SBIR/STTR Research Award
YayaGuide: AI-Enabled Personalized Training for Caregivers of Older Adults with ADRD
Award amount
$505,042Program and phase
SBIR · Phase IAward year
2025Award details
- Awarding agency
- Department of Health and Human Services
- Branch
- National Institutes of Health
- Recipient company
- CAREYAYA HEALTH TECHNOLOGIES INC
- Proposal award date
- 2025-09-22
- Contract end date
- 2026-09-21
- UEI
- E9FAWBDDM2D4
- Solicitation number
- PAS22-196
- Topic code
- NIA
Research abstract
SUMMARY CareYaya is developing YayaGuide, a personalized, artificial intelligence (AI)-driven training tool for caregivers of individuals with Alzheimer's disease and related dementias (AD/ADRD). The growing burden of AD/ADRD on individuals, families, and the healthcare system is compounded by a shortage of caregivers and inadequate training opportunities. While existing educational resources and caregiver training programs offer some support, they often fail to address the unique needs and challenges faced by this population. Barriers to access, lack of personalization, and low adoption rates limit the effectiveness of traditional training methods. The YayaGuide prototype app directly addresses this critical need by offering a personalized, AI-powered training platform designed to empower a new generation of caregivers. By leveraging the technological familiarity and engagement of Generation Z, YayaGuide fills a crucial gap in caregiver resources. This approach not only tackles the immediate shortage of skilled caregivers but also fosters early career development in healthcare and promotes the integration of technology into AD/ADRD caregiving. This project uniquely integrates scientific insights on multi-modal caregiver education with cutting-edge AI capabilities. The prototype utilizes a micro-learning curriculum backed by evidence-based best practices in dementia care, and a conversational agent supports users through training by providing personalized feedback and suggestions. Machine learning algorithms adapt content to users' demonstrated competencies, while mobile delivery promotes engagement by fitting into caregivers’ busy routines. Iterative optimization of the interface and content, with real-world testing and a focus on appealing to all age groups and caregiver skill levels, distinguishes it from existing platforms. Its advanced approach promises to significantly enhance knowledge retention, engagement, and adaptability to the evolving demands of caregiving, making it a valuable tool in addressing the challenges posed by AD/ADRD in an aging population. For the proposed Phase I project, we will collect quantitative and qualitative data from diverse age groups with limited caregiving experience to refine our YayaGuide prototype into a beta version suitable for universal accessibility. Successful completion of this work will enable a Phase II program focused on integrating additional features, such as support for multiple languages, educational content on caregiver wellness and health disparities, peer- to-peer learning capabilities, and built-in notifications to encourage regular app use. Ultimately, YayaGuide aims to equip caregivers with the knowledge and skills necessary to provide high-quality care confidently.
Technology keywords
Not reported
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