Deploying a robotic positive psychology coach to improve college students’ psychological well-being

Despite the increase in awareness and support for mental health, college students’ mental health is reported to decline every year in many countries. Several interactive technologies for mental health have been proposed and are aiming to make therapeutic service more accessible, but most of them onl...

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Veröffentlicht in:User modeling and user-adapted interaction Jg. 33; H. 2; S. 571 - 615
Hauptverfasser: Jeong, Sooyeon, Aymerich-Franch, Laura, Arias, Kika, Alghowinem, Sharifa, Lapedriza, Agata, Picard, Rosalind, Park, Hae Won, Breazeal, Cynthia
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Dordrecht Springer Netherlands 01.04.2023
Springer Nature B.V
Schlagworte:
College students
Colleges & universities
Computer Science
Feasibility studies
Intervention
Management of Computing and Information Systems
Mental health
Motivation
Multimedia Information Systems
Psychological factors
Psychology
Qualitative analysis
Robotics
Robots
Students
User Interfaces and Human Computer Interaction
Well being
Socially assistive robot
Positive psychology
Well-being
ISSN:0924-1868, 1573-1391
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Zusammenfassung:Despite the increase in awareness and support for mental health, college students’ mental health is reported to decline every year in many countries. Several interactive technologies for mental health have been proposed and are aiming to make therapeutic service more accessible, but most of them only provide one-way passive contents for their users, such as psycho-education, health monitoring, and clinical assessment. We present a robotic coach that not only delivers interactive positive psychology interventions but also provides other useful skills to build rapport with college students. Results from our on-campus housing deployment feasibility study showed that the robotic intervention showed significant association with increases in students’ psychological well-being, mood, and motivation to change. We further found that students’ personality traits were associated with the intervention outcomes as well as their working alliance with the robot and their satisfaction with the interventions. Also, students’ working alliance with the robot was shown to be associated with their pre-to-post change in motivation for better well-being. Analyses on students’ behavioral cues showed that several verbal and nonverbal behaviors were associated with the change in self-reported intervention outcomes. The qualitative analyses on the post-study interview suggest that the robotic coach’s companionship made a positive impression on students, but also revealed areas for improvement in the design of the robotic coach. Results from our feasibility study give insight into how learning users’ traits and recognizing behavioral cues can help an AI agent provide personalized intervention experiences for better mental health outcomes
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ISSN:0924-1868
1573-1391
DOI:10.1007/s11257-022-09337-8