Collaborating Investigator:
Neng Wan, The University of Utah
Funding Status:
NIH/NCI
08/09/23 – 06/30/28
Associated with:
This project focuses on understanding how neighborhood environments, individual factors, and social history influence physical activity (PA) adoption and maintenance among sedentary Pacific Islander adults in Utah who experience significant health disparities.
This project will explore how neighborhood environments, individual factors, and social history impact physical activity (PA) adoption and maintenance among sedentary Pacific Islander adults in Utah. Pacific Islanders suffer from disparities in a variety of health problems such as obesity, cardiovascular diseases, diabetes, and cancer at several sites. Although physical activity is an effective way to reduce the risks of these health problems, Pacific Islander adults are generally less physically activity than non-Hispanic whites. The search for effective policies and interventions to promote PA among Pacific Islanders is severely hampered by the paucity of research on the mechanisms underlying PA behavioral change in this population. This Study will leverage mobile health technologies to capture PA and its key influences in real-time, addressing a critical gap in understanding PA behavior change within this high-risk, understudied population. The study aims to provide valuable insights into improving PA levels and reducing obesity and related health issues in this group. Additionally, the methodology and findings will offer broader perspectives on PA behavior for other racial/ethnic groups with high obesity and low PA levels.
CP12 utilizes MotionSense wrist bands from TR&D3 researchers have collaborated to develop an optimized version of the MotionSense activity band.
CP12 challenges TR&D3 in developing a self-contained version of MotionSense that implements computationally efficient micromarkers for real-time PA assessment and heart rate variability (HRV).
CP12 can collect PA in a multi-week study without a need for Internet connectivity together with raw data for extensive post-analysis, making it suitable for rural/remote populations.
This study is guided by an overarching conceptual framework derived from models of the social/environmental determinants of health, social cognitive theories of behavioral 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 track behavioral and physiologic data in real-time and can objectively detect PA behaviors and negative affect/stress of participants.
MotionSense sensor hardware and firmware is developed by TR&D3 researchers. Working in tandem with the project team, we have developed a version of the activity band that can store all the raw data for the study to enable a diverse set of post data analyses. In addition, in alignment of TR&D3 Aim 1, we have developed computationally efficient micromarker implementations of Physical activity measures. This allow the band in real-time assess physical activity and trigger EMAs at the mobile phone when moderate sustained activity is detected. Part of the project we will work in extending real-time measures of stress and arousal using heart rate variability metrics. This effort will significantly rely on using autoencoder structures optimized for the embedded hardware of MotionSense band, that gleans information from the raw PPG measures to create micromarkers from which HRV measures can be derived at the mobile phone. Implementing and validating of these real-time HRV measures against the post-processed PPG data will further our goals under Aim 1 of TR&D3. This collaboration has the potential to synergistically enhance both TR&D3’s as well as this Projects aims.
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