Vaccination RefusalNCT04779827
Improving Health Equity for COVID-19 Vaccination for At-risk Populations Using Online Social Networks
A study testing Online Social Network and Collective Intelligence Intervention in people with Vaccination Refusal and Covid19, run by University of Pennsylvania at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Vaccination Refusal, Covid19, Heart Diseases
- What is being tested?
- Online Social Network and Collective Intelligence Intervention
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 4,476 participants
- Where
- 1 siteUnited States
- Study dates
- 4 May 2021to 30 Mar 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Having internet access
- Aged 18 and above
- Living in the United States
Who cannot join
- Having no internet access
- Aged below 18
- Living outside of the United States
Trial locations and contacts
1 site in 1 country.
United States1 site
Annenberg School for Communication
Philadelphia, Pennsylvania, 19104
About this study
Official title: Improving Health Equity for COVID-19 Vaccination and Related Health Behaviors for At-risk Populations Using Online Social Networks
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.
Read the 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.).
- Conditions
- Vaccination Refusal, Covid19, Heart Diseases
- Being tested
- Online Social Network and Collective Intelligence Intervention, Independent Control
- Medical subject headings
- Vaccination Refusal, COVID-19, Heart Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Online Social Network and Collective Intelligence InterventionBehavioural
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 ControlBehavioural
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.
| Study group | Role | What they receive |
|---|---|---|
| Egalitarian Networks of Homogeneous Populations | Experimental | 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. Receives: Behavioral: Online Social Network and Collective Intelligence Intervention |
| Egalitarian Networks of Diverse Populations | Experimental | 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. Receives: Behavioral: Online Social Network and Collective Intelligence Intervention |
| Centralized Networks of Homogeneous Populations | Experimental | 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. Receives: Behavioral: Online Social Network and Collective Intelligence Intervention |
| Centralized Networks of Diverse Populations | Experimental | 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. Receives: Behavioral: Online Social Network and Collective Intelligence Intervention |
| Independent Control of Homogeneous Populations | Experimental | 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. Receives: Behavioral: Independent Control |
| Independent Control of Diverse Populations | Experimental | 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. Receives: Behavioral: Independent Control |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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.
Measured: 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."
Measured: Immediate after intervention
Secondary outcomes (1)
COVID-19 vaccine belief
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.
Measured: Immediate after intervention
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Mar 2021
- Study start4 May 2021
- Primary completion30 Mar 2023
- Study completion30 Mar 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Vaccination RefusalStudies of the same condition, open and under way.
- More trials run by University of PennsylvaniaThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Basic science
- Allocation
- Randomised
- Intervention model
- Factorial
- Masking
- None (open label)
- Enrolment
- 4,476 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Pennsylvania
- Sponsor type
- University, hospital or other
- Collaborators
- University of California, Davis, University of California, San Francisco, University of California, Berkeley
- Responsible party
- Principal investigator, Damon Centola, PhD, University of Pennsylvania
- Investigators
- Damon Centola, PhD, Principal investigator, University of Pennsylvania
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04779827
- Sponsor's protocol ID
- 827141
- Status last verified
- Mar 2026
- First submitted
- 21 Feb 2021
- Last updated
- 19 Mar 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: We will share the data collected from our online experiments. All sets of data are anonymous.
Publications
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.
PubMed 32027656Guilbeault 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.
PubMed 30181271
Study at a glance
From the registry record, last updated by the sponsor on 19 Mar 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Improving Health Equity for COVID-19 Vaccination and Related Health Behaviors for At-risk Populations Using Online Social Networks
- ClinicalTrials.gov ID
- NCT04779827
- Acronym / sponsor ID
- 827141
- Conditions
- Vaccination Refusal, Covid19, Heart Diseases
- Study type
- Interventional
- Recruitment status
- Active, not recruiting
- Enrolment
- 4,476 participants (actual)
- Lead sponsor
- University of PennsylvaniaUniversity, hospital or other
- Collaborators
- University of California, Davis, University of California, San Francisco, University of California, Berkeley
- Study start
- 4 May 2021 (actual)
- Primary completion
- 30 Mar 2023 (actual)
- Study completion
- 30 Mar 2027 (estimated)
- First posted
- 3 Mar 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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.).
Study design
- Primary purpose
- Basic science
- Allocation
- Randomised
- Intervention model
- Factorial
- Masking
- None (open label)
- Number of arms
- 6
| Arm | Type | Receives |
|---|---|---|
| Egalitarian Networks of Homogeneous Populations | Experimental | Behavioral: Online Social Network and Collective Intelligence InterventionEgalitarian 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 | Experimental | Behavioral: Online Social Network and Collective Intelligence InterventionEgalitarian 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 | Experimental | Behavioral: Online Social Network and Collective Intelligence InterventionCentralized 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 | Experimental | Behavioral: Online Social Network and Collective Intelligence InterventionCentralized 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 | Experimental | Behavioral: Independent ControlIndependent 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 | Experimental | Behavioral: Independent ControlIndependent 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Having internet access
- Aged 18 and above
- Living in the United States
Key exclusion criteria (3 listed)
- Having no internet access
- Aged below 18
- Living outside of the United States
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Online Social Network and Collective Intelligence InterventionThe 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. | Behavioural | Centralized Networks of Diverse Populations, Centralized Networks of Homogeneous Populations, Egalitarian Networks of Diverse Populations, Egalitarian Networks of Homogeneous Populations |
| Independent ControlIndependent 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. | Behavioural | Independent Control of Diverse Populations, Independent Control of Homogeneous Populations |
Primary outcome
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.
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.
COVID-19 vaccine safety perception
Time frame: Immediate after intervention
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."
1 secondary outcome
COVID-19 vaccine belief
Time frame: Immediate after intervention
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Mar 2026.
- Background: PubMed 32027656Guilbeault 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.
- Background: PubMed 30181271Guilbeault 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.
- Individual participant dataSharing planned: Yes. We will share the data collected from our online experiments. All sets of data are anonymous.
Related trials for Vaccination Refusal
Recruiting
Intrahospital Influenza Vaccination in Patients at High Cardiovascular Risk (VACC-UP)
Acute Coronary Syndrome, Heart Failure
Not yet recruiting
Development and Evaluation of a Digital Educational Intervention to Improve Vaccine Confidence and Communication Among Registered Nurses: Protocol for a Randomized Controlled Trial (VaxNurse-RCT).
Vaccine Hesitancy, Vaccine Acceptance
Active, not recruiting
Communication Strategies to Increase HPV Vaccinations
Papilloma Viral Infection, Vaccine Hesitancy
Not yet recruiting
Parents' Knowledge and Attitudes Towards Vaccinating Their Children
Vaccine Hesitancy
Not yet recruiting
A Bio-Psycho-Social Medical Model-Based Study on Adolescent Female HPV Vaccination Behavior and Comprehensive Intervention
HPV, Vaccination Hesitancy
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Damon Centola, PhD principal investigator
University of Pennsylvania
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Online Social Network and Collective Intelligence Intervention in people with Vaccination Refusal and Covid19, run by University of Pennsylvania at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 19 Mar 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
COVID-19 vaccination attitude (time frame: Immediate after intervention). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04779827, which also lists 2 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Mar 2026.