Investigator:
Joseph Chung, Kinto
MassAITC Cohort: Year 2 (AD/ADRD)
Numerous peer-reviewed studies show that caregiver support interventions that engage directly with caregivers to address the burdens of ADRD caregiving, result in significantly improved outcomes for both caregivers and Persons Living With Dementia (PLWD) with lower care costs. However, most traditional caregiver interventions are highly labor intensive and difficult to scale, particularly to underserved and remote communities.
Like traditional support interventions, Kinto relies on human coaches to create trusted relationships. However, Kinto leverages technology, including a mobile app, asynchronous text messaging, personalized content, and remote video, to amplify the reach of its coaches. We believe that AI can further amplify efficiency, and as an initial step we seek to apply AI algorithms to the caregiver and coach conversations that take place through the platform.
During this pilot project period, we will apply Sentiment Analysis on text messaging between coaches and caregivers to identify and prioritize elevated risk situations for which a proactive intervention may be warranted and on peer-to-peer support group text messaging to identify both negative situations which may need moderation as well as positive interactions that merit praise and confirmation. In addition, we will apply generative large language models to produce editable coach response templates that can reduce the time and effort required in composing responses to caregiver messages. Both efforts will lead to increased scalability of the Kinto platform by enabling coaches to support more caregivers simultaneously.
Outcomes:
- Additional Funding
- New Product Versions
- We deployed the two main generative AI features to our production system where coaches can view strain assessment data and resource recommendations. We also created a repeatable framework for extracting and anonymizing caregiver data sets from the Kinto platform on demand.