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. 2024 Jan 18;31(2):472-478.
doi: 10.1093/jamia/ocad181.

Using a chat-based informed consent tool in large-scale genomic research

Sarah K Savage  1 , Jonathan LoTempio  2 , Erica D Smith  1 , E Hallie Andrew  3   4 , Gloria Mas  1 , Amanda H Kahn-Kirby  1   2 , Emmanuèle Délot  4   5 , Andrea J Cohen  4 , Georgia Pitsava  4 , Robert Nussbaum  1 , Vincent A Fusaro  1   2 , Seth Berger  3   4   5 , Eric Vilain  2   4   5
Affiliations

Using a chat-based informed consent tool in large-scale genomic research

Sarah K Savage et al. J Am Med Inform Assoc. .

Abstract

Objective: We implemented a chatbot consent tool to shift the time burden from study staff in support of a national genomics research study.

Materials and methods: We created an Institutional Review Board-approved script for automated chat-based consent. We compared data from prospective participants who used the tool or had traditional consent conversations with study staff.

Results: Chat-based consent, completed on a user's schedule, was shorter than the traditional conversation. This did not lead to a significant change in affirmative consents. Within affirmative consents and declines, more prospective participants completed the chat-based process. A quiz to assess chat-based consent user understanding had a high pass rate with no reported negative experiences.

Conclusion: Our report shows that a structured script can convey important information while realizing the benefits of automation and burden shifting. Analysis suggests that it may be advantageous to use chatbots to scale this rate-limiting step in large research projects.

Keywords: chatbot; genetic counseling; genomics; informed consent; large-scale research.

PubMed Disclaimer

Conflict of interest statement

EDS, SKS, GM, AHKK, RN, and VAF were full time employees and stockholders of Invitae Corporation at the time of the study.

Figures

Figure 1.
Figure 1.
Examples of Gia chat interactions and accessibility. (A–C) Chat using a mobile device and highlighting HIPAA compliance, educational video link outs, and the final consent. (D) Chat using a desktop web browser and the built-in teach back for incorrect quiz answers. (E) Chat using a handheld tablet showing the ability to select more in-depth information about genetics. Link to interface demonstration: https://app.cleargenetics.com/invite/x63498877448bb9d9?onboarding&demo&noresume.
Figure 2.
Figure 2.
Consent status for referred families at the time of data collection. A flowchart showing the progression from referral to completion of consent and the demographics survey. Ovals indicate the current status of referred families. This analysis includes the first 6 months during which the chat-based consent was offered, June-December 2022.
Figure 3.
Figure 3.
Consent chat engagement patterns. (A) Duration of consent conversation: Amount of time elapsed between opening chat and completing the consent conversation (with an outcome of enrolled, declined, or lost to follow-up). The chat time elapsed to completion includes breaks. For the Traditional method, time displayed is the duration of the uninterrupted video chat. (B) Timing of consent signatures: Proportion of enrollees who signed the consent form before 9 am, between 9 am and 7 pm, after 7 pm, and on a Saturday or a Sunday. Does not include participants who declined or were lost to follow-up. (C) Distribution of the number of days elapsed between referral and consent completion for each enrollee. Using the chat-based consent allowed 16 individuals to enroll on the same day that they heard about the study. Traditional consent was used to enroll 13 individuals on the same day they learned of the study.
See this image and copyright information in PMC

References

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