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Improving Health Equity for COVID-19 Vaccination for At-risk Populations Using Online Social Networks

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ClinicalTrials.gov Identifier: NCT04779827
Recruitment Status : Recruiting
First Posted : March 3, 2021
Last Update Posted : May 7, 2021
Sponsor:
Collaborators:
University of California, Davis
University of California, San Francisco
University of California, Berkeley
Information provided by (Responsible Party):
Damon Centola, PhD, University of Pennsylvania

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.


Condition or disease Intervention/treatment Phase
Vaccination Refusal Covid19 Contraception Behavior Heart Diseases Behavioral: Online Social Network and Collective Intelligence Intervention Behavioral: Independent Control Not Applicable

Detailed Description:

To investigate the causal effects of network structure and composition on the acceptance of new or unfamiliar behavior-relevant health information, the investigators propose a randomized controlled experiment that compares several independent populations to identify and address participants' endorsement of biased information, and engagement with novel behavior relevant information (e.g., regarding COVID-19 vaccination). Each population will have its own network structure (i.e., level of centralization) and composition (i.e., level of homophily).

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.).

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Study Type : Interventional  (Clinical Trial)
Estimated Enrollment : 1920 participants
Allocation: Randomized
Intervention Model: Factorial Assignment
Masking: None (Open Label)
Primary Purpose: Basic Science
Official Title: Improving Health Equity for COVID-19 Vaccination and Related Health Behaviors for At-risk Populations Using Online Social Networks
Actual Study Start Date : May 4, 2021
Estimated Primary Completion Date : October 30, 2022
Estimated Study Completion Date : December 30, 2022

Arm Intervention/treatment
Experimental: 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.
Behavioral: 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.

Experimental: 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.
Behavioral: 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.

Experimental: 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.
Behavioral: 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.

Experimental: 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.
Behavioral: 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.

Experimental: 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.
Behavioral: 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.

Experimental: 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.
Behavioral: 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.




Primary Outcome Measures :
  1. COVID-19 vaccination attitude [ Time Frame: Immediate after intervention ]
    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.

  2. COVID-19 vaccination intention [ Time Frame: Immediate after intervention ]
    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.


Secondary Outcome Measures :
  1. COVID-19 vaccine belief [ Time Frame: Immediate after intervention ]
    COVID-19 vaccine belief scale, which is a self-reported scale measuring participants' knowledge and belief (including misbelief) about the COVID-19 vaccine safety and effectiveness. The scale is consisted of 12 items (e.g., "A COVID-19 vaccine will not alter my DNA") with responses ranging from 1 (completely disagree) to 5 (completely agree); a higher average score means more accurate knowledge and belief towards the COVID-19 vaccine.



Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Criteria

Inclusion Criteria:

  • Having internet access
  • Aged 18 and above
  • Living in the United States

Exclusion Criteria:

  • Having no internet access
  • Aged below 18
  • Living outside of the United States

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04779827


Contacts
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Contact: Damon Centola 215-898-7954 dcentola@asc.upenn.edu

Locations
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United States, Pennsylvania
Annenberg School for Communication Recruiting
Philadelphia, Pennsylvania, United States, 19104
Contact: Rachel Xian       rachel.xian@asc.upenn.edu   
Sponsors and Collaborators
University of Pennsylvania
University of California, Davis
University of California, San Francisco
University of California, Berkeley
Investigators
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Principal Investigator: Damon Centola, PhD University of Pennsylvania
Publications:
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Responsible Party: Damon Centola, PhD, Professor of Communication, Sociology and Engineering, University of Pennsylvania
ClinicalTrials.gov Identifier: NCT04779827    
Other Study ID Numbers: 827141
First Posted: March 3, 2021    Key Record Dates
Last Update Posted: May 7, 2021
Last Verified: May 2021
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: Yes
Plan Description: We will share the data collected from our online experiments. All sets of data are anonymous.
Supporting Materials: Study Protocol
Statistical Analysis Plan (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.

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Additional relevant MeSH terms:
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Heart Diseases
Cardiovascular Diseases