Improving Health Equity for COVID-19 Vaccination for At-risk Populations Using Online Social Networks
1 other identifier
interventional
4,476
1 country
1
Brief Summary
Social technologies for health have already become essential means for providing underserved populations greater social connectedness and increased access to novel health information. However, these technologies have also had negative unintended consequences. The resulting digital divide in social technology takes many forms - from explicit racism that excludes African American and Latinx populations from the resources enjoyed by White and Asian members of online communities, to self-segregation for the purposes of identity preservation and community-building that unintentionally results in limited informational diversity in underserved communities. The result is an often unnoticed, but highly consequential compounding of inequities. 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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started May 2021
Longer than P75 for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
February 21, 2021
CompletedFirst Posted
Study publicly available on registry
March 3, 2021
CompletedStudy Start
First participant enrolled
May 4, 2021
CompletedPrimary Completion
Last participant's last visit for primary outcome
March 30, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
March 30, 2027
ExpectedMarch 19, 2026
March 1, 2026
1.9 years
February 21, 2021
March 18, 2026
Conditions
Outcome Measures
Primary Outcomes (3)
COVID-19 vaccination attitude
COVID-19 vaccination attitude scale, which is a self-reported scale measuring participants' attitudes toward COVID-19 vaccination. The scale is consisted of 5 questions (e.g., "How much confidence do you have that the COVID-19 vaccine in the U.S. is safe and effective?") with responses ranging from 1 (No confidence at all) to 5 (A great deal of confidence); a higher average score means a more positive attitude in favor of COVID-19 vaccination.
Immediate after intervention
COVID-19 vaccination intention
COVID-19 vaccination intention scale, which is a self-reported scale measuring participants' intention toward COVID-19 vaccination. The scale is consisted of 5 questions (e.g., "Would you get a COVID-19 vaccine when it is available to you?") with responses ranging from 1 (Definitely Not) to 5 (Definitely); a higher average score means a stronger intention to receive the COVID-19 vaccine.
Immediate after intervention
COVID-19 vaccine safety perception
One question asks participant's estimation of one potential side effect from the COVID-19 vaccine. The question asks "According to the most recent data, for every 10 million people in the US vaccinated for COVID-19, how many experienced a severe allergic reaction (anaphylaxis)? Answer must be between 0 and 10,000."
Immediate after intervention
Secondary Outcomes (1)
COVID-19 vaccine belief
Immediate after intervention
Study Arms (6)
Egalitarian Networks of Homogeneous Populations
EXPERIMENTALEgalitarian 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.
Egalitarian Networks of Diverse Populations
EXPERIMENTALEgalitarian 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.
Centralized Networks of Homogeneous Populations
EXPERIMENTALCentralized 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.
Centralized Networks of Diverse Populations
EXPERIMENTALCentralized 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.
Independent Control of Homogeneous Populations
EXPERIMENTALIndependent 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 of Diverse Populations
EXPERIMENTALIndependent 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.
Interventions
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 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
You may qualify if:
- Having internet access
- Aged 18 and above
- Living in the United States
You may not qualify if:
- Having no internet access
- Aged below 18
- Living outside of the United States
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- University of Pennsylvanialead
- University of California, Daviscollaborator
- University of California, San Franciscocollaborator
- University of California, Berkeleycollaborator
Study Sites (1)
Annenberg School for Communication
Philadelphia, Pennsylvania, 19104, United States
Related Publications (2)
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.
PMID: 32027656BACKGROUNDGuilbeault 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.
PMID: 30181271BACKGROUND
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Damon Centola, PhD
University of Pennsylvania
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- NONE
- Purpose
- BASIC SCIENCE
- Intervention Model
- FACTORIAL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Professor of Communication, Sociology and Engineering
Study Record Dates
First Submitted
February 21, 2021
First Posted
March 3, 2021
Study Start
May 4, 2021
Primary Completion
March 30, 2023
Study Completion (Estimated)
March 30, 2027
Last Updated
March 19, 2026
Record last verified: 2026-03
Data Sharing
- IPD Sharing
- Will share
- Shared Documents
- STUDY PROTOCOL, SAP, ANALYTIC CODE
- Time Frame
- Data will be available when the primary intervention paper is published.
- Access Criteria
- Data will be shared as a part of the published paper, in forms of supplementary materials. The public can access the data through the publisher's website.
We will share the data collected from our online experiments. All sets of data are anonymous.