ArticleJMIR research protocols2025
Optimizing and Testing an Individualized and Adaptive Physical Activity Digital Health Intervention: Protocol for a Control Optimization Trial Embedded Within a Randomized Controlled Trial.
Article in JMIR research protocols, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05598996 (The YourMove Study), which is not on this map. Cited by 4 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
The YourMove Study: Optimizing Individualized and Adaptive mHealth Interventions Via Control Systems Engineering Methods
Who cites it
4 citing papers in PubMed.
- Technology-Based Interventions for Physical Activity and Sedentary Behaviour in Adults: A Scoping Review.Journal of functional morphology and kinesiology · 2026Review
- Physical activity behavior pathway from intention to action in older adults: a structural equation model based on the multi-process action control framework.Frontiers in psychology · 2026Article
- Heterogeneity among exercise participants: latent profile analysis and differential persistence pathways based on the pressure-support-motivation (PSM) framework.Frontiers in public health · 2026Article
- Special Issue "Novel Strategies in the Development of New Therapies, Drug Substances and Drug Carriers, 3rd Edition".International journal of molecular sciences · 2025Article
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Authors and funding
15 authors.
Funding
Abstract
backgroundWhile effective physical activity (PA) interventions exist, interventions often work only for some individuals or only for a limited time. Thus, there is a need for digital health interventions that account for dynamic, idiosyncratic PA determinants to support each person's PA. We hypothesize that supporting individuals with their personal PA goals requires a personalized intervention that both supports each person in forming daily habits of walking more and develops personalized knowledge, skills, and practices regarding engaging in exercise routines. We operationalized these adaptive features via a digital health intervention called YourMove that uses a control systems approach to support personalized habit formation and a self-experimentation approach to develop personalized knowledge, skills, and practices.
objectiveThe primary aim is to evaluate differences in minutes of moderate to vigorous PA (MVPA) per week at 12 months comparing our personalized intervention, called YourMove, with an active control that is similar but without personalization of the intervention components and mimics best-in-class digital health worksite wellness programs.
methodsThe YourMove study is a 12-month randomized controlled trial that involves 386 inactive adults aged 25 to 80 years. All participants receive (1) a Fitbit Versa smartwatch and corresponding smartphone app; (2) weekly PA goal suggestions and feedback, behavior change strategies, and reminders via SMS text messaging; and (3) up to US $50 in incentives for reaching daily step goals. Participants randomized to the active control group, modeled after worksite wellness programs, receive all the elements described in addition to a static daily step goal and static point rewards. Participants randomized to the intervention group receive (1) a habit formation element with daily personalized step goals and personalized point rewards generated through a control optimization trial approach and (2) a knowledge, skill, and practice development element featuring a self-guided self-experimentation tool that helps individuals find strategies to improve MVPA. The primary outcome is objectively assessed weekly minutes of MVPA via an ActiGraph monitor.
resultsRecruitment began in October 2022 and concluded in August 2024. Data collection will conclude in August 2025, with results expected by early 2026.
conclusionsWe hypothesize that the intervention group will show greater improvement in MVPA than the active control group at 12 months. If the hypothesis is supported, this will provide compelling evidence to suggest that personalized and perpetually adaptive support can enhance PA more effectively than intervention elements commonly used in digital health worksite wellness programs. If the trial is successful, the results will provide justification to explore both the control optimization trial approach and self-experimentation approach for other complex, idiosyncratic, and dynamic behaviors such as weight management, smoking, or substance abuse.
trial registrationClinicalTrials.gov NCT05598996; https://clinicaltrials.gov/study/NCT05598996. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/70599.
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