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.

项目概要/摘要 LatiNET 将使用多级社交网络模型来研究 SARS-CoV-2 错误信息和 阴谋论 (CT) 信息在五种环境中共享（朋友、家庭、工作、医疗服务和 影响者），影响拉丁裔疫苗犹豫。 社交网络是创造的自组织社会系统。 并强化正面和负面的看法。 有关 SARS-CoV-2 错误信息和 CT 信息的内容、背景和传播方向。 了解拉丁裔社交网络结构如何阻碍或促进 SARS-CoV-2 错误信息和 CT 消息，我们将告知干预措施的设计，以减少不信任/恐惧并提供正确、及时、 通过多个社交网络来源提供全面的信息，使 Latinx 能够做到最好 LatiNET 将重点关注长期存在的低收入拉丁裔。 佛罗里达州迈阿密戴德县将成为该项目的举办地。 研究显示，来自最富裕地区的近 100% 的居民至少感染过一种 SARS-CoV-2 疫苗剂量，而在主要由拉丁裔居住的较贫困社区中，只有不到三分之一的居民接受了疫苗接种 1 我们还发现，错误信息和 CT 信息是 2 我们将使用 Kanamori 博士 (PI) K99/R00 社交网络方法 3-8 和 Drs. Uscinski 和 Stoler (Co-Is) 错误信息和 CT 消息框架2,9-11 用于识别网络如何 结构和动态引入并传播错误信息和 CT 消息，从而可能影响 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 消息的 LatiNET 将研究：1) 参与者的特征，2) 624 个以社会为中心的友谊网络，3) 1,872 个以自我为中心的网络（家庭、工作和健康服务），以及 4) 影响者网络，所有这些都将成为我们改编的 NIMHD 框架的一部分。12 我们的目标是： 1) 确定 拉丁裔友谊网络内部的网络结构和动态如何影响网络的传播和采用 与 SARS-CoV-2 疫苗犹豫相关的错误信息和 CT 信息 2) 区分同质性。 与家人分享的错误信息和 CT 信息相关的二元特征和动态 3）确定拉丁裔与社区、名人的关系， 在所有 AIMS 中，传播 CT 和反 CT 信息的公共卫生、政治影响者和沟通渠道。 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 （例如歧视、耻辱、亲密伴侣暴力）以及与错误信息和 CT 相关的信念和行为 信息（例如，个人层面的政治、心理和社会因素）。 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 以及关于全国范围内以及不同优先人群对 SARS-CoV-2 疫苗犹豫的 CT 信息。