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AI-Based Personalized Exercise Prescription Through Mobile Health on Physical Activity and Health Outcomes in Older Adults: A Feasibility Study

The University of Tennessee, Knoxville · NCT07768670

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Opens the official ClinicalTrials.gov record, with the study team’s contacts. Bored Studies doesn’t enroll anyone.

Key facts

Compensation
Not posted. Ask the study team before screening.
Who can join
Ages 65+ · All sexes
Healthy volunteers
Accepted
Study type
Interventional · Not applicable
Target enrollment
20
US sites recruiting
1
Study start
October 1, 2026
Record last updated
August 20, 2026

Status re-checked against ClinicalTrials.gov within the last 12 hours.

What the study is about

The purpose of this research is to investigate the feasibility, acceptability, appropriateness, and preliminary efficacy of a wearable and artificial intelligence-driven mobile application-based exercise prescription grounded in self-determination theory (SDT) and behavioral change techniques (BCTs) among older adults. As no data exists on the feasibility of AI-driven exercise programs grounded in SDT and multiple BCTs specifically for older adults, this will be a pioneering study to explore the feasibility of wearable and AI-driven exercise program protocols and the rates of acceptance and appropriateness of the exercise prescription intervention among older adults. In addition, this study will test the preliminary efficacy of the intervention on physical activity (PA), mental health, and quality of life. This study follows the National Institute of Health (NIH) stage model, and it represents stage 1b of the NIH stage model, which emphasizes the feasibility and actionable processes for delivering a new health intervention. Specifically, this study will: 1.Evaluate the research protocol feasibility of a wearable and AI-driven mobile application-based exercise prescription grounded in SDT and BCTs (of goal setting, self-monitoring, graded task, and demonstration) on older adults over 8 weeks 2. Evaluate the acceptability and appropriateness of a wearable, AI-driven, mobile application-based exercise prescription grounded in SDT and BCTs among older adults over 8 weeks. 3. Evaluate the preliminary impact of a wearable and AI-driven mobile application-based exercise prescription grounded in SDT and BCTs on older adult PA (steps per day and daily duration of light PA and Moderate-vigorous PA), sedentary time, sleep, mental health (depression and anxiety), and quality of life.

Being studied: Fitness app powered by AI and wearable device

Conditions: Feasibility Studies; Physical Activity; Mental Health (Depression); Anxiety; Quality of Life

Eligibility criteria

Copied from the official record. The study team makes the final decision at screening.

Show full criteria

Inclusion Criteria

  • Be aged 65 years or older.
  • Own a smartphone (Android or iOS) compatible with study applications.
  • Have reliable access to the internet or Wi-Fi.
  • Demonstrate basic digital literacy sufficient to operate a smartphone (e.g., ability to open applications, navigate simple interfaces, and follow on-screen instructions), with or without initial guidance from the research staff.
  • Be able to safely engage in physical activity, as determined by the Physical Activity Readiness Questionnaire for Everyone (PAR-Q+) or physician approval if indicated.
  • Report engaging in less than 150 minutes of moderate-to-vigorous physical activity (MVPA) per week.
  • Be able to communicate in English sufficiently to complete study procedures and assessments.

Exclusion Criteria

  • Are younger than 65 years of age.
  • Do not own a compatible smartphone (Android or iOS) or do not have reliable internet/Wi-Fi access.
  • Are deemed unable to safely participate in physical activity based on the screening process (including PAR-Q+, STEADI, and research staff assessment), or do not obtain required physician clearance when indicated.
  • Currently meet or exceed 150 minutes of moderate-to-vigorous physical activity (MVPA) per week.
  • Are unable to communicate in English sufficiently to understand study procedures, provide informed consent, or complete study-related assessments.
  • Have any medical, physical, or cognitive condition that, in the judgment of the research team, would make participation unsafe or prevent completion of study procedures.

Recruiting US locations

  • Kinesiology, Recreation, and Sport Studies (865) 974-3340 krss@utk.edu

    Knoxville, TN 37996-2700

    Site contact: John Oginni · (865) 974-3340 · joginni@vols.utk.edu

Study contacts (from the official record)

  • John Oginni, MS · 8659747971 · pael@utk.edu
All mental health studies in Tennessee →
AI-Based Personalized Exercise Prescription Through Mobile Health… (NCT07768670) | Bored Studies