“Development and Implementation of Novel Chatbot-based Genomic Research Consent” Article Swipe
Erica D. Smith
,
Sarah Savage
,
E. Hallie Andrew
,
Glòria Mas Martín
,
Amanda Kahn-Kirby
,
Jonathan LoTempio
,
Emmanuèle C. Délot
,
Andrea J. Cohen
,
Georgia Pitsava
,
Seth Berger
,
Vincent A. Fusaro
,
Éric Vilain
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.01.23.525221
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.01.23.525221
Objective To conduct a retrospective analysis comparing traditional human-based consenting to an automated chat-based consenting process. Materials and Methods We developed a new chat-based consent using our IRB-approved consent forms. We leveraged a previously developed platform (Gia®, or “Genetic Information Assistant”) to deliver the chat content to candidate participants. The content included information about the study, educational information, and a quiz to assess understanding. We analyzed 144 families referred to our study during a 6-month time period. A total of 37 families completed consent using the traditional process, while 35 families completed consent using Gia. Results Engagement rates were similar between both consenting methods. The median length of the consent conversation was shorter for Gia users compared to traditional (44 vs. 76 minutes). Additionally, the total time from referral to consent completion was faster with Gia (5 vs. 16 days). Within Gia, understanding was assessed with a 10-question quiz that most participants (96%) passed. Feedback about the chat consent indicated that 86% of participants had a positive experience. Discussion Using Gia resulted in time savings for both the participant and study staff. The chatbot enables studies to reach more potential candidates. We identified five key features related to human-centered design for developing a consent chat. Conclusion This analysis suggests that it is feasible to use an automated chatbot to scale obtaining informed consent for a genomics research study. We further identify a number of advantages when using a chatbot.
Related Topics
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2023.01.23.525221
- https://www.biorxiv.org/content/biorxiv/early/2023/01/24/2023.01.23.525221.full.pdf
- OA Status
- green
- Cited By
- 8
- References
- 20
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4317891123
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4317891123Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2023.01.23.525221Digital Object Identifier
- Title
-
“Development and Implementation of Novel Chatbot-based Genomic Research Consent”Work title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-01-24Full publication date if available
- Authors
-
Erica D. Smith, Sarah Savage, E. Hallie Andrew, Glòria Mas Martín, Amanda Kahn-Kirby, Jonathan LoTempio, Emmanuèle C. Délot, Andrea J. Cohen, Georgia Pitsava, Seth Berger, Vincent A. Fusaro, Éric VilainList of authors in order
- Landing page
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https://doi.org/10.1101/2023.01.23.525221Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2023/01/24/2023.01.23.525221.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.biorxiv.org/content/biorxiv/early/2023/01/24/2023.01.23.525221.full.pdfDirect OA link when available
- Concepts
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Chatbot, Computer science, World Wide Web, Data scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
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8Total citation count in OpenAlex
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2025: 1, 2024: 4, 2023: 3Per-year citation counts (last 5 years)
- References (count)
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20Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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