LatiNET, a Multilevel Social Network Model to Examine and Address SARS-CoV-2 Misinformation in Low-Income Latinx Communities.

LatiNET，一种多层次社交网络模型，用于检查和解决低收入拉丁裔社区中的 SARS-CoV-2 错误信息。

• 批准号: 10631361
• 负责人: Mariano Juan Kanamori Nishimura
• 金额: $ 77.78万
• 依托单位: UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-20 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10631361
• 关键词: 2019-nCoV; Address; Adoption; Area; Behavior; Belief; COVID-19 vaccine; Characteristics; Communication; Communities; Contracts; County; Decision Making; Discrimination; Disease; Dose; Economics; Emotional Bonds; Family; Family member; Florida; Frequencies; Friends; Friendships; Fright; Future; Health; Health Services; Individual; Influentials; Intervention; Knowledge; Language; Latinx; Latinx population; Learning; Low income; Medical; Misinformation; National Institute on Minority Health and Health Disparities; Network-based; Participant; Pathway Analysis; Perception; Policies; Political Factor; Politics; Population; Predisposition; Psychological Factors; Public Health; SARS-CoV-2 negative; Science; Seeds; Shapes; Site; Social Network; Source; Structural Racism; Structure; Symptoms; System; Testing; Time; Trust; Vaccinated; Vaccination; Work; cohesion; cultural values; design; economic disparity; experience; health disparity; health inequalities; health services network; intimate partner violence; member; network models; pandemic disease; poor communities; pressure; psychologic; recruit; service providers; social; social disparities; social factors; social stigma; social structure; sociodemographics; theories; therapy design; unvaccinated; vaccine hesitancy

PROJECT SUMMARY/ABSTRACT LatiNET will use a multilevel social network model to examine how SARS-CoV-2 misinformation and Conspiracy Theory (CT) messages are shared across five settings (friends, family, work, health service and influencers), impacting Latinx vaccine hesitancy. Social networks are self-organizing social systems that create and reinforce perceptions, both positive and negative. An important gap in current knowledge relates to the content, context and communication direction about SARS-CoV-2 misinformation and CT messages. By learning how Latinx social network structures hinder or promote SARS-CoV-2 misinformation and CT messages, we will inform the design of interventions that will reduce mistrust/fear and provide correct, timely, and comprehensive information, through multiple social network sources, enabling Latinx to make the best health decisions for themselves and their families. LatiNET will focus on low-income Latinx, which have long struggled with social, economic and health inequalities. Miami-Dade County, Florida will be the site for this study, where almost 100% of residents from in wealthiest areas have received at least one SARS-CoV-2 vaccine dose while fewer than a third of residents in poorer communities, mainly inhabited by Latinx individuals, have been vaccinated.1 We have also identified that misinformation and CT messages are prevalent in Florida.2 We will use Dr. Kanamori’s (PI) K99/R00 social network approaches3-8 and Drs. Uscinski’s and Stoler’s (Co-Is) misinformation and CT message framework2,9-11 to identify how network structures and dynamics introduce and spread misinformation and CT messages that could then influence Latinx vaccine hesitancy. We will also identify network structures and dynamics that promote discussion against SARS-CoV-2 misinformation and CT messages. LatiNET will study: 1) participants’ characteristics, 2) 624 friendship sociocentric networks, 3) 1,872 egocentric networks (family, work and health service), and 4) influencer networks, all of which will be part of our adapted NIMHD framework.12 Our AIMS are: 1) Determine how network structures and dynamics inside Latinx friendship networks shape the spread and adoption of misinformation and CT messages associated with SARS-CoV-2 vaccine hesitancy. 2) Distinguish homophily and dyadic characteristics and dynamics associated with misinformation and CT messages shared with family members, co-workers and health service providers. 3) Identify Latinx affiliations with community, celebrity, public health, political influencer and communication channels that spread CT and anti-CT messages. In all AIMS, we will also study the underlying social and structural factors associated with Latinx health decision-making (e.g., discrimination, stigma, intimate partner violence) and beliefs and behaviors tied to misinformation and CT messages (e.g., individual-level political, psychological, and social factors). LatiNET will provide new information that can inform policy and the design of future interventions to reduce the impact of misinformation and CT messages on SARS-CoV-2 vaccine hesitancy nationwide, and also with different priority populations.

项目总结/摘要 该网络将使用一个多层次的社会网络模型来研究SARS-CoV-2错误信息和 阴谋论（CT）的信息在五个环境（朋友，家人，工作，医疗服务和 影响者），影响Latinx疫苗的犹豫。社交网络是一种自组织的社会系统， 并强化正面和负面的看法。当前知识的一个重要空白涉及 关于SARS-CoV-2错误信息和CT信息的内容、背景和传播方向。通过 学习拉丁裔社会网络结构如何阻碍或促进SARS-CoV-2错误信息和CT 信息，我们将告知干预措施的设计，这将减少不信任/恐惧，并提供正确的，及时的， 和全面的信息，通过多个社交网络来源，使拉丁美洲，使最好的 为自己和家人做出健康决定。AZNET将专注于低收入的拉丁裔，他们长期以来 与社会、经济和健康不平等作斗争。迈阿密戴德县，佛罗里达将是网站为这一点 在这项研究中，来自最富裕地区的几乎100%的居民至少感染了一种SARS-CoV-2 而在主要由拉丁裔居民居住的较贫困社区， 1我们还发现，错误信息和CT信息是 我们将使用Kanamori博士（PI）的K99/R 00社交网络方法3 -8和Dr. Uplusski和Steluski（Co-Is）错误信息和CT消息框架2，9-11，以确定网络如何 结构和动力学引入并传播错误信息和CT信息， Latinx疫苗犹豫。我们还将确定促进讨论的网络结构和动态 针对SARS-CoV-2错误信息和CT消息。该网络将研究：1）参与者的特点，2） 624个友谊社会中心网络，3）1，872个自我中心网络（家庭，工作和健康服务），和4） 影响者网络，所有这些都将成为我们适应NIMHD框架的一部分。12我们的目标是：1）确定 拉丁友谊网络内部的网络结构和动态如何塑造 与SARS-CoV-2疫苗犹豫相关的错误信息和CT信息。2)辨别同质性 与家庭共享的错误信息和CT信息相关的二元特征和动态 成员、同事和卫生服务提供者。3)确定拉丁裔与社区，名人， 公共卫生、政治影响者和传播CT和反CT信息的沟通渠道。在所有大西洋、印度洋、地中海和南海区域， 我们还将研究与拉丁裔健康决策相关的潜在社会和结构因素 (e.g.,歧视，耻辱，亲密伴侣暴力）以及与错误信息和CT相关的信仰和行为 消息（例如，个人层面的政治、心理和社会因素）。互联网将提供新的 可以为政策和未来干预措施的设计提供信息，以减少错误信息的影响 和CT信息对SARS-CoV-2疫苗犹豫全国范围内，也与不同的优先人群。