LatiNET, a Multilevel Social Network Model to Examine and Address SARS-CoV-2 Misinformation in Low-Income Latinx Communities.
LatiNET, a Multilevel Social Network Model to Examine and Address SARS-CoV-2 Misinformation in Low-Income Latinx Communities.
批准号:
10631361
负责人:
Mariano Juan Kanamori Nishimura
金额:
$77.78万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-09-20 至 2027-05-31
关键词:
2019-nCoVAddressAdoptionAreaBehaviorBeliefCOVID-19 vaccineCharacteristicsCommunicationCommunitiesContractsCountyDecision MakingDiscriminationDiseaseDoseEconomicsEmotional BondsFamilyFamily memberFloridaFrequenciesFriendsFriendshipsFrightFutureHealthHealth ServicesIndividualInfluentialsInterventionKnowledgeLanguageLatinxLatinx populationLearningLow incomeMedicalMisinformationNational Institute on Minority Health and Health DisparitiesNetwork-basedParticipantPathway AnalysisPerceptionPoliciesPolitical FactorPoliticsPopulationPredispositionPsychological FactorsPublic HealthSARS-CoV-2 negativeScienceSeedsShapesSiteSocial NetworkSourceStructural RacismStructureSymptomsSystemTestingTimeTrustVaccinatedVaccinationWorkcohesioncultural valuesdesigneconomic disparityexperiencehealth disparityhealth inequalitieshealth services networkintimate partner violencemembernetwork modelspandemic diseasepoor communitiespressurepsychologicrecruitservice providerssocialsocial disparitiessocial factorssocial stigmasocial structuresociodemographicstheoriestherapy designunvaccinatedvaccine hesitancy
中文摘要
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英文摘要
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.
期刊论文(0)
专著(0)
科研奖励(0)
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批准号:10707207
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依托单位:
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Multilevel approaches for embracing dyadic, egocentric and two-mode networks which address substance use disorders and HIV risk in Latina seasonal workers
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依托单位:
海外基金