Literature DB >> 33326935

Comparing Methods to Identify Wear-Time Intervals for Physical Activity With the Fitbit Charge 2.

Sophie E Claudel, Kosuke Tamura, James Troendle, Marcus R Andrews, Joniqua N Ceasar, Valerie M Mitchell, Nithya Vijayakumar, Tiffany M Powell-Wiley.   

Abstract

There is no established method for processing data from commercially available physical activity trackers. This study aims to develop a standardized approach to defining valid wear time for use in future interventions and analyses. Sixteen African American women (mean age = 62.1 years and mean body mass index = 35.5 kg/m2) wore the Fitbit Charge 2 for 20 days. Method 1 defined a valid day as ≥10-hr wear time with heart rate data. Method 2 removed minutes without heart rate data, minutes with heart rate ≤ mean - 2 SDs below mean and ≤2 steps, and nighttime. Linear regression modeled steps per day per week change. Using Method 1 (n = 292 person-days), participants had 20.5 (SD = 4.3) hr wear time per day compared with 16.3 (SD = 2.2) hr using Method 2 (n = 282) (p < .0001). With Method 1, participants took 7,436 (SD = 3,543) steps per day compared with 7,298 (SD = 3,501) steps per day with Method 2 (p = .64). The proposed algorithm represents a novel approach to standardizing data generated by physical activity trackers. Future studies are needed to improve the accuracy of physical activity data sets.

Entities:  

Keywords:  mobile health; physical activity intervention; steps

Mesh:

Year:  2020        PMID: 33326935      PMCID: PMC8493649          DOI: 10.1123/japa.2020-0059

Source DB:  PubMed          Journal:  J Aging Phys Act        ISSN: 1063-8652            Impact factor:   1.961


  42 in total

1.  Accuracy of Wristband Activity Monitors during Ambulation and Activities.

Authors:  Ming-DE Chen; Chang-Chih Kuo; Christine A Pellegrini; Miao-Ju Hsu
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Review 2.  The Wild Wild West: A Framework to Integrate mHealth Software Applications and Wearables to Support Physical Activity Assessment, Counseling and Interventions for Cardiovascular