IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i4p2267-d751348.html
   My bibliography  Save this article

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

Author

Listed:
  • Donna Spruijt-Metz

    (Center for Economic and Social Research, Department of Psychology, University of Southern California, Los Angeles, CA 90089, USA)

  • Benjamin M. Marlin

    (Manning College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, MA 01003, USA)

  • Misha Pavel

    (Khoury College of Computer Sciences, Northeastern University, Boston, MA 02115, USA
    Bouve College of Health Sciences, Northeastern University, Boston, MA 02115, USA)

  • Daniel E. Rivera

    (Control Systems Engineering Laboratory, School for Engineering of Matter, Transport, Energy, Arizona State University, Tempe, AZ 85287, USA)

  • Eric Hekler

    (Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, CA 92093, USA
    Design Laboratory, University of California, San Diego, CA 92093, USA
    Center for Wireless and Population Health Systems, University of California, San Diego, CA 92093, USA)

  • Steven De La Torre

    (Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90032, USA)

  • Mohamed El Mistiri

    (Control Systems Engineering Laboratory, School for Engineering of Matter, Transport, Energy, Arizona State University, Tempe, AZ 85287, USA)

  • Natalie M. Golaszweski

    (Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, CA 92093, USA
    The VA San Diego Healthcare System, San Diego, CA 92161, USA)

  • Cynthia Li

    (Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90032, USA)

  • Rebecca Braga De Braganca

    (Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90032, USA)

  • Karine Tung

    (Manning College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, MA 01003, USA)

  • Rachael Kha

    (Control Systems Engineering Laboratory, School for Engineering of Matter, Transport, Energy, Arizona State University, Tempe, AZ 85287, USA)

  • Predrag Klasnja

    (School of Information, University of Michigan, Ann Arbor, MI 48109, USA)

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 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.

Suggested Citation

  • Donna Spruijt-Metz & Benjamin M. Marlin & Misha Pavel & Daniel E. Rivera & Eric Hekler & Steven De La Torre & Mohamed El Mistiri & Natalie M. Golaszweski & Cynthia Li & Rebecca Braga De Braganca & Kar, 2022. "Advancing Behavioral Intervention and Theory Development for Mobile Health: The HeartSteps II Protocol," IJERPH, MDPI, vol. 19(4), pages 1-22, February.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:4:p:2267-:d:751348
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/4/2267/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/4/2267/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Audrey Boruvka & Daniel Almirall & Katie Witkiewitz & Susan A. Murphy, 2018. "Assessing Time-Varying Causal Effect Moderation in Mobile Health," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(523), pages 1112-1121, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    2. Iavor Bojinov & David Simchi-Levi & Jinglong Zhao, 2023. "Design and Analysis of Switchback Experiments," Management Science, INFORMS, vol. 69(7), pages 3759-3777, July.
    3. Davide Viviano & Jelena Bradic, 2021. "Dynamic covariate balancing: estimating treatment effects over time with potential local projections," Papers 2103.01280, arXiv.org, revised Jan 2024.
    4. Yuqian Zhang & Weijie Ji & Jelena Bradic, 2021. "Dynamic treatment effects: high-dimensional inference under model misspecification," Papers 2111.06818, arXiv.org, revised Jun 2023.
    5. Ashesh Rambachan & Neil Shephard, 2019. "Econometric analysis of potential outcomes time series: instruments, shocks, linearity and the causal response function," Papers 1903.01637, arXiv.org, revised Feb 2020.
    6. Shi, Chengchun & Wan, Runzhe & Song, Ge & Luo, Shikai & Zhu, Hongtu & Song, Rui, 2023. "A multiagent reinforcement learning framework for off-policy evaluation in two-sided markets," LSE Research Online Documents on Economics 117174, London School of Economics and Political Science, LSE Library.
    7. Hailin Li & Fengxiao Fan & Yan Sun & Weigang Wang, 2022. "Low-Carbon Action in Full Swing: A Study on Satisfaction with Wise Medical Development," IJERPH, MDPI, vol. 19(8), pages 1-17, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:4:p:2267-:d:751348. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.