Designing and Deploying Robotic Companions to Improve Human Psychological Wellbeing
Author: Sooyeon Jeong
Submitted to the Program in Media Arts and Sciences, School of Architecture and Planning,on June 29, 2022, in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Media Arts and Sciences
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Abstract:
Globally, more than 264 million people of all ages are affected by depression, which
has become a leading cause of disability. Several interactive technologies for mental
health have been developed to make various therapeutic services more accessible and scalable. However, most are designed to engage users only within therapy and in-
tervention tasks. This thesis presents social robots that deliver interactive positive psychology interventions and build rapport with people over time as helpful compan-
ions to improve psychological wellbeing. Two long-term deployment studies explored and evaluated how these robotic agents could improve people’s psychological wellbeing in real-world contexts. In Study 1, a robotic coach provided seven positive psychology interventions for college students in on-campus dormitory settings and showed significant association with improvements in students’ psychological wellbeing, mood,and motivation to change. In Study 2, we deployed our robots in 80 people’s homes across the U.S. during the COVID-19 pandemic and evaluated the efficacy of a social robot that delivers wellbeing interventions as a peer-like companion rather than an expert coach. The companion-like robot was shown to be the most effective in building a positive therapeutic alliance with people and resulted in enhanced psychological wellbeing, improved readiness for change, and reduced negative affect. We further explored how traits, such as personality and age, influence the intervention outcomes and participants’ engagement with the robot. The two long-term in-the-wild studies offer valuable insights into design challenges and opportunities for companion AI agents that personalize mental health interventions and agent behaviors based on users’ traits and behavioral cues for better mental health outcomes.
