Department of Library & Information Science, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan.
Information Management School, Sun Yat-sen University, Guangzhou 510006, China.
Int J Environ Res Public Health. 2021 Jul 30;18(15):8091. doi: 10.3390/ijerph18158091.
Low digital health literacy affects large percentages of populations around the world and is a direct contributor to the spread of COVID-19-related online misinformation (together with bots). The ease and 'viral' nature of social media sharing further complicate the situation. This paper provides a quick overview of the magnitude of the problem of COVID-19 misinformation on social media, its devastating effects, and its intricate relation to digital health literacy. The main strategies, methods and services that can be used to detect and prevent the spread of COVID-19 misinformation, including machine learning-based approaches, health literacy guidelines, checklists, mythbusters and fact-checkers, are then briefly reviewed. Given the complexity of the COVID-19 infodemic, it is very unlikely that any of these approaches or tools will be fully effective alone in stopping the spread of COVID-19 misinformation. Instead, a mixed, synergistic approach, combining the best of these strategies, methods, and services together, is highly recommended in tackling online health misinformation, and mitigating its negative effects in COVID-19 and future pandemics. Furthermore, techniques and tools should ideally focus on evaluating both the message (information content) and the messenger (information author/source) and not just rely on assessing the latter as a quick and easy proxy for the trustworthiness and truthfulness of the former. Surveying and improving population digital health literacy levels are also essential for future infodemic preparedness.
数字健康素养低下影响着全球很大一部分人群,是 COVID-19 相关网络错误信息(与机器人共同作用)传播的直接原因。社交媒体分享的便利性和“病毒性”进一步使情况复杂化。本文简要概述了社交媒体上 COVID-19 错误信息的问题规模、其破坏性影响,以及其与数字健康素养的复杂关系。然后,简要回顾了可用于检测和预防 COVID-19 错误信息传播的主要策略、方法和服务,包括基于机器学习的方法、健康素养指南、清单、破除迷思和事实核查。鉴于 COVID-19 信息疫情的复杂性,任何这些方法或工具都不太可能单独有效地阻止 COVID-19 错误信息的传播。相反,强烈建议采用混合、协同的方法,将这些策略、方法和服务的优点结合起来,以解决网络健康错误信息问题,并减轻其在 COVID-19 和未来大流行中的负面影响。此外,技术和工具应理想地专注于评估信息内容和信息发布者,并不仅仅依靠评估后者作为对前者可信度和真实性的快速简便代理。调查和提高人口数字健康素养水平对于未来的信息疫情准备也是必不可少的。