Designing and Deploying Robotic Companions to Improve Human Psychological Wellbeing
Name
jeong-sooyeon-PHD-MAS-2022-thesis.pdf
Description
Thesis PDF
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15.86 MB
Format
Adobe PDF
Checksum (MD5)
f922f009c9693d7657f96bd00f9a8489
Author(s)
Jeong, Sooyeon
Advisor(s)
Breazeal, Cynthia
Date Issued
September 2022
Publisher
Massachusetts Institute of Technology
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 intervention tasks. This thesis presents social robots that deliver interactive positive psychology interventions and build rapport with people over time as helpful companions 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.
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
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