Interactive AI Routines for Pain Symptoms and Loneliness in Older Adults

Pain consists of biological, psychological, and sociological elements that are influenced by the aging process. Pain management in older adults may be improved by multimodal strategies that impact the biopsychosocial model. Chronic musculoskeletal pain in older adults is often linked with social isolation which limits the use of in-person nonpharmacologic therapies. The purpose of this study was to compare two interactive routines delivered with artificial intelligence (AI) on pain severity, pain interference, and other outcomes in older adults with chronic musculoskeletal pain that live alone.

Adults 60 years of age and older were recruited, enrolled, and randomly assigned to the conversational voice assistant-standard or the conversational voice assistant-enhanced (CVA-E) group. Participants interacted with routines twice a day and as needed for 12 weeks in their homes. Self-reported pain and pain-related outcome data were collected at baseline and postintervention.

A sample of N = 50 participants engaged with the interactive voice assistant routines twice daily. After 12 weeks, the participants self-reported decreased scores in pain interference, loneliness, and depression. Self-reported depression scores were significantly reduced in both intervention groups. There was a statistically significant decrease in self-reported loneliness reported by older adults in the CVA-E group.

The experience of pain can be detrimental to older adults, especially when they live alone or are socially isolated. The preliminary findings from this study suggest that prescribed routines delivered with an AI voice assistant may encourage older adults' engagement with nonpharmacologic biopsychosocial strategies, and influence pain interference in older adults. There is a need to continue exploring personalized and biopsychosocial tailored routines delivered with technology and their impact on pain and other pain-related outcomes.