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

200 Participants Needed

Trial Summary

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.

What data supports the effectiveness of the Crowdsourced campaign package treatment for coronavirus?

Crowdsourcing has been used effectively in other health areas, such as improving HIV and sexual health outcomes, and increasing hepatitis C testing and care. This suggests that a crowdsourced campaign could potentially be effective in addressing coronavirus by engaging the community in health promotion and data collection. ^{1 2 3 4 5}

Is there any safety data available for the Crowdsourced Campaign for Coronavirus treatment?

The research articles reviewed do not provide specific safety data for the Crowdsourced Campaign for Coronavirus treatment. They focus on using social media and crowdsourcing for monitoring adverse drug reactions in general, but not for this specific treatment. ^{6 7 8 9 10}

How is the Crowdsourced campaign package treatment for coronavirus different from other treatments?

The Crowdsourced campaign package is unique because it uses community-driven efforts to gather and analyze data, helping to address knowledge gaps and improve public health messaging. This approach leverages the collective input of the public to enhance understanding and response to the coronavirus, unlike traditional treatments that focus solely on medical interventions. ^{1 3 5 11 12}

What is the purpose of this trial?

This study evaluates the impact of an intervention to increase COVID-19 prevention behaviors, including COVID-19 testing. The intervention will be developed through a crowdsourcing contest.

Research Team

Tiarney Ritchwood, PhD

Principal Investigator

Wake Forest University Health Sciences

Eligibility Criteria

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

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

Treatment Details

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.

Participant Groups

Group I: Crowdsourced campaign package Experimental Treatment 1 Intervention

The intervention will be developed through a crowdsourcing process, including an open call for submissions.

Group II: Standard information Active Control 1 Intervention

The control will be the provision of standard information (e.g., view standard informational videos promoting the adoption of health-protective behaviors and COVID-19 testing).

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+

Findings from Research

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]

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]

References

1. Switzerland pubmed.ncbi.nlm.nih.gov

Hyperlocal Postcode Based Crowdsourced Surveillance Systems in the COVID-19 Pandemic Response. [2021]

2. United States pubmed.ncbi.nlm.nih.gov

Power of crowdsourcing: novel methods of data collection in psoriasis and psoriatic arthritis. [2022]

3. England pubmed.ncbi.nlm.nih.gov

Crowdsourcing a crisis response for COVID-19 in oncology. [2022]

4. United States pubmed.ncbi.nlm.nih.gov

Crowdsourcing to Improve HIV and Sexual Health Outcomes: a Scoping Review. [2021]

5. England pubmed.ncbi.nlm.nih.gov

Crowdsourcing to promote hepatitis C testing and linkage-to-care in China: a randomized controlled trial protocol. [2021]

6. England pubmed.ncbi.nlm.nih.gov

Utility of social media and crowd-sourced data for pharmacovigilance: a scoping review protocol. [2019]

7. United States pubmed.ncbi.nlm.nih.gov

Crowdsourcing Twitter annotations to identify first-hand experiences of prescription drug use. [2018]

8. Switzerland pubmed.ncbi.nlm.nih.gov

Engaging Patients via Online Healthcare Fora: Three Pharmacovigilance Use Cases. [2022]

9. England pubmed.ncbi.nlm.nih.gov

Crowdsourcing sugammadex adverse event rates using an in-app survey: feasibility assessment from an observational study. [2022]

10. England 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. [2022]

11. England pubmed.ncbi.nlm.nih.gov

Using crowdsourcing at an academic conference to develop STI testing messaging for public dissemination. [2023]

12. United States pubmed.ncbi.nlm.nih.gov

Wisdom of the Crowds: Crowd-Based Development of a Logo for a Conference Using a Crowdsourcing Contest. [2018]