Abstract
Background: Recent advances in mobile and wearable technologies have led to new forms of interventions, called “Just-in-Time Adaptive Interventions” (JITAI). JITAIs interact with the individual at the most appropriate time and provide the most appropriate support depending on the continu-ously acquired Intensive Longitudinal Data (ILD) on participant physiology, behavior, and contexts. These advances raise an important question: How do we model these data to better understand and intervene on health behaviors? The HeartSteps II study, described here, is a Micro-Randomized Trial (MRT) intended to advance both intervention development and theory-building enabled by the new generation of mobile and wearable technology. Methods: The study involves a year-long deployment of HeartSteps, a JITAI for physical activity and sedentary behavior, with 96 sedentary, overweight, but otherwise healthy adults. The central purpose is twofold: (1) to support the development of modeling approaches for operationalizing dynamic, mathematically rigorous theories of health behavior; and (2) to serve as a testbed for the development of learning algorithms that JITAIs can use to individualize intervention provision in real time at multiple timescales. Discussion and Conclusions: We outline an innovative modeling paradigm to model and use ILD in real-or near-time to individually tailor JITIAs.
Original language | English (US) |
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Article number | 2267 |
Journal | International journal of environmental research and public health |
Volume | 19 |
Issue number | 4 |
DOIs | |
State | Published - Feb 1 2022 |
Externally published | Yes |
Keywords
- Behavioral health
- Digital health
- Intensive longitudinal data
- MHealth
- Mobile Health
- New technologies
- Physical activity
- Psychosocial theory
- Real-time interventions
ASJC Scopus subject areas
- Pollution
- Public Health, Environmental and Occupational Health
- Health, Toxicology and Mutagenesis