A REDCap-based model for electronic consent (eConsent): Moving toward a more personalized consent
AuthorsLawrence, Colleen E.
Goins, Karin V.
Fischer, Melissa A.
Allison, Jeroan J.
Lemon, Stephenie C.
Harris, Paul A.
UMass Chan AffiliationsPrevention Research Center
Department of Population and Quantitative Health Sciences
Department of Medicine
Document TypeJournal Article
Health Information Technology
Translational Medical Research
MetadataShow full item record
AbstractIntroduction: 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. The New England Journal of Medicine. 2017; 376(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. Journal of Biomedical Informatics 2009; 42(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. Journal of Obstetric, Gynecologic, and Neonatal Nursing. 2018; 47(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.
Lawrence CE, Dunkel L, McEver M, Israel T, Taylor R, Chiriboga G, Goins KV, Rahn EJ, Mudano AS, Roberson ED, Chambless C, Wadley VG, Danila MI, Fischer MA, Joosten Y, Saag KG, Allison JJ, Lemon SC, Harris PA. A REDCap-based model for electronic consent (eConsent): Moving toward a more personalized consent. J Clin Transl Sci. 2020 Apr 3;4(4):345-353. doi: 10.1017/cts.2020.30. PMID: 33244416; PMCID: PMC7681162. Link to article on publisher's site
Permanent Link to this Itemhttp://hdl.handle.net/20.500.14038/50410
Full author list omitted for brevity. For the full list of authors, see article.