T2 Coach: A Qualitative Study of an Automated Health Coach for Diabetes Self-Management

要旨

Computational intelligence is increasingly common in interactive systems in many domains, including health. Health coaching with conversational agents (CA) can reach wide populations, but the level of computational intelligence needed for a positive coaching experience is unclear. We conducted a study with sixteen individuals with diabetes and prediabetes who used a CA for health coaching, T2 Coach. Qualitative interviews revealed that participants saw T2 Coach as reliable in helping them stay on track with self-management, appreciated the flexibility in choosing personally meaningful goals and engaging on their own terms, and felt it provided encouragement and even compared it favorably with human coaches. However, they also noted that coaching experience could be improved with more fluid conversations, more tailoring to their personal preferences and lifestyles, and more sensitivity to specific contexts, all of which require more computational intelligence. We discuss implications and design directions for more intelligent coaching CA in health.

著者
Elliot G. Mitchell
Geisinger Health, Danville, Pennsylvania, United States
Pooja M. Desai
Columbia University Irving Medical Center, New York, New York, United States
Arlene Smaldone
Columbia University, New York, New York, United States
Andrea Cassells
Clinical Directors Network, New York, New York, United States
Jonathan N.. Tobin
Clinical Directors Network (CDN), New York, New York, United States
David Albers
University of Colorado Anschutz Medical Center, Aurora, Colorado, United States
Matthew Levine
Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States
Lena Mamykina
Columbia University, New York, New York, United States
DOI

10.1145/3706598.3714404

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714404

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Eating and Digital Health

G401
7 件の発表
2025-05-01 01:20:00
2025-05-01 02:50:00
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