Crowdsourced Campaign for Coronavirus

Overseen By Tiarney Ritchwood, PhD

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Wake Forest University Health Sciences

Disqualifiers: Outside study area, Under 18

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

30 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial tests a new campaign to reduce virus spread by using ideas gathered from the public. The goal is to determine if this approach, alongside standard information, can improve behaviors to prevent viral transmission. Participants will either undergo new training focused on contact tracing or review the results of a crowdsourced prevention campaign, known as the "crowdsourced campaign package." People living in certain zip codes in North Carolina who haven't had COVID-19 or been tested in the last two weeks may qualify for this study. As an unphased trial, this study allows participants to contribute to innovative public health strategies that could shape future virus prevention efforts.

Do I need to stop my current medications for the trial?

The trial information does not specify whether you need to stop taking your current medications.

Is there any evidence suggesting that this trial's treatments are likely to be safe?

Research has shown that the crowdsourced campaign package gathers ideas from many people to find solutions. This method is new and affordable, but lacks extensive data on safety. However, it has been used in other areas, such as social marketing campaigns, without direct safety issues. This is because it focuses on sharing and developing ideas, not physical treatments.

Since it is not a medical treatment and focuses on behavior and information, no known negative effects exist. People generally handle it well because it involves participation and teamwork. This suggests it is likely safe for those involved, but it does not have the same safety data as medical treatments. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about this trial because it explores innovative methods for tackling coronavirus through community engagement and rapid response. The crowdsourced campaign package stands out as it harnesses the collective creativity and input from diverse communities to develop effective disease prevention strategies. Meanwhile, the Rapid Response Team focuses on enhancing contact tracing and case investigation, blending traditional techniques with new hybrid training methods. These approaches aim to empower communities and improve the speed and effectiveness of pandemic response.

What evidence suggests that this trial's treatments could be effective for coronavirus?

Research has shown that crowdsourced campaigns successfully address COVID-19 challenges. For example, one study found that a crowdsourcing approach helped identify effective ways to encourage COVID-19 booster shots. Another study, which gathered ideas from a university community, led to creative solutions for making campuses safer during the pandemic. Additionally, crowdsourcing has quickly identified important COVID-19 studies. In this trial, participants may receive the Crowdsourced Campaign Package, which leverages these findings to encourage behaviors that reduce virus spread through collective creativity and quick problem-solving. Meanwhile, another group will participate in the Rapid Response Team arm, piloting a new hybrid training focused on contact tracing and case investigation. ^{2 6 7 8 9}

Who Is on the Research Team?

Tiarney Ritchwood, PhD

Principal Investigator

Wake Forest University Health Sciences

Are You a Good Fit for This Trial?

This trial is for individuals living in certain North Carolina zip codes, who have never had COVID-19 and haven't been tested for it in the last two weeks. The specific zip codes will be determined.

Inclusion Criteria

specific zip codes in North Carolina (specific zip codes to be determined)

I have never had COVID-19.

have not tested within the past 14 days

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention Development

Development of intervention through a crowdsourcing process, including an open call for submissions

6-12 months

Implementation

Implementation of the crowdsourced campaign package and provision of standard information to control group

up to 3 years

Follow-up

Participants are monitored for changes in health-promotive behaviors and intervention acceptability

up to 4 years

What Are the Treatments Tested in This Trial?

Interventions

• Crowdsourced campaign package
• Standard information

Trial Overview The study is testing a new way to encourage COVID-19 prevention behaviors and testing through a campaign created by a crowdsourcing contest, compared to standard information provided.

How Is the Trial Designed?

Group I: Rapid Response Team Experimental Treatment 1 Intervention

Pilot a new hybrid training focused on contact tracing and case investigation.

Group II: Crowdsourced campaign package Experimental Treatment 1 Intervention

Disease prevention intervention developed using a crowdsourcing process.

Who Is Running the Clinical Trial?

Wake Forest University Health Sciences

Lead Sponsor

Trials

1,432

Recruited

2,506,000+

Duke University

Lead Sponsor

Trials

2,495

Recruited

5,912,000+

Published Research Related to This Trial

Social media discussions about adverse events (AEs) are increasing, but traditional data sources like the FDA's Adverse Event Reporting System (FAERS) show a greater increase in frequency, indicating that while social media can provide insights, it may not fully replace established pharmacovigilance methods.

