The YourMove Study: Optimizing Individualized and Adaptive mHealth Interventions Via Control Systems Engineering Methods

NCT ID: NCT05598996

Last Updated: 2024-08-15

Basic Information

• Recruitment Status: ACTIVE_NOT_RECRUITING
• Clinical Phase: NA
• Total Enrollment: 386 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2022-10-07
• Study Completion Date: 2025-08-09

Brief Summary

The purpose of this study is to determine the efficacy of a new digital health tool that uses a phone and smartwatch to encourage physical activity and increase weekly amounts of Moderate to Vigorous Physical Activity (MVPA) over 12 months among adults compared to a digital health intervention that mimics a standard of care corporate wellness program.

Detailed Description

Strong evidence indicates physical activity (PA) reduces risk of bladder, breast, colon, endometrium, esophagus, gastric, and renal cancer, and there is moderate evidence for lung cancer. Individuals aged 25+ who are inactive are at high risk of developing a variety of cancers. Unfortunately, only 1/3 of adults meet guidelines for PA; thus, they are an important group to target. In response, the investigators developed JustWalk, a modular adaptive mobile health (mHealth) intervention that makes daily N-of-1 adjustments to support PA for each person. JustWalk can perform N-of-1 adaptation based on our innovative use of control engineering methods, which the investigators call a control optimization trial (COT).

The YourMove study is a 12-month 2-arm randomized control trial (RCT) designed to assess the efficacy of COT methods in 386 adults aged 25+ who are inactive. The investigators will evaluate the differences in minutes/week of moderate-to-vigorous intensity PA (MVPA), measured via accelerometers, among the COT-optimized (intervention) vs. non-COT intervention designed in accordance with standard of care digital corporate wellness to support physical activity (control) groups at 12 months.

The YourMove Study uses a fully integrated system of modalities that include: 1) a popular consumer-level wearable (e.g., Fitbit Versa) and corresponding app (e.g., the Fitbit app); 2) daily process-level analyses done using the Fitbit Versa and ecological momentary assessment (EMA) measures rooted in social cognitive theory (SCT) constructs to promote behavior change; 3) a highly tailored text messaging system encouraging participants to achieve recommended minutes of physical activity: >150 minutes per week of moderate-to-vigorous physical activity (MVPA); and 4) a self-study tool called "Reflect", which is meant to support individuals in self-experimentation to identify strategies that work for them to fit regular MVPA into their lives. The consumer-level devices and app will be used to self-monitor behavior, and their data will be passively acquired in real-time. A variety of self-reported measures asked daily via EMA enables the measurement of psychosocial factors important for the development of a dynamical SCT model and produces ambitious yet achievable step goals that are adaptive to each individual. Algorithms will be used to automatically deliver text messages to support individually tailored goal setting, performance feedback, and goal review in a highly dynamic style that reflects participants' behavioral progress towards achieving a minimum goal of 150 min/week of MVPA.

Conditions

Inactivity, Physical; Sedentary Behavior

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: TREATMENT
• Blinding Strategy: DOUBLE

Study Groups

COT-Based Intervention

The COT-based intervention will include the following to improve both steps/day (move more), and improving minutes/week of MVPA (exercise): adaptive daily steps/day goal-setting plus feedback; positive reinforcement (i.e., points, which translate to gift cards), self-monitoring of both steps/day and min/week MVPA; education about MVPA sent via text message in both conditions; planning support for scheduling bouts of MVPA via SMS in both conditions; and motivational messages sent via SMS in both conditions, and the use of a self-experimentation tool (REFLECT), developed based on prior successful pilot efforts, focused on fostering effective self-regulatory capacities of individuals.

Group Type: EXPERIMENTAL

COT-Based Intervention

Intervention Type: BEHAVIORAL

The COT-based approach uses a controller that runs case-by-case dynamical systems simulations modeling based on answers to daily questions rooted in social cognitive theory to produce ambitious but achievable daily adaptive step goal recommendations. The process for the COT-based approach is as follows: Phase 1) 2-week measurement only; Phase 2) open-loop system identification experiment (meant to create individualized dynamical models for each participant); Phase 3) closed-loop experiment to optimize for PA initiation, and Phase 4) closed-loop experiment to optimize for PA maintenance.

