Abstract
We discuss a large research project aimed at building socially expressive virtual health agents or assistants (VHA) that can deliver brief motivational interventions (BMI) for behavior change, in a communication style that individuals and patients not only accept, but also find emotionally supportive and socially appropriate. Because of their well-defined sequential structure, BMIs lend themselves well to automation, and are adaptable to address a variety of target behaviors, from obesity, to alcohol and drug use, to lack treatment adherence, among others. We discuss the advantages that VHAs provide for the delivery of health interventions. We describe components of our intelligent agent architecture that enables our virtual health agents to dialogue with users in realtime while delivering the appropriate intervention based on the patient’s specific needs at the time. We conclude by identifying open research challenges in developing virtual health agents.
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We use the term evidence-based as most scholars in medicine and healthcare seem to agree that the evidence-based decision-making process integrates (1) best available research evidence, (2) practitioner expertise and other available resources, and (3) the characteristics, needs, values, and preferences of those who will be affected by the intervention [24]
It is important to note that, unlike avatars that are representation of the user in a virtual environment controlled or tele-operated by the user, IVAs are autonomous entities capable of making decisions and of interacting with users
It is important to note that our system can be adapted to any type of brief motivational intervention, e.g. against obesity.
RL raises an individuals’ awareness about their at-risk behavior(s)—an initial important step toward behavior change
We use the SightCorp off-the-shelf face reader for detecting emotional facial expressions
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Part of the research described in this article was developed with funding from the National Science Foundation, grant numbers HRD-0833093, IIP-1338922, IIP- 1237818, and IIS-1423260.
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Lisetti, C., Amini, R. & Yasavur, U. Now All Together: Overview of Virtual Health Assistants Emulating Face-to-Face Health Interview Experience. Künstl Intell 29, 161–172 (2015). https://doi.org/10.1007/s13218-015-0357-0
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DOI: https://doi.org/10.1007/s13218-015-0357-0