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地方政府目标的选民推断以及政党与新冠疫情错误信息中的信念之间的关系:对州公共卫生部门推特关注者的横断面调查

Constituents' Inferences of Local Governments' Goals and the Relationship Between Political Party and Belief in COVID-19 Misinformation: Cross-sectional Survey of Twitter Followers of State Public Health Departments.

作者信息

Stevens Hannah, Palomares Nicholas A

机构信息

Department of Communication College of Letters and Science University of California, Davis Davis, CA United States.

Department of Communication Studies Moody College of Communication The University of Texas at Austin Austin, TX United States.

出版信息

JMIR Infodemiology. 2022 Feb 10;2(1):e29246. doi: 10.2196/29246. eCollection 2022 Jan-Jun.

Abstract

BACKGROUND

Amid the COVID-19 pandemic, social media have influenced the circulation of health information. Public health agencies often use Twitter to disseminate and amplify the propagation of such information. Still, exposure to local government-endorsed COVID-19 public health information does not make one immune to believing misinformation. Moreover, not all health information on Twitter is accurate, and some users may believe misinformation and disinformation just as much as those who endorse more accurate information. This situation is complicated, given that elected officials may pursue a political agenda of re-election by downplaying the need for COVID-19 restrictions. The politically polarized nature of information and misinformation on social media in the United States has fueled a COVID-19 infodemic. Because pre-existing political beliefs can both facilitate and hinder persuasion, Twitter users' belief in COVID-19 misinformation is likely a function of their goal inferences about their local government agencies' motives for addressing the COVID-19 pandemic.

OBJECTIVE

We shed light on the cognitive processes of goal understanding that underlie the relationship between partisanship and belief in health misinformation. We investigate how the valence of Twitter users' goal inferences of local governments' COVID-19 efforts predicts their belief in COVID-19 misinformation as a function of their political party affiliation.

METHODS

We conducted a web-based cross-sectional survey of US Twitter users who followed their state's official Department of Public Health Twitter account (n=258) between August 10 and December 23, 2020. Inferences about local governments' goals, demographics, and belief in COVID-19 misinformation were measured. State political affiliation was controlled.

RESULTS

Participants from all 50 states were included in the sample. An interaction emerged between political party affiliation and goal inference valence for belief in COVID-19 misinformation (∆ =0.04; =4.78; <.001); positive goal inference valence predicted increased belief in COVID-19 misinformation among Republicans (β=.47; =2.59; =.01) but not among Democrats (β=.07; =0.84; =.40).

CONCLUSIONS

Our results reveal that favorable inferences about local governments' COVID-19 efforts can accelerate belief in misinformation among Republican-identifying constituents. In other words, accurate COVID-19 transmission knowledge is a function of constituents' sentiment toward politicians rather than science, which has significant implications on public health efforts for minimizing the spread of the disease, as convincing misinformed constituents to practice safety measures might be a political issue just as much as it is a health one. Our work suggests that goal understanding processes matter for misinformation about COVID-19 among Republicans. Those responsible for future COVID-19 public health messaging aimed at increasing belief in valid information about COVID-19 should recognize the need to test persuasive appeals that address partisans' pre-existing political views in order to prevent individuals' goal inferences from interfering with public health messaging.

摘要

背景

在新冠疫情期间,社交媒体影响了健康信息的传播。公共卫生机构经常利用推特来传播和扩大此类信息的传播。然而,接触当地政府认可的新冠公共卫生信息并不能使人对错误信息免疫。此外,推特上并非所有健康信息都是准确的,一些用户可能和那些认可更准确信息的用户一样相信错误信息和虚假信息。鉴于民选官员可能通过淡化对新冠限制措施的需求来推行连任的政治议程,这种情况变得更加复杂。美国社交媒体上信息和错误信息的政治两极分化性质助长了新冠信息疫情。由于先前存在的政治信念既可以促进也可以阻碍说服,推特用户对新冠错误信息的相信程度可能取决于他们对当地政府机构应对新冠疫情动机的目标推断。

目的

我们揭示了目标理解的认知过程,这些过程构成了党派性与对健康错误信息的相信之间关系的基础。我们调查推特用户对地方政府新冠疫情应对措施的目标推断的效价如何根据他们的政党归属预测他们对新冠错误信息的相信程度。

方法

我们对2020年8月10日至12月23日期间关注本州公共卫生部门官方推特账号的美国推特用户进行了一项基于网络的横断面调查(n = 258)。测量了对地方政府目标的推断、人口统计学特征以及对新冠错误信息的相信程度。控制了州政治归属。

结果

样本包括来自所有50个州的参与者。在政党归属和对新冠错误信息的相信程度的目标推断效价之间出现了交互作用(∆ = 0.04;F = 4.78;p <.001);积极的目标推断效价预测共和党人对新冠错误信息的相信程度增加(β =.47;t = 2.59;p =.01),而民主党人则不然(β =.07;t = 0.84;p =.40)。

结论

我们的结果表明,对地方政府新冠疫情应对措施的有利推断会加速共和党选民对错误信息的相信。换句话说,准确的新冠传播知识是选民对政治家的情绪而非科学的函数,这对将疾病传播降至最低的公共卫生努力具有重大影响,因为说服被误导的选民采取安全措施可能既是一个政治问题,也是一个健康问题。我们的研究表明,目标理解过程对共和党人关于新冠的错误信息很重要。那些负责未来旨在增加对新冠有效信息相信程度的新冠公共卫生信息传递的人应该认识到,有必要测试针对党派人士先前政治观点的有说服力的呼吁,以防止个人的目标推断干扰公共卫生信息传递。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/358a/10014089/e6c46f69afe1/infodemiology_v2i1e29246_fig1.jpg

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