Other Titles
Does the Algorithm Care? Preliminary Findings from a Randomized Study of AI Communication Tone and Perceived Caring Behaviors [Poster Title]
Abstract
As AI tools increasingly mediate health communication, questions arise about whether users perceive these systems as capable of relational behaviors such as caring, empathy, or emotional support. Existing scholarship emphasizes accuracy and safety, yet little is known about how the emotional tone of AI communication, caring versus neutral, shapes user perceptions across cultural contexts.
This research-in-progress pilot examines how college students in the United States and Kenya interpret caring-tone and neutral-tone AI responses in health scenarios. Using a 2 (Tone: Caring vs. Neutral) × 2 (Health Context: Mental vs. Physical) × 2 (Site: U.S. vs. Kenya) mixed factorial vignette design, the study will recruit 200 undergraduate students (100 per site). Participants will be randomly assigned to AI-generated vignettes and will rate each interaction on trust, empathy, emotional comfort, and authenticity.
We hypothesize that caring-tone responses will yield higher ratings across relational dimensions and that cultural context will moderate these effects. Data will be collected via Qualtrics and analyzed using repeated-measures ANOVA to test main and interaction effects.
Findings, available by the time of presentation, will provide early insight into how tone, culture, and health context influence perceptions of AI’s relational roles. The study lays foundational evidence for developing culturally responsive, ethically grounded AI tools in health communication and informs future federally funded research examining care ethics in AI design.
Notes
References:
Chandra, A., Senthilvel, K., Anjum, R., Uchegbu, I., Smith, L. J., Beaumont, H., Punjabi, R., Begum, S., & Marshall, C. R. (2025). Cultural variation in trust and acceptability of artificial intelligence diagnostics for dementia. Journal of Alzheimer’s Disease, 104(3), 653–655.
De Togni, G., Erikainen, S., Chan, S., & Cunningham-Burley, S. (2021). What makes AI 'intelligent' and 'caring'? Exploring affect and relationality across three sites of intelligence and care. Soc Sci Med, 277, 113874. https://doi.org/10.1016/j.socscimed.2021.113874
Folk, D. P., Wu, C., & Heine, S. J. (2025). Cultural variation in attitudes toward social chatbots. Journal of Cross-Cultural Psychology, 56(3), 219–239.
Sigma Membership
Non-member
Type
Poster
Format Type
Text-based Document
Study Design/Type
Other
Research Approach
Pilot/Exploratory Study
Keywords:
Ethics, Cultural Exchange Programs or Study Abroad, Competence, College Students, Student Attitudes, Cognitive Bias, Artificial Intelligence, Caring
Recommended Citation
Kimani, Rachel W. and Maina, Rose, "Perceptions of AI Caring Behaviors Among University Students in Kenya and the United States" (2026). International Nursing Research Congress (INRC). 113.
https://www.sigmarepository.org/inrc/2026/posters_2026/113
Conference Name
37th International Nursing Research Congress
Conference Host
Sigma Theta Tau International
Conference Location
Toronto, Ontario, Canada
Conference Year
2026
Rights Holder
All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record. All permission requests should be directed accordingly and not to the Sigma Repository. All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.
Review Type
Abstract Review Only: Reviewed by Event Host
Acquisition
Publisher-submission
Date of Issue
2026-09-24
Perceptions of AI Caring Behaviors Among University Students in Kenya and the United States
Toronto, Ontario, Canada
As AI tools increasingly mediate health communication, questions arise about whether users perceive these systems as capable of relational behaviors such as caring, empathy, or emotional support. Existing scholarship emphasizes accuracy and safety, yet little is known about how the emotional tone of AI communication, caring versus neutral, shapes user perceptions across cultural contexts.
This research-in-progress pilot examines how college students in the United States and Kenya interpret caring-tone and neutral-tone AI responses in health scenarios. Using a 2 (Tone: Caring vs. Neutral) × 2 (Health Context: Mental vs. Physical) × 2 (Site: U.S. vs. Kenya) mixed factorial vignette design, the study will recruit 200 undergraduate students (100 per site). Participants will be randomly assigned to AI-generated vignettes and will rate each interaction on trust, empathy, emotional comfort, and authenticity.
We hypothesize that caring-tone responses will yield higher ratings across relational dimensions and that cultural context will moderate these effects. Data will be collected via Qualtrics and analyzed using repeated-measures ANOVA to test main and interaction effects.
Findings, available by the time of presentation, will provide early insight into how tone, culture, and health context influence perceptions of AI’s relational roles. The study lays foundational evidence for developing culturally responsive, ethically grounded AI tools in health communication and informs future federally funded research examining care ethics in AI design.
Description
This pilot study examines how university students in Kenya and the United States perceive caring versus neutral AI communication in mental and physical health scenarios. Using vignette-based experiments, it explores how tone and cultural context shape trust, empathy, emotional comfort, and authenticity in AI-mediated interactions.