Motivating users is an important task for virtual agents in behaviour chance support systems. In this study we present a system which generates motivational statements based on situation type, aimed at a virtual agent for Post-Traumatic Stress Disorder therapy. Using input from experts (n=13), we built a database containing what categories of motivation to use based on therapy progress and current user trust. A statistical analysis confirmed that we can significantly predict the category of statements to use. Using the database, we present a system that generates motivational statements. Because this system is based on expert data, it has the advantage of not needing large amounts of patient data. We envision that by basing the content directly on expert knowledge, the virtual agent can motivate users as a human expert would.
|Title of host publication||Intelligent Virtual Agents|
|Subtitle of host publication||17th International Conference, IVA 2017, Proceedings|
|Place of Publication||Cham|
|Number of pages||4|
|Publication status||Published - 2017|
|Event||IVA 2017: 17th International Conference on Intelligent Virtual Agents - Stockholm, Sweden|
Duration: 27 Aug 2017 → 30 Aug 2017
|Name||Lecture Notes in Computer Science|
|Period||27/08/17 → 30/08/17|
- Behavior change
- Virtual agent
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Dataset belonging to the paper: Generating Situation-based Motivational Feedback in a Post-Traumatic Stress Disorder E-health System