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Currently submitted to: JMIR Research Protocols

Date Submitted: Aug 3, 2026

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Using Momentary Measures to Understand Physical Activity Adoption and Maintenance: A mHealth Research Protocol

  • Neng Wan; 
  • Won Byun; 
  • Ming Wen; 
  • Emre Ertin; 
  • Jeff Phillips; 
  • Nia Aitaoto; 
  • Simon Brewer; 
  • David Wetter

ABSTRACT

Physical inactivity is prevalent among US adults and is related to various health disparities. The search for effective policies and interventions to promote physical activity (PA) is severely hampered by the paucity of research on the mechanisms underlying PA behavioral change. This paper describes a research protocol using mHealth technology to examine the influence of contextual/environmental factors and acute momentary precipitants on PA adoption and maintenance among US Pacific Islanders. The study is guided by an overarching conceptual framework derived from models of the social and environmental determinants of health, social cognitive theories of behavior change, and prior empirical findings. Participants will be assessed using real-time, field-based, state-of-the-art methodologies consisting of MotionSense, ecological momentary assessment, and GPS. MotionSense tracks behavioral and physiologic data in real-time and can objectively detect PA behaviors of participants. GPS permits real-time mapping of an individual’s space-time trajectories and relevant environmental exposures/characteristics (e.g., proximity to PA facilities; neighborhood safety) using geographic information system data. Principal outcomes of interest are PA adoption and PA maintenance. This research is among the first to combine objective and momentary indices of PA, and key environmental influences in PA behavior studies. The comprehensive, multi-method approach addresses two longstanding limitations in PA research: the reliance on self-reported outcome measures and the use of static residential locations as proxies for neighborhood exposure. In addition, this study is among the first to apply dynamic prediction models, a novel statistical approach well suited to the high-frequency, intensive longitudinal data generated by real time mHealth assessment. The findings will provide actionable evidence to inform policies and interventions aimed at reducing PA-related health disparities among Pacific Islanders and other racial/ethnic groups that suffer from similar health problems.


 Citation

Please cite as:

Wan N, Byun W, Wen M, Ertin E, Phillips J, Aitaoto N, Brewer S, Wetter D

Using Momentary Measures to Understand Physical Activity Adoption and Maintenance: A mHealth Research Protocol

JMIR Preprints. 03/08/2026:108686

DOI: 10.2196/preprints.108686

URL: https://preprints.jmir.org/preprint/108686

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