Accepted for/Published in: JMIR Formative Research
Date Submitted: Feb 24, 2022
Date Accepted: Jan 9, 2023
Date Submitted to PubMed: Feb 16, 2023
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Applications of Precision Medicine Digital Health Research to COVID-19: Leveraging Research Partnership Success through a Wisdom of Crowds Approach
ABSTRACT
Background:
The COVID-19 pandemic swiftly and significantly impacted lives in the United States. A “Wisdom in Crowds” model posits that a team of diverse, independently thinking individuals works better in predicting outcomes. Strong relationships are fundamentally important for working collaboratively with diverse stakeholders and co-producing research projects on digital health platforms during the COVID-19 pandemic. We present here an effort of three diverse organizations in designing and deploying a complex digital health research study called COVIDsmart to understand the impact of the pandemic on study participants, their wellbeing, and their communities across large geographical areas with a low-financial and low-personnel cost design.
Objective:
The objective of this paper is to describe the digital solutions adopted in the implementation of the COVIDsmart study and share the preliminary study results.
Methods:
In a multi-institutional effort, COVIDsmart used a combination of digital recruitment, eConsent, survey design through a precision medicine digital health platform. This HIPAA compliant digital platform is alternative to the traditional in-person recruitment and onboarding method for studies. Participants in Virginia were recruited using over three months of active recruitment utilizing widespread digital marketing strategies. Six months of data were collected on the participants of the COVIDsmart study on demographics, COVID-19 clinical parameters, health perceptions, mental and physical health, resilience, vaccination status, education/work functioning, social/family functioning, and economic impact. Data were collected using validated questionnaires or surveys reviewed by an expert panel that were completed in a cyclical fashion. To retain high level of engagement throughout the study, participants were incentivized to stay enrolled and complete more surveys to further their chances of receiving monthly gift card drawing and/or one of multiple grand prizes.
Results:
Virtual recruitment demonstrated relatively high rates of interest in Virginia (N=3,737), and 782 have consented to participate in the study (21.1%). The most successful recruitment technique was the effective use of newsletters/emails (41.4%). The primary reason for contributing as a study participant was advancing research (79.9%), followed by the need to give back to their community (64.8%). Incentives only reported as a reason among 21% of the consented participants. Overall, the primary reason for contributing as a study participant was attributed to altruism at 88.6%.
Conclusions:
From its start-up, to its careful planning and structured process, and to its successful completion, the development of this large-scale digital COVID-19 study is attributed to the “Wisdom in Crowds” approach. This method has helped forge a partnership among multiple diverse institutions and disciplines where the collaborative decision-making process is the essential element. With the help of the “Wisdom in Crowds” approach, more large-scale digital study designs can be co-developed to research health impacts on diverse populations over large geographic areas.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.