ArticleInternet interventions2022
Automatic topic selection for long-term interaction with embodied conversational agents in health coaching: A micro-randomized trial.
Article in Internet interventions, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 14 citations in OpenAlex.
- Embodied Intelligence Applications in Health Care Populations: Scoping Review.Journal of medical Internet research · 2026Article
- Multimodal Sentiment and Emotion Analysis Framework for Personalized Health Coaching Messages: Proof-of-Concept Study.JMIR formative research · 2026Article
- Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review.Journal of medical Internet research · 2024Review
- Participant Engagement in Microrandomized Trials of mHealth Interventions: Scoping Review.JMIR mHealth and uHealth · 2023Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionEmbodied Conversational Agents (ECAs) can be included in health coaching applications as virtual coaches. The engagement with these virtual coaches could be improved by presenting users with tailored coaching dialogues. In this article, we investigate if the suggestion of an automatically tailored topic by an ECA leads to higher engagement by the user and thus longer sessions of interaction.
methodsA Micro-Randomized Trial (MRT) was conducted in which two types of interaction with an ECA were compared: (a) the coach suggests a relevant topic to discuss, and (b) the coach asks the user to select a topic from a set of options. Every time the user would interact with the ECA, one of those conditions would be randomly selected. Participants interacted in their daily life with the ECA that was part of a multi-agent health coaching application for 4-8 weeks.
resultsIn two rounds, 82 participants interacted with the micro-randomized coach a total of 1011 times. Interactions in which the coach took the initiative were found to be of equal length as interactions in which the user was allowed to choose the topic, and the acceptance of topic suggestions was high (71.1% overall, 75.8% for coaching topics).
conclusionTailoring coaching conversations with ECAs by letting the coach automatically suggest a topic that is tailored to the user is perceived as a natural variation in the flow of interaction. Future research could focus on improving the novel coaching engine component that supports the topic selection process for these suggestions or on investigating how the amount of initiative and coaching approach by the ECA could be tailored.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.