Improving Health Equity for COVID-19 Vaccination for At-risk Populations Using Online Social Networks
NCT ID: NCT04779827
Last Updated: 2025-02-19
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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ACTIVE_NOT_RECRUITING
NA
4476 participants
INTERVENTIONAL
2021-05-04
2026-01-30
Brief Summary
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This research seeks to use an online social network approach to address these challenges, in which the investigators demonstrate how reducing the online levels of network centralization and network homophily among African American community members directly increases their productive engagement with health-promoting information.
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Detailed Description
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To run each experimental trial, the investigators will recruit 240 African American participants, aged 18 to 40, collectively to answer behavior-relevant questions over a period of no greater than 8 minutes. Participants can respond asynchronously - i.e., when the participants' time permits. As with previous studies, the technical infrastructure will manage participants' progress through the study to ensure that all participants have the relevant information about each other's responses.
To ensure causal identification, each network graph will constitute a single observation of how individual decisions change under conditions of interdependent social information. Thus, each trial of 240 people (6 networks x 40 participants per network) produces 6 observations of a community-level social learning process. Power calculations indicate that 8 independent trials are sufficient to produce results of p\<0.05 with 85% power, resulting in a desired population of 1920 participants for each health topic (e.g., COVID-19 vaccination is a single "health topic"), producing 48 independent observations of collective decision making per health topic.
The studies will target health topics for which there is substantial racial disparity in outcomes and behavior, such as acceptance of COVID-19 vaccination, and spreading of various categories of COVID-19 misinformation (e.g. beliefs related to assessment of personal risk, effectiveness of protective behaviors, methods of transmission, disease prevention, treatment, origins of the virus) and related health practices (e.g. choice of appropriate contraceptive methods, value of heart disease screenings, etc.).
Conditions
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Study Design
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RANDOMIZED
FACTORIAL
BASIC_SCIENCE
NONE
Study Groups
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Egalitarian Networks of Homogeneous Populations
Egalitarian networks are characterized by equal connectivity for all participants in an online network for information exchange. Each network is consisted of 40 individual participants. All network participants in this condition share similar baseline demographic characteristics, attitudes, or behavioral choices.
Online Social Network and Collective Intelligence Intervention
The online network intervention aims to use different configurations of online social networks to optimize the impacts of collective intelligence process to improve individuals' understanding, beliefs, and behavioral choices regarding a variety of health behaviors. Participants will be put into different online networks and respond to health questions while receiving feedback from their network members.
Egalitarian Networks of Diverse Populations
Egalitarian networks are characterized by equal connectivity for all participants in an online network for information exchange. Each network is consisted of 40 individual participants. All network participants in this condition have very different baseline demographic characteristics, attitudes, or behavioral choices.
Online Social Network and Collective Intelligence Intervention
The online network intervention aims to use different configurations of online social networks to optimize the impacts of collective intelligence process to improve individuals' understanding, beliefs, and behavioral choices regarding a variety of health behaviors. Participants will be put into different online networks and respond to health questions while receiving feedback from their network members.
Centralized Networks of Homogeneous Populations
Centralized networks have a small number of influential individuals, called "hubs," with connections to most other people. Centralized networks characterize situations in which most or all individuals are connected to, and seek advice from, a few well-connected "influencers." Each network is consisted of 40 individual participants. All network participants in this condition share similar baseline demographic characteristics, attitudes, or behavioral choices.
Online Social Network and Collective Intelligence Intervention
The online network intervention aims to use different configurations of online social networks to optimize the impacts of collective intelligence process to improve individuals' understanding, beliefs, and behavioral choices regarding a variety of health behaviors. Participants will be put into different online networks and respond to health questions while receiving feedback from their network members.
Centralized Networks of Diverse Populations
Centralized networks have a small number of influential individuals, called "hubs," with connections to most other people. Centralized networks characterize situations in which most or all individuals are connected to, and seek advice from, a few well-connected "influencers." Each network is consisted of 40 individual participants. All network participants in this condition have very different baseline demographic characteristics, attitudes, or behavioral choices.
Online Social Network and Collective Intelligence Intervention
The online network intervention aims to use different configurations of online social networks to optimize the impacts of collective intelligence process to improve individuals' understanding, beliefs, and behavioral choices regarding a variety of health behaviors. Participants will be put into different online networks and respond to health questions while receiving feedback from their network members.
Independent Control of Homogeneous Populations
Independent control condition does not have online networks. Participants in this condition are not put into online networks. Participants only respond to questions by themselves. All participants in this condition share similar baseline demographic characteristics, attitudes, or behavioral choices.
Independent Control
Independent control aims to test the baseline of population understanding of health behaviors and choices. Participants will respond to health questions independently without getting any feedback from others.
Independent Control of Diverse Populations
Independent control condition does not have online networks. Participants in this condition are not put into online networks. Participants only respond to questions by themselves. All participants in this condition have very different baseline demographic characteristics, attitudes, or behavioral choices.
Independent Control
Independent control aims to test the baseline of population understanding of health behaviors and choices. Participants will respond to health questions independently without getting any feedback from others.
Interventions
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Online Social Network and Collective Intelligence Intervention
The online network intervention aims to use different configurations of online social networks to optimize the impacts of collective intelligence process to improve individuals' understanding, beliefs, and behavioral choices regarding a variety of health behaviors. Participants will be put into different online networks and respond to health questions while receiving feedback from their network members.
Independent Control
Independent control aims to test the baseline of population understanding of health behaviors and choices. Participants will respond to health questions independently without getting any feedback from others.
Eligibility Criteria
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Inclusion Criteria
* Aged 18 and above
* Living in the United States
Exclusion Criteria
* Aged below 18
* Living outside of the United States
18 Years
ALL
Yes
Sponsors
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University of California, Davis
OTHER
University of California, San Francisco
OTHER
University of California, Berkeley
OTHER
University of Pennsylvania
OTHER
Responsible Party
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Damon Centola, PhD
Professor of Communication, Sociology and Engineering
Principal Investigators
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Damon Centola, PhD
Role: PRINCIPAL_INVESTIGATOR
University of Pennsylvania
Locations
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Annenberg School for Communication
Philadelphia, Pennsylvania, United States
Countries
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References
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Guilbeault D, Centola D. Networked collective intelligence improves dissemination of scientific information regarding smoking risks. PLoS One. 2020 Feb 6;15(2):e0227813. doi: 10.1371/journal.pone.0227813. eCollection 2020.
Guilbeault D, Becker J, Centola D. Social learning and partisan bias in the interpretation of climate trends. Proc Natl Acad Sci U S A. 2018 Sep 25;115(39):9714-9719. doi: 10.1073/pnas.1722664115. Epub 2018 Sep 4.
Other Identifiers
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827141
Identifier Type: -
Identifier Source: org_study_id
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