John Jennifer N, Gorman Sara, Scales David
Perelman School of Medicine, Penn Medical Communication Research Institute, University of Pennsylvania, Smilow Center for Translational Research Room 12-136, 3400 Civic Center Boulevard, Philadelphia, PA, 19104, United States, 1 (215) 573-5359.
Critica, Bronx, NY, United States.
JMIR Infodemiology. 2025 Mar 24;5:e67119. doi: 10.2196/67119.
The COVID-19 pandemic was accompanied by a barrage of false, misleading, and manipulated information that inhibited effective pandemic response and led to thousands of preventable deaths. Recognition of the urgent public health threat posed by this infodemic led to the development of numerous infodemic management interventions by a wide range of actors. The need to respond rapidly and with limited information sometimes came at the expense of strategy and conceptual rigor. Given limited funding for public health communication and growing politicization of countermisinformation efforts, responses to future infodemics should be informed by a systematic and conceptually grounded evaluation of the successes and shortcomings of existing interventions to ensure credibility of the field and evidence-based action.
This study sought to identify gaps and opportunities in existing infodemic management interventions and to assess the use of public health frameworks to structure responses to infodemics.
We expanded a previously developed dataset of infodemic management interventions, spanning guidelines, policies, and tools from governments, academic institutions, nonprofits, media companies, and other organizations, with 379 interventions included in total. We applied framework analysis to describe and interpret patterns within these interventions through their alignment with codes derived from 3 frameworks selected for their prominence in public health and infodemic-related scholarly discourse: the epidemiological model, the socioecological model, and the environmental health framework.
The epidemiological model revealed the need for rigorous, transparent risk assessments to triage misinformation. The socioecological model demonstrated an opportunity for greater coordination across levels of influence, with only 11% of interventions receiving multiple socioecological codes, and more robust partnerships with existing organizations. The environmental health framework showed that sustained approaches that comprehensively address all influences on the information environment are needed, representing only 19% of the dataset.
Responses to future infodemics would benefit from cross-sector coordination, adoption of measurable and meaningful goals, and alignment with public health frameworks, which provide critical conceptual grounding for infodemic response approaches and ensure comprehensiveness of approach. Beyond individual interventions, a funded coordination mechanism can provide overarching strategic direction and promote collaboration.
新冠疫情伴随着大量虚假、误导性和被操纵的信息,这些信息阻碍了有效的疫情应对,并导致数千例可预防的死亡。认识到这一信息疫情对公共卫生构成的紧迫威胁,促使众多行为主体制定了大量信息疫情管理干预措施。有时,在信息有限的情况下迅速做出反应,是以牺牲策略和概念严谨性为代价的。鉴于公共卫生传播资金有限,以及打击错误信息的努力日益政治化,应对未来的信息疫情应基于对现有干预措施的成功与不足进行系统且基于概念的评估,以确保该领域的可信度和基于证据的行动。
本研究旨在确定现有信息疫情管理干预措施中的差距和机遇,并评估公共卫生框架在构建信息疫情应对措施中的应用情况。
我们扩充了先前开发的信息疫情管理干预措施数据集,涵盖政府、学术机构、非营利组织、媒体公司和其他组织的指南、政策和工具,总共纳入了379项干预措施。我们应用框架分析,通过将这些干预措施与从3个因其在公共卫生和信息疫情相关学术论述中的突出地位而选定的框架衍生出的代码进行比对,来描述和解释这些干预措施中的模式:流行病学模型、社会生态模型和环境卫生框架。
流行病学模型显示,需要进行严格、透明的风险评估,以便对错误信息进行分类。社会生态模型表明,有机会在不同影响层面进行更好的协调,只有11%的干预措施获得了多个社会生态代码,并且需要与现有组织建立更稳固的伙伴关系。环境卫生框架表明,需要采取持续的方法,全面应对对信息环境的所有影响,这类措施在数据集中仅占19%。
应对未来的信息疫情将受益于跨部门协调、采用可衡量且有意义的目标,以及与公共卫生框架保持一致,公共卫生框架为信息疫情应对方法提供了关键的概念基础,并确保方法的全面性。除了个别干预措施外,一个有资金支持的协调机制可以提供总体战略方向并促进合作。