Improving Health Equity for COVID-19 Vaccination for At-risk Populations Using Online Social Networks
Purpose
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.
Conditions
- Vaccination Refusal
- Covid19
- Heart Diseases
Eligibility
- Eligible Ages
- Over 18 Years
- Eligible Genders
- All
- Accepts Healthy Volunteers
- Yes
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
Study Design
- Phase
- N/A
- Study Type
- Interventional
- Allocation
- Randomized
- Intervention Model
- Factorial Assignment
- Primary Purpose
- Basic Science
- Masking
- None (Open Label)
Arm Groups
| Arm | Description | Assigned Intervention |
|---|---|---|
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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. |
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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. |
|
|
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. |
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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. |
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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. |
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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. |
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Recruiting Locations
More Details
- NCT ID
- NCT04779827
- Status
- Active, not recruiting
- Sponsor
- University of Pennsylvania
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.).