Awardee Organization(s): Weill Cornell Medicine
Principal Investigator(s): Nili Solomonov, PhD | Logan Grosenick, PhD
Official Project Title: Scalable subtyping for personalized assessment of late-life social disconnection
AITC Partner: PennAITech
Website(s): https://www.solomonovlab.com
Social disconnection is a growing public health crisis in the US, with half of adults reporting social isolation. It predicts accelerated brain aging, poor adherence to medical care, and decline in cognition and daily functioning. Still, there are no gold- standard, evidence-based methods to assess social disconnection in healthy older adults, highlighting the need for new approaches.
Here, we propose SOCIAL-Q (“Scalable Online Classification and Individual Assessment for Loneliness Quantification”): a scalable tool for quantification and classification of an individual’s social-emotional profile and their risk of social disconnection. This approach will provide a scalable, rapid, and precise assessment of individuals’ social-emotional functioning. It will also guide development of scalable interventions to increase social connectedness and improve well-being in healthy older adults.
To achieve this goal, we will leverage exciting developments in machine learning and computer vision including “large language models” (LLMs) for speech tracking and emotion detection from vocal prosody. We will combine these advances with multimodal subtyping methods we developed to design an automated AI-powered tool that will estimate an individual’s socio-emotional profile based on a brief multimodal assessment.
Findings from SOCIAL-Q will inform scalable, personalized, interventions aimed at increasing social connectedness that can be delivered in community settings to healthy adults (e.g., senior centers).