Investigators:
Inbal Billie Nahum-Shani, University of Michigan, d3center, Institute for Social Research
Vivek Shetty, UCLA
Guy Shani, Michigan State University
Susan A. Murphy, Harvard University

MassAITC Cohort: Year 3 (AD/ADRD)

This project seeks to develop a novel AI-powered digital tool to empower older adults with Alzheimer’s disease and related dementias (AD/ADRD) to engage in oral self-care in at-home settings. More than a mere digital assistant, this Dyadic Digital Coach (DDC) will leverage the untapped potential of dyadic relationships between older adults and their primary caregivers.

Central to the DDC is the creation of a bespoke Reinforcement Learning (RL) algorithm specifically designed for dyadic interactions. The AI-driven approach will continually adapt to each participant’s unique needs in real-time, thereby optimizing behavioral intervention strategies and fostering positive care partner-patient interactions.

First, a usability study with an existing app will collect digital biomarkers of Oral Hygiene Practices (OHPs) by AD/ADRD participants. This data will drive a participatory design process aimed at developing a new app specifically for older adults with AD/ADRD and their care partners.

Second, we will develop a new dyadic RL algorithm that will learn and adapt the delivery of digital prompts to both the targeted older adult and their care partner. This will involve developing variants of the RL algorithm and comparing their performance via simulation studies.