Quality, Empathy, and Readability of AI Chatbot Responses to the Survivorship Needs of Adolescents and Young Adults With Melanoma: Evaluation Study
AI chatbots can provide moderately accurate and supportive responses to needs of AYA patients with melanoma, but outputs are inconsistent, written above the recommended reading level for health information, and limited in empathy. Question framing strongly influenced chatbot performance, with more emotional prompts drawing greater empathy, and readability aligning with both quality and empathy. Chatbot use in this population should remain adjunctive, with further research needed to standardize quality, improve readability, and enhance empathetic communication.
Authors
- Richard E. Moore (ORCID: https://orcid.org/0009-0007-8483-7818)
- Marcus Roth (ORCID: https://orcid.org/0000-0002-5676-8137)
- Kelly C. Nelson (ORCID: https://orcid.org/0000-0002-5042-7366)
- Jordan Jafarnia (ORCID: https://orcid.org/0000-0001-7195-9882)
- K Riley
- Priscilla L Haff (ORCID: https://orcid.org/0009-0009-2824-1985)
- Sabrina Zheng
- Alyssa Leigh Osheim
- Madeleine Hines Salge
Institutions
- Texas Tech University (US)
- The University of Texas MD Anderson Cancer Center (US)
- The University of Texas Health Science Center (US)
- Texas Tech University Health Sciences Center (US)
Publication Details
- Journal
- JMIR Cancer
- Published
- 2026-02-25
- DOI
- https://doi.org/10.2196/84234
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00