Control

The non-COT approach was designed to be an equivalent to emerging standard of care options for digital health worksite wellness programs to increase PA (control) for a 12-month study period. Participants assigned to the non-COT-based (control) group will receive the latest Fitbit Versa smartwatch and will download the Fitbit smartphone app. Unlike the intervention group, the daily step goal and the accompanying number of points will be static (10,000 steps/day; 150 points/day, respectively). The goal will be delivered to participants via the standard Fitbit app features and points will be communicated via email. Participants will also receive a weekly PA goal (150 minutes of MVPA/per week) and the same accompanying motivational and informative texts that the intervention group receives. Control participants will not complete the physical activity and exercise reflection and planning exercise (Reflect).

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

COT-Based Intervention

The COT-based approach uses a controller that runs case-by-case dynamical systems simulations modeling based on answers to daily questions rooted in social cognitive theory to produce ambitious but achievable daily adaptive step goal recommendations. The process for the COT-based approach is as follows: Phase 1) 2-week measurement only; Phase 2) open-loop system identification experiment (meant to create individualized dynamical models for each participant); Phase 3) closed-loop experiment to optimize for PA initiation, and Phase 4) closed-loop experiment to optimize for PA maintenance.

Intervention Type: BEHAVIORAL

Eligibility Criteria

Inclusion Criteria

• Age 25-80 years old
• Intend to be available for a 12-month intervention
• Willing and able to attend 3 measurement visits over 12-months
• Willing and able to use a smartphone and text messaging
• Willing and able to use the wearable and corresponding app
• Willing and able to walk and engage in moderate-intensity physical activity
• Healthy enough to participate based on the Physical Activity Readiness Questionnaire
• BMI between 18-40 kg/m^2

Exclusion Criteria

• Psychiatric or medical conditions that prohibit compliance with the study protocol
• Enrolled in or planning to enroll in a physical activity program during the study period
• Those with a mechanical medical implant, such as a pacemaker

• Minimum Eligible Age: 25 Years
• Maximum Eligible Age: 80 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Arizona State University

OTHER

Sponsor Role: collaborator

University of Michigan

OTHER

Sponsor Role: collaborator

National Cancer Institute (NCI)

NIH

Sponsor Role: collaborator

Small Steps Labs, LLC

UNKNOWN

Sponsor Role: collaborator

University of California, San Diego

OTHER

Sponsor Role: lead

Responsible Party

Eric Hekler

Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Eric Hekler, PhD

Role: PRINCIPAL_INVESTIGATOR

University of California, San Diego

Daniel Rivera, PhD

Role: PRINCIPAL_INVESTIGATOR

Arizona State University

Locations

University of California San Diego

San Diego, California, United States

Countries

United States

References

Kim M, Mansour-Assi S, El Mistiri M, Park J, Banerjee S, Khan O, De La Torre S, Higgins M, Godino J, Patrick K, Nebeker C, Jain S, Klasnja P, E Rivera D, Hekler E. Optimizing and Testing an Individualized and Adaptive Physical Activity Digital Health Intervention: Protocol for a Control Optimization Trial Embedded Within a Randomized Controlled Trial. JMIR Res Protoc. 2025 Aug 15;14:e70599. doi: 10.2196/70599.

Reference Type: DERIVED

PMID: 40815836 (View on PubMed)

Mistiri ME, Khan O, Martin CA, Hekler E, Rivera DE. Data-Driven Mobile Health: System Identification and Hybrid Model Predictive Control to Deliver Personalized Physical Activity Interventions. IEEE Open J Control Syst. 2025;4:83-102. doi: 10.1109/ojcsys.2025.3538263. Epub 2025 Feb 4.

Reference Type: DERIVED

PMID: 40626117 (View on PubMed)

Other Identifiers

1R01CA244777-01A1

Identifier Type: NIH

Identifier Source: secondary_id

View Link

20733

Identifier Type: -

Identifier Source: org_study_id