Bridging Technology and Pretest Genetic Services: Quantitative Study of Chatbot Interaction Patterns, User Characteristics, and Genetic Testing Decisions
Findings highlight the chatbot's effectiveness in engaging users and its high acceptability, with most participants completing the chat, opting for additional information, and showing a high willingness to pursue genetic testing. Sociodemographic factors were not associated with interaction patterns, potentially indicating the chatbot's scalability across diverse populations provided they have internet access. Future efforts should address the concerns of users with high information needs and integrate them into chatbot design to better support informed genetic decision-making.
Authors
- Kensaku Kawamoto (ORCID: https://orcid.org/0000-0003-4282-9338)
- David Mann (ORCID: https://orcid.org/0000-0002-2099-0852)
- Whitney Espinel (ORCID: https://orcid.org/0000-0002-7159-9239)
- Rachel Hess (ORCID: https://orcid.org/0000-0003-2545-8504)
- David W. Wetter (ORCID: https://orcid.org/0000-0002-4013-1932)
- Kimberly A. Kaphingst (ORCID: https://orcid.org/0000-0003-2668-9080)
- Daniel Chavez‐Yenter (ORCID: https://orcid.org/0000-0001-7764-4443)
- Rachelle Lorenz Chambers (ORCID: https://orcid.org/0000-0003-2478-8835)
- Meenakshi Sigireddi (ORCID: https://orcid.org/0000-0003-4448-0504)
- Richard L. Bradshaw (ORCID: https://orcid.org/0000-0001-7363-0327)
- Yang Yi (ORCID: https://orcid.org/0000-0001-6178-0758)
- Guilherme Del Fiol (ORCID: https://orcid.org/0000-0001-9954-6799)
- Saundra S. Buys (ORCID: https://orcid.org/0000-0003-4120-5697)
- Melody S. Goodman (ORCID: https://orcid.org/0000-0001-8932-624X)
- Jemar R. Bather (ORCID: https://orcid.org/0000-0002-0285-3678)
- Ophira Ginsburg (ORCID: https://orcid.org/0000-0002-1384-2675)
- Rachel Monahan (ORCID: https://orcid.org/0000-0003-1000-2790)
- Lauren Kaiser‐Jackson
Institutions
- University of Utah (US)
- Huntsman Cancer Institute (US)
- NYU Langone Health (US)
- International Center for Transitional Justice (US)
- Center for Global Health (US)
- National Cancer Institute (US)
- New York University (US)
- University of Pennsylvania (US)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2025-09-17
- DOI
- https://doi.org/10.2196/73391
- Citations
- 2
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 4.96