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Automatic topic selection for long-term interaction with embodied conversational agents in health coaching: A
Tessa Beinema1,2, Harm Op den Akker1,2,3, Marian Hurmuz1,2
1eHealth Group, Roessingh Research and Development, Enschede, the Netherlands.
Embodied Conversational Agents (ECAs) in health coaching can automatically suggest topics, leading to user engagement comparable to user-selected topics. This approach is perceived as natural and accepted by users.
Area of Science:
- Human-Computer Interaction
- Digital Health
- Artificial Intelligence in Healthcare
Background:
- Embodied Conversational Agents (ECAs) serve as virtual coaches in health applications.
- Enhancing user engagement with virtual coaches is crucial for effective health coaching.
- Tailored coaching dialogues can potentially improve user interaction with ECAs.
Purpose of the Study:
- To investigate if automatically suggested topics by an ECA increase user engagement.
- To determine if ECAs suggesting topics lead to longer interaction sessions.
- To assess user acceptance of automatically tailored coaching dialogues.
Main Methods:
- A Micro-Randomized Trial (MRT) compared two ECA interaction conditions: coach-suggested topics vs. user-selected topics.
- Participants interacted with the ECA in a health coaching application for 4-8 weeks in their daily lives.
- Random assignment determined the interaction type for each user session.
Main Results:
- 82 participants completed 1011 interactions across two study rounds.
- Interactions initiated by the coach showed similar duration to user-initiated topics.
- Topic suggestions by the ECA had a high acceptance rate (71.1% overall, 75.8% for coaching topics).
Conclusions:
- Automatically tailoring conversation topics by ECAs is perceived as a natural interaction flow.
- Future research should refine ECA topic suggestion engines and explore tailoring ECA initiative and coaching approach.
- This study supports the integration of proactive, tailored dialogue strategies in virtual health coaching.
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