

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