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Advancing Behavioral Intervention and Theory Development for Mobile Health: The HeartSteps II Protocol

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 continuously acquir...

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Autores principales: Spruijt-Metz, Donna, Marlin, Benjamin M., Pavel, Misha, Rivera, Daniel E., Hekler, Eric, De La Torre, Steven, El Mistiri, Mohamed, Golaszweski, Natalie M., Li, Cynthia, Braga De Braganca, Rebecca, Tung, Karine, Kha, Rachael, Klasnja, Predrag
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8872509/
https://www.ncbi.nlm.nih.gov/pubmed/35206455
http://dx.doi.org/10.3390/ijerph19042267
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author Spruijt-Metz, Donna
Marlin, Benjamin M.
Pavel, Misha
Rivera, Daniel E.
Hekler, Eric
De La Torre, Steven
El Mistiri, Mohamed
Golaszweski, Natalie M.
Li, Cynthia
Braga De Braganca, Rebecca
Tung, Karine
Kha, Rachael
Klasnja, Predrag
author_facet Spruijt-Metz, Donna
Marlin, Benjamin M.
Pavel, Misha
Rivera, Daniel E.
Hekler, Eric
De La Torre, Steven
El Mistiri, Mohamed
Golaszweski, Natalie M.
Li, Cynthia
Braga De Braganca, Rebecca
Tung, Karine
Kha, Rachael
Klasnja, Predrag
author_sort Spruijt-Metz, Donna
collection PubMed
description 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 continuously 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.
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spelling pubmed-88725092022-02-25 Advancing Behavioral Intervention and Theory Development for Mobile Health: The HeartSteps II Protocol Spruijt-Metz, Donna Marlin, Benjamin M. Pavel, Misha Rivera, Daniel E. Hekler, Eric De La Torre, Steven El Mistiri, Mohamed Golaszweski, Natalie M. Li, Cynthia Braga De Braganca, Rebecca Tung, Karine Kha, Rachael Klasnja, Predrag Int J Environ Res Public Health Protocol 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 continuously 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. MDPI 2022-02-17 /pmc/articles/PMC8872509/ /pubmed/35206455 http://dx.doi.org/10.3390/ijerph19042267 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Protocol
Spruijt-Metz, Donna
Marlin, Benjamin M.
Pavel, Misha
Rivera, Daniel E.
Hekler, Eric
De La Torre, Steven
El Mistiri, Mohamed
Golaszweski, Natalie M.
Li, Cynthia
Braga De Braganca, Rebecca
Tung, Karine
Kha, Rachael
Klasnja, Predrag
Advancing Behavioral Intervention and Theory Development for Mobile Health: The HeartSteps II Protocol
title Advancing Behavioral Intervention and Theory Development for Mobile Health: The HeartSteps II Protocol
title_full Advancing Behavioral Intervention and Theory Development for Mobile Health: The HeartSteps II Protocol
title_fullStr Advancing Behavioral Intervention and Theory Development for Mobile Health: The HeartSteps II Protocol
title_full_unstemmed Advancing Behavioral Intervention and Theory Development for Mobile Health: The HeartSteps II Protocol
title_short Advancing Behavioral Intervention and Theory Development for Mobile Health: The HeartSteps II Protocol
title_sort advancing behavioral intervention and theory development for mobile health: the heartsteps ii protocol
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8872509/
https://www.ncbi.nlm.nih.gov/pubmed/35206455
http://dx.doi.org/10.3390/ijerph19042267
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