CHS: Large: Collaborative Research: Participatory Design and Evaluation of Socially Assistive Robots for Use in Mental Health Services in Clinics and Patient Homes

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A significant concern in the United States relates to mental health disorders, especially depression; the National Institute of Mental Health (NIMH) has estimated that 17.3 million adults aged 18 or older (7.1% of the adult population in the U.S.) had at least one major depressive episode in 2017. The primary goal of this project is to enable patients and clinicians working together with researchers to design a socially assistive robot to provide support for, and as an intervention to alleviate the symptoms of, depression. The robot, Therabot, currently takes the form of a dog and is intended to serve as a pet-like companion. The project will allow both patients and clinicians to customize the capabilities and behaviors of the robot in order to improve patient health and well-being. The effectiveness of the modified robots will be evaluated in clinical settings and by means of longer-term use in patient homes. Project outcomes will include advances in healthcare robotics and improvements in human-robot interaction, thanks to a combination of onboard sensors that provide additional information to clinicians along with artificial intelligence to customize the interactions of the robot with the patient. This activity is also expected to transform mental healthcare interventions, and to reduce healthcare costs for mental health concerns by allowing many patients to remain in their homes longer with the aid of their assistive support robot. This research topic is of interest to a diversity of students, as well as clinical practitioners, and will promote educational training and opportunities in the areas of science, technology, engineering, and mathematics.This project will employ Participatory Design (PD) methods to develop an adaptable socially assistive robot platform by extending the features and capabilities of Therabot. Appropriate therapeutic interventions will be identified and their effectiveness evaluated using this platform to address the needs of individuals diagnosed with depression. The main research contributions are to apply PD methods to socially assistive robots for mental health with particular focus on bridging therapy in clinical and home settings, to further the technical development of adaptable robotic systems, and to provide an extension to the Interactive Social Engagement Architecture and Toolkit for long-term interaction outside of the laboratory. The project will develop PD activities to expand the design of Therabot which, unlike off-the-shelf systems, can be amended to suit the changing needs and preferences of diverse patients and clinicians over time.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.