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KINGSTON, R.I. — Nov. 3, 2025 — By the year 2030, more than one-quarter of Americans will be 65 or older, 80% of whom will be living with one or more chronic disease. At the same time, many older adults find themselves living alone, which creates unique physical, psychological, and social challenges that are often overlooked without daily support.

University of Rhode Island College of Nursing Associate Professor Jung Eun Lee aims to empower older adults to help them better manage their own health care, using innovative chatbot-based technology. The Self-Management Intervention for heaLthy LifE (SMILE) chatbot is a web-based, personalized symptom self-management tool built on Microsoft Azure Health Bot. The SMILE prototype guides users through brief daily check-ins about how they’re feeling, physically and emotionally, and provides tailored feedback and health tips. It offers short, evidence-based suggestions on topics such as managing fatigue, improving sleep, staying active, and maintaining emotional well-being.

“As the aging population grows, so does the number of individuals living with multiple chronic conditions,” Lee said. “Older adults living alone often manage several health problems such as diabetes, hypertension, arthritis, and heart disease, while coping with fatigue, pain, sleep problems, and complex medication routines. Loneliness and social isolation are also common, and can worsen both physical and mental health, especially for those in low-income settings. Yet much of today’s research still treats one condition at a time, rather than addressing the complex realities of multimorbidity.”

To ensure the study reached individuals who face the greatest barriers to care, Lee recruited 35 older adults through a local public housing authority to participate in surveys and focus group discussions exploring their symptom experiences and technology needs. Based on those findings, user testing of the SMILE prototype was conducted with 10 participants, who were provided tablets for convenient access to the program. During the five-day period, participants were encouraged to check in at least twice a day to register their symptoms and record how they were feeling. The chatbot guided users through brief questions about symptoms and mood, and responded with simple, tailored suggestions related to healthy habits, emotional support, and symptom awareness. 

“While this prototype did not make medical diagnoses, it was designed to help users reflect on their symptoms, build awareness, and reinforce healthy routines—a core part of self-management for people with multiple chronic conditions,” Lee said. 

Participants described the chatbot as “helpful,” “educational,” and “available 24/7.” They noted it was intuitive and easy to follow.

Participants also offered suggestions to enhance usability, including larger buttons, clearer navigation options, and more in-depth training at the beginning. Features such as medication reminders and goal setting for physical activity will be added in the refined version, based on their suggestions. 

“The project generated meaningful insights into the lived experiences, technology engagement, and self-management needs of older adults living alone with multimorbidity in low-income housing,” Lee said. “Overall, participants found the chatbot motivating and easy to use, and many reported learning something new about their health. These results establish a strong foundation for a future clinical trial to evaluate the impact of AI-supported symptom management on health outcomes and quality of life.”