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A REDCap-based model for electronic consent (eConsent): Moving toward a more personalized consent. | LitMetric

AI Article Synopsis

  • The updated common rule for human subjects research mandates that consent forms should clearly present key information to help individuals decide on study participation, focusing on transparency and regulatory compliance.
  • A community-engaged approach was used to enhance the REDCap software for electronic consent (eConsent), targeting issues like rural access and cultural barriers through personalized, interactive features like avatars and videos.
  • Initial testing of the eConsent framework at academic medical centers showed it was well-received, with plans for further testing to assess how well its features engage participants in the consent process.

Article Abstract

Introduction: The updated common rule, for human subjects research, requires that consents "begin with a 'concise and focused' presentation of the key information that will most likely help someone make a decision about whether to participate in a study" (Menikoff, Kaneshiro, Pritchard. . 2017; (7): 613-615.). We utilized a community-engaged technology development approach to inform feature options within the REDCap software platform centered around collection and storage of electronic consent (eConsent) to address issues of transparency, clinical trial efficiency, and regulatory compliance for informed consent (Harris, et al. 2009; (2): 377-381.). eConsent may also improve recruitment and retention in clinical research studies by addressing: (1) barriers for accessing rural populations by facilitating remote consent and (2) cultural and literacy barriers by including optional explanatory material (e.g., defining terms by hovering over them with the cursor) or the choice of displaying different videos/images based on participant's race, ethnicity, or educational level (Phillippi, et al. . 2018; (4): 529-534.).

Methods: We developed and pilot tested our eConsent framework to provide a personalized consent experience whereby users are guided through a consent document that utilizes avatars, contextual glossary information supplements, and videos, to facilitate communication of information.

Results: The eConsent framework includes a portfolio of eight features, reviewed by community stakeholders, and tested at two academic medical centers.

Conclusions: Early adoption and utilization of this eConsent framework have demonstrated acceptability. Next steps will emphasize testing efficacy of features to improve participant engagement with the consent process.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7681162PMC
http://dx.doi.org/10.1017/cts.2020.30DOI Listing

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