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大流行期间不断变化的口罩指南和对公众认知的潜在危害:Twitter 上情感的信息流行病学研究。

Evolving Face Mask Guidance During a Pandemic and Potential Harm to Public Perception: Infodemiology Study of Sentiment and Emotion on Twitter.

机构信息

School of Public Affairs, American University, Washington, DC, United States.

Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States.

出版信息

J Med Internet Res. 2023 Feb 27;25:e40706. doi: 10.2196/40706.


DOI:10.2196/40706
PMID:36763687
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9973548/
Abstract

BACKGROUND: Throughout the COVID-19 pandemic, US Centers for Disease Control and Prevention policies on face mask use fluctuated. Understanding how public health communications evolve around key policy decisions may inform future decisions on preventative measures by aiding the design of communication strategies (eg, wording, timing, and channel) that ensure rapid dissemination and maximize both widespread adoption and sustained adherence. OBJECTIVE: We aimed to assess how sentiment on masks evolved surrounding 2 changes to mask guidelines: (1) the recommendation for mask use on April 3, 2020, and (2) the relaxation of mask use on May 13, 2021. METHODS: We applied an interrupted time series method to US Twitter data surrounding each guideline change. Outcomes were changes in the (1) proportion of positive, negative, and neutral tweets and (2) number of words within a tweet tagged with a given emotion (eg, trust). Results were compared to COVID-19 Twitter data without mask keywords for the same period. RESULTS: There were fewer neutral mask-related tweets in 2020 (β=-3.94 percentage points, 95% CI -4.68 to -3.21; P<.001) and 2021 (β=-8.74, 95% CI -9.31 to -8.17; P<.001). Following the April 3 recommendation (β=.51, 95% CI .43-.59; P<.001) and May 13 relaxation (β=3.43, 95% CI 1.61-5.26; P<.001), the percent of negative mask-related tweets increased. The quantity of trust-related terms decreased following the policy change on April 3 (β=-.004, 95% CI -.004 to -.003; P<.001) and May 13 (β=-.001, 95% CI -.002 to 0; P=.008). CONCLUSIONS: The US Twitter population responded negatively and with less trust following guideline shifts related to masking, regardless of whether the guidelines recommended or relaxed mask usage. Federal agencies should ensure that changes in public health recommendations are communicated concisely and rapidly.

摘要

背景:在整个 COVID-19 大流行期间,美国疾病控制与预防中心(CDC)的口罩使用政策一直在波动。了解公共卫生信息如何围绕关键政策决策演变,可能有助于为未来的预防措施提供信息,方法是辅助沟通策略的设计(例如措辞、时间安排和渠道),以确保快速传播,并最大限度地提高广泛采用和持续遵守的程度。

目的:我们旨在评估围绕口罩指南的 2 次更改(1)2020 年 4 月 3 日的口罩使用建议,以及(2)2021 年 5 月 13 日放宽口罩使用的建议,评估围绕口罩的情绪如何演变。

方法:我们应用中断时间序列方法分析了与每次指南更改相关的美国 Twitter 数据。结果是(1)正面、负面和中性推文的比例以及(2)带有给定情感(例如信任)标签的推文内的字数的变化。结果与同一时期没有口罩关键字的 COVID-19 Twitter 数据进行了比较。

结果:2020 年(β=-3.94 个百分点,95%CI-4.68 至-3.21;P<.001)和 2021 年(β=-8.74,95%CI-9.31 至-8.17;P<.001)期间,与口罩相关的中性推文减少。在 4 月 3 日的建议发布后(β=.51,95%CI.43-.59;P<.001)和 5 月 13 日的放松管制后(β=3.43,95%CI 1.61-5.26;P<.001),与口罩相关的负面推文的比例增加。在 4 月 3 日的政策变更后(β=-.004,95%CI-.004 至-.003;P<.001)和 5 月 13 日(β=-.001,95%CI-.002 至 0;P=.008)之后,与信任相关的术语数量减少。

结论:无论指南是建议还是放宽口罩使用,美国 Twitter 用户对口罩相关指南的变化均做出了负面反应,并且信任度降低。联邦机构应确保简明、快速地传达公共卫生建议的变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/328c/9973548/7d8b3472c6ff/jmir_v25i1e40706_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/328c/9973548/7453883abf9b/jmir_v25i1e40706_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/328c/9973548/7d8b3472c6ff/jmir_v25i1e40706_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/328c/9973548/7453883abf9b/jmir_v25i1e40706_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/328c/9973548/7d8b3472c6ff/jmir_v25i1e40706_fig2.jpg

相似文献

[1]
Evolving Face Mask Guidance During a Pandemic and Potential Harm to Public Perception: Infodemiology Study of Sentiment and Emotion on Twitter.

J Med Internet Res. 2023-2-27

[2]
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[6]
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[7]
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[8]
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[9]
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[10]
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引用本文的文献

[1]
Insight into public sentiment and demand in China's public health emergency response: a weibo data analysis.

BMC Public Health. 2025-4-10

[2]
Anti-masking Posts on Instagram: Content Analysis During the COVID-19 Pandemic.

Saf Health Work. 2025-3

本文引用的文献

[1]
The ephemeral effects of fact-checks on COVID-19 misperceptions in the United States, Great Britain and Canada.

Nat Hum Behav. 2022-2

[2]
Covid-19: Trust in government and other people linked with lower infection rate and higher vaccination uptake.

BMJ. 2022-2-2

[3]
Unmasking the conversation on masks: Natural language processing for topical sentiment analysis of COVID-19 Twitter discourse.

AMIA Jt Summits Transl Sci Proc. 2021

[4]
Why the backfire effect does not explain the durability of political misperceptions.

Proc Natl Acad Sci U S A. 2021-4-13

[5]
Why do people oppose mask wearing? A comprehensive analysis of U.S. tweets during the COVID-19 pandemic.

J Am Med Inform Assoc. 2021-7-14

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Multiple testing: when is many too much?

Eur J Endocrinol. 2021-3

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An "Infodemic": Leveraging High-Volume Twitter Data to Understand Early Public Sentiment for the Coronavirus Disease 2019 Outbreak.

Open Forum Infect Dis. 2020-6-30

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The COVID-19 social media infodemic.

Sci Rep. 2020-10-6

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Leveraging media and health communication strategies to overcome the COVID-19 infodemic.

J Public Health Policy. 2020-12

[10]
Conversations and Medical News Frames on Twitter: Infodemiological Study on COVID-19 in South Korea.

J Med Internet Res. 2020-5-5

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