This study evaluates the efficacy of a smartphone-based multi-domain intervention designed to promote healthy aging and prevent cognitive decline in older adults. Building on preliminary findings that automated alerts improved exercise, sleep and nutrition-thereby mediating enhanced cognitive performance-we developed a dedicated application that integrates longitudinal Fitbit data (activity, sleep, and nutrition) with daily interactive dialogues powered by Generative AI (LLM). A six-month Randomized Controlled Trial (RCT) will be conducted with 300 healthy participants aged 65 and older. The primary objective is to analyze how these digital interventions influence health outcomes, particularly cognitive and motor functions. Furthermore, we aim to construct a predictive mathematical model to estimate health states based on wearable data streams. Finally, the study will assess the potential for scalability to facilitate the large-scale social implementation of this digital health service.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
NONE
Enrollment
300
Multi-domain App Intervention: Participants receive a dedicated smartphone application integrated with Fitbit. The app provides guidance on exercise, sleep, and nutrition, and features daily interactive dialogues powered by Generative AI (LLM) to promote health engagement.
Standard Care: Participants may receive standard health information without the specialized multi-domain app or AI dialogue features.
GSFS, The University of Tokyo
Kashiwa, Chiba, Japan
RECRUITINGCognitive Function
MoCA
Time frame: Baseline and 6 months
Cognitive function
MMSE
Time frame: Baseline and 6 months
Cognitive function
SAGE (Self-Administered Gerocognitive Examination)
Time frame: Baseline and 6 months
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