Addressing Antivaccine Sentiment on Public Social Media Forums Through Web-Based Conversations Based on Motivational Interviewing Techniques: Observational Study.

IF 3.5 Q1 HEALTH CARE SCIENCES & SERVICES
JMIR infodemiology Pub Date : 2023-11-14 DOI:10.2196/50138
David Scales, Lindsay Hurth, Wenna Xi, Sara Gorman, Malavika Radhakrishnan, Savannah Windham, Azubuike Akunne, Julia Florman, Lindsey Leininger, Jack Gorman
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引用次数: 0

Abstract

Background: Health misinformation shared on social media can have negative health consequences; yet, there is a dearth of field research testing interventions to address health misinformation in real time, digitally, and in situ on social media.

Objective: We describe a field study of a pilot program of "infodemiologists" trained with evidence-informed intervention techniques heavily influenced by principles of motivational interviewing. Here we provide a detailed description of the nature of infodemiologists' interventions on posts sharing misinformation about COVID-19 vaccines, present an initial evaluation framework for such field research, and use available engagement metrics to quantify the impact of these in-group messengers on the web-based threads on which they are intervening.

Methods: We monitored Facebook (Meta Platforms, Inc) profiles of news organizations marketing to 3 geographic regions (Newark, New Jersey; Chicago, Illinois; and central Texas). Between December 2020 and April 2021, infodemiologists intervened in 145 Facebook news posts that generated comments containing either false or misleading information about vaccines or overt antivaccine sentiment. Engagement (emojis plus replies) data were collected on Facebook news posts, the initial comment containing misinformation (level 1 comment), and the infodemiologist's reply (level 2 reply comment). A comparison-group evaluation design was used, with numbers of replies, emoji reactions, and engagements for level 1 comments compared with the median metrics of matched comments using the Wilcoxon signed rank test. Level 2 reply comments (intervention) were also benchmarked against the corresponding metric of matched reply comments (control) using the Wilcoxon signed rank test (paired at the level 1 comment level). Infodemiologists' level 2 reply comments (intervention) and matched reply comments (control) were further compared using 3 Poisson regression models.

Results: In total, 145 interventions were conducted on 132 Facebook news posts. The level 1 comments received a median of 3 replies, 3 reactions, and 7 engagements. The matched comments received a median of 1.5 (median of IQRs 3.75) engagements. Infodemiologists made 322 level 2 reply comments, precipitating 189 emoji reactions and a median of 0.5 (median of IQRs IQR 0) engagements. The matched reply comments received a median of 1 (median of IQRs 2.5) engagement. Compared to matched comments, level 1 comments received more replies, emoji reactions, and engagements. Compared to matched reply comments, level 2 reply comments received fewer and narrower ranges of replies, reactions, and engagements, except for the median comparison for replies.

Conclusions: Overall, empathy-first communication strategies based on motivational interviewing garnered less engagement relative to matched controls. One possible explanation is that our interventions quieted contentious, misinformation-laden threads about vaccines on social media. This work reinforces research on accuracy nudges and cyberbullying interventions that also reduce engagement. More research leveraging field studies of real-time interventions is needed, yet data transparency by technology platforms will be essential to facilitate such experiments.

通过基于动机性访谈技术的网络对话解决公共社交媒体论坛上的反疫苗情绪:观察性研究
背景:在社交媒体上分享的健康错误信息可能对健康产生负面影响;然而,缺乏实地研究测试干预措施,以实时、数字化和现场的方式解决社交媒体上的健康错误信息。目的:我们描述了一项对“信息流行病学”试点项目的实地研究,这些“信息流行病学”接受了大量受动机性访谈原则影响的循证干预技术的培训。在这里,我们详细描述了信息流行病学学家对分享有关COVID-19疫苗的错误信息的帖子进行干预的性质,提出了此类实地研究的初步评估框架,并使用可用的参与指标来量化这些群内信使对其干预的网络线程的影响。方法:我们监测了面向3个地理区域(新泽西州纽瓦克;芝加哥,伊利诺斯州;以及德克萨斯州中部)。在2020年12月至2021年4月期间,信息流行病学学家干预了145个Facebook新闻帖子,这些帖子产生的评论包含有关疫苗的虚假或误导性信息或公开的反疫苗情绪。参与(表情符号加回复)数据收集于Facebook新闻帖子、包含错误信息的初始评论(1级评论)和信息流行病学家的回复(2级回复评论)。使用比较组评估设计,将回复数量、表情符号反应和1级评论的参与与使用Wilcoxon签名秩检验的匹配评论的中位数指标进行比较。2级回复评论(干预)也使用Wilcoxon签名秩检验(在1级评论水平配对)对匹配回复评论(对照)的相应度量进行基准测试。采用3种泊松回归模型对信息流行病学专家的二级回复评论(干预)和匹配回复评论(对照)进行比较。结果:共对132个Facebook新闻帖子进行了145次干预。第1级的评论收到了3个回复,3个反应和7个参与。匹配的评论的参与度中位数为1.5 (IQRs中位数为3.75)。信息流行学家发表了322条二级回复评论,引发了189个表情符号反应,参与的中位数为0.5 (IQR中位数为0)。匹配的回复评论的参与度中位数为1 (IQRs中位数为2.5)。与匹配的评论相比,1级评论收到了更多的回复、表情符号反应和参与。与匹配的回复评论相比,除了回复的中位数比较外,第2级回复评论收到的回复、反应和参与的范围更少、更窄。结论:总体而言,基于动机性访谈的共情优先沟通策略相对于匹配的对照组获得了更少的参与。一种可能的解释是,我们的干预平息了社交媒体上关于疫苗的有争议的、充满错误信息的帖子。这项工作加强了对准确性推动和网络欺凌干预的研究,这些干预也会降低参与度。需要更多利用现场实时干预研究的研究,但技术平台的数据透明度对于促进此类实验至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
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