The study found that linking posts from the same authors on social media resulted in higher quality medical insights, and actively engaging patients for follow-up information yielded a high response rate, suggesting that social media can enhance the depth of pharmacovigilance data.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Engaging Patients via Online Healthcare Fora: Three Pharmacovigilance Use Cases. Powell, G., Kara, V., Painter, JL., et al.[2022]

The CoVaKo project successfully implemented an online survey to identify and document adverse reactions to COVID-19 vaccines, demonstrating feasibility with 2199 participants registered within 31 days.

Feedback from focus groups and health professionals led to improvements in the study materials, highlighting the importance of clear communication and adaptability in research design, especially in response to changing vaccination strategies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Active monitoring of adverse reactions following COVID-19 and other vaccinations: a feasibility study as part of the CoVaKo project. Zeschick, N., Warkentin, L., Kühlein, T., et al.[2022]

A systematic review of 37 studies found that adverse events related to medications are under-reported by 94% in spontaneous reporting systems, highlighting a significant gap in postmarketing surveillance.

This scoping review aims to explore the potential of using social media and crowd-sourced data to improve the detection and monitoring of adverse events associated with health products, which could enhance pharmacovigilance efforts both in Canada and internationally.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Utility of social media and crowd-sourced data for pharmacovigilance: a scoping review protocol. Tricco, AC., Zarin, W., Lillie, E., et al.[2019]

This study demonstrates that Twitter can be effectively used to gather self-reported patient experiences regarding adverse drug reactions (ADRs) for SSRIs and cognitive enhancers, utilizing machine learning to analyze 1548 annotated tweets.

The research achieved a moderate level of agreement in annotations between lay annotators and experienced annotators, and the best-performing machine learning model (Bayesian Generalized Linear Model) showed an F-Score of 0.64, indicating its potential for accurately identifying first-hand drug experiences.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Crowdsourcing Twitter annotations to identify first-hand experiences of prescription drug use. Alvaro, N., Conway, M., Doan, S., et al.[2018]

Citations

1. sciencedirect.com sciencedirect.com/science/article/pii/S2589537022003625

Crowdsourcing interventions to promote uptake of COVID ... We applied a novel crowdsourcing approach to provide rapid insights on the most promising interventions to promote uptake of COVID-19 booster vaccines.

2. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC8122225/

Assessment of a Crowdsourcing Open Call for Approaches ... This qualitative study evaluated 82 submissions to a university open call for creative solutions from students, faculty, and staff to inform safety in the fall ...

3. israel21c.org israel21c.org/crowdsourced-campaign-leads-to-blueprint-for-future-pandemic-drugs/

Crowdsourced campaign leads to blueprint for future ... To be ready for that inevitable arrival, an international crowdsourced campaign to discover an anti-Covid-19 drug has created a blueprint for ...

4. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC9088532/

Crowdsourcing the identification of studies for COVID‐19 ... Crowdsourcing can play a valuable role in study identification and offers willing contributors the opportunity to help identify COVID‐19 research for rapid ...

5. nature.com nature.com/articles/s41598-021-93042-w

Wisdom of crowds detects COVID-19 severity ahead ... Twitter activity as a proxy for crowd perception of the severity of COVID19. We have used readily accessible data from Twitter activity across ...

6. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC9822568/

Crowdsourced Perceptions of Human Behavior to Improve ... We showed this by measuring the correlation between crowdsourced perceptions of NPIs and US incident cases of COVID-19 1-4 weeks ahead, and evaluating whether ...

7. nature.com nature.com/articles/s41598-022-26492-5

Reliability of crowdsourced data and patient-reported ... Crowd-sourced cough data is less reliable than PCR-confirmed data for developing predictive models for COVID-19, and raises concerns about the utility of ...

8. formative.jmir.org formative.jmir.org/2022/5/e35764

A Crowdsourcing Open Contest to Design a Latino-Specific ... The aims of this study are to (1) implement and evaluate a crowdsourcing open contest to solicit a name for a COVID-19 social marketing campaign for Latino ...

9. frontiersin.org frontiersin.org/journals/medicine/articles/10.3389/fmed.2022.961360/full

Twitter-based crowdsourcing: What kind of measures can ... Background: Crowdsourcing is a low-cost, adaptable, and innovative method to collect ideas from numerous contributors with diverse backgrounds.