Initial Proposal Abstract: 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.

Outcomes:

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  Publication: Reinforcement Learning on Dyads to Enhance Medication AdherenceJune 23, 2025
  Authors: Ziping Xu, Hinal Jajal, Sung Won Choi, Inbal Nahum-Shani, Guy Shani, Alexandra M. Psihogios, Pei-Yao Hung, Susan A. Murphy Abstract Medication adherence is critical for the recovery of adolescents and young adults (AYAs) who have undergone hematopoietic cell transplantation. However, maintaining adherence is challenging for AYAs after hospital discharge,… Read more: Publication: Reinforcement Learning on Dyads to Enhance Medication Adherence
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  Publication: Causal Directed Acyclic Graph-informed Reward DesignJune 3, 2025
  Authors: Luton Zou, Ziping Xu, Daiqi Gao, Susan Murphy Abstract It is well known that in reinforcement learning (RL) different reward functions may lead to the same optimal policy, while some reward functions can be substantially easier to learn. In this paper, we propose a framework for reward design by… Read more: Publication: Causal Directed Acyclic Graph-informed Reward Design
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  Publication: Digital Twins for Just-in-Time Adaptive Interventions (JITAI-Twins): A Framework for Optimizing and Continually Improving JITAIsMay 9, 2025
  Authors: Asim H. Gazi, Daiqi Gao, Susobhan Ghosh, Ziping Xu, Anna Trella, Predrag Klasnja, Susan A. Murphy Abstract Just-in-time adaptive interventions (JITAIs) are nascent precision medicine systems that extend personalized healthcare support to everyday life. A challenge in designing JITAIs is that personalized support often involves sophisticated decision-making algorithms. These… Read more: Publication: Digital Twins for Just-in-Time Adaptive Interventions (JITAI-Twins): A Framework for Optimizing and Continually Improving JITAIs
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  Poster Presentation: a2 National SymposiumApril 4, 2025
  Title: A Digital Dyadic Coach to Promote Oral Health Self-Care in Older Adults Authors: Guy Shani, Vivek Shetty, Jenin Alcaraz, Susan A Murphy, Inbal Billie Nahum-Shani
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  Oral Presentation: NIA workshop – Leveraging Adaptive Technology (“Just-in-Time”) Interventions for Aging and Alzheimer’s Disease and Alzheimer’s Disease-related DementiasOctober 16, 2024
  Dr. Inbal Billie Nahum-Shani (PI) presented work from this pilot project during a talk titled “Adaptive interventions and JITAIs as decision policies: What and why?” as part of Session 1 – Digital adaptive interventions: decision-focused evidence production held on October 16, 2024. Source: NIA Event Page