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.

项目摘要/摘要 LatiNET将使用多层社交网络模型来检查SARS-CoV-2错误信息和 阴谋论(CT)信息在五个环境中共享(朋友、家人、工作、医疗服务和 影响者)，影响拉丁裔疫苗的犹豫不决。社交网络是自组织的社会系统，它创造了 并强化正面和负面的看法。当前知识中的一个重要缺口与 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 了解Latinx社交网络结构如何阻碍或促进SARS-CoV-2错误信息和CT 信息，我们将告知干预的设计，这些干预将减少不信任/恐惧，并提供正确、及时、 和全面的信息，通过多个社交网络来源，使Latinx能够做到最好 为他们自己和他们的家人做出健康决定。LatiNET将专注于低收入Latinx，他们已经有很长一段时间了 与社会、经济和健康不平等作斗争。迈阿密-佛罗里达州戴德县将举办这一活动 研究表明，来自最富裕地区的几乎100%的居民至少感染了一种SARS-CoV-2 在主要由拉丁裔居住的贫困社区，只有不到三分之一的居民接种疫苗 我们还发现，错误信息和CT信息是 流行于佛罗里达州2我们将使用Kanamori博士的K99/R00社交网络方法3-8和Dr. Uscinski‘s和Stoler’s(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，然后可能会影响 拉丁疫苗犹豫不决。我们还将确定促进讨论的网络结构和动态 防止SARS-CoV-2错误信息和CT信息。LatiNet将研究：1)参与者的特征，2) 624个以友谊为中心的社会网络，3)1,872个以自我为中心的网络(家庭、工作和保健服务)，4) 影响者网络，所有这些都将成为我们调整后的NIMHD框架的一部分。12我们的目标是：1)确定 Latinx友谊网络中的网络结构和动态如何影响 与SARS-CoV-2疫苗迟疑相关的错误信息和CT信息。2)同源区分 以及与家庭共享的错误信息和CT信息相关的二元性特征和动力学 会员、同事和健康服务提供者。3)确定拉丁裔与社区、名人、 传播CT和抗CT信息的公共卫生、政治影响者和传播渠道。在所有目标中， 我们还将研究与Latinx健康决策相关的潜在社会和结构因素 (例如，歧视、污名、亲密伴侣暴力)以及与错误信息和CT有关的信念和行为 信息(例如，个人层面的政治、心理和社会因素)。LatiNET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信息关于SARS-CoV-2疫苗在全国范围内的犹豫不决，也与不同的优先人群。