Message Humanness as a Predictor of AI’s Perception as Human: Secondary Data Analysis of the HeartBot Study
To the best of our knowledge, this is the first study to explicitly ask participants whether they perceive an interaction as human or from a chatbot (HeartBot) in the health care field. This study's findings (role and importance of message humanness) provide new insights into designing chatbots. However, the current evidence remains preliminary. Future research is warranted to understand the relationship between chatbot identity, message humanness, and health outcomes in a larger-scale study.
Authors
- Haruno Suzuki (ORCID: https://orcid.org/0009-0000-7401-5721)
- Yoshimi Fukuoka (ORCID: https://orcid.org/0000-0002-2245-9264)
- Kenji Sagae (ORCID: https://orcid.org/0000-0003-3371-0618)
- Diane Dagyong Kim (ORCID: https://orcid.org/0009-0003-7174-9684)
- Holli A. DeVon (ORCID: https://orcid.org/0000-0002-4526-9631)
- Jingwen Zhang (ORCID: https://orcid.org/0000-0003-1733-6857)
Institutions
- University of California, Los Angeles (US)
- University of California, San Francisco (US)
- University of California, Davis (US)
Publication Details
- Journal
- JMIR AI
- Published
- 2025-11-21
- DOI
- https://doi.org/10.2196/67717
- Citations
- 1
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 2.48