Evaluating Health Outcomes of AI-Based Fitness Wearables and App Programs in Older Adults Living Alone With Cognitive Decline

Conditions

• AI-Based Fitness
• Cognitive Decline
• Older Adults
• Older Adults With Cognitive Decline
• Physical Activity
• Physical Inactivity
• Wearables

Eligibility Criteria

Sex

ALL

Age

65 Years - N/A

Healthy Volunteers

Not accepted

Interventions

• Fitness app for self-efficacy — OTHER
  AI-driven personalized exercise prescription via a fitness app. This targets self-efficacy.
• Social network via app for social support — OTHER
  Participants will be provided access to a social network via app. This targets social support.
• Health education app targeting outcome expectations — OTHER
  Participants are provided with an app-based health education. This targets outcome expectations.

Study Details

The overarching goal of our research is to develop personalized and accessible healthy aging lifestyle interventions aimed at promoting physical activity (PA) and improving health among community-dwelling older adults living alone with cognitive decline (LACD). To achieve this goal, the purpose of this project is to determine whether wearable and app-based mHealth intervention component(s) will contribute to increased PA and improved health outcomes in older adults LACD. Our specific aims are to: identify and evaluate mHealth intervention components that practically and significantly contribute to enhanced mechanistic outcomes (e.g., self-efficacy, outcome expectations) and increased PA (primary outcome) in older adults LACD over a 6-month period; determine the optimal combinations of intervention components for future efficacy testing; elucidate the mechanism of behavioral change (MoBC) and potential outcomes of these intervention components, namely, the mediating effects of MoBC variables (e.g., self-efficacy, outcome expectations) on the relationship between intervention components and change in PA. The first two aims are primary and fully-powered. The third aim is exploratory. The aims will support a refined, data-driven intervention design for a subsequent larger trial.

Key Dates

First listed

Oct 6, 2025

Start date

Jun 8, 2026

Status verified

Jun 2026

Primary completion

Jun 8, 2028

Completion

Jun 8, 2028

Study Design

Enrollment

64 participants (estimated)

Allocation

RANDOMIZED

Intervention model

FACTORIAL

Primary purpose

PREVENTION

Arms

• Experimental: Access to all applications
  Condition 1: Participant are provided with the prescription application (application1), social application (application 2), and health tips application (application 3).
• Experimental: Access to application 1 & 2
  Condition 2: Participant are provided with the prescription application, social application, but they aren't provided with the health tips application.
• Experimental: Access to application 1 & 3
  Condition 3: Participant are provided with the prescription application, and they aren't provided with the social application, but they are provided with the health tips application.
• Experimental: Access to application 1 only
  Condition 4: Participant are provided with the prescription application, but aren't provided with the social application, and the health tips application.
• Experimental: Access to application 2 & 3
  Condition 5: Participant are not provided with the prescription application, but they are provided with the social application, and the health tips application.
• Experimental: Access to application 2 only
  Condition 6: Participant are not provided with the prescription application, but they are provided with the social application, and they aren't provided with the health tips application.
• Experimental: Access to application 3 only
  Condition 7: Participant are not provided with the prescription application, or the social application, but they are provided with the health tips application.
• No Intervention: No access to any application
  Condition 8: Participant are not provided with the prescription application, or the social application, or with the health tips application.

Primary Outcome Measure

Fitbit MVPA [ Time Frame: Baseline (i.e., pre-intervention), 3 months (mid-point), and 6 months (end-point). ]

Central Contacts

• Zan Gao, PhD
  865-974-7971
  [email protected]

Locations (2)

Find similar trials in Knoxville, TN

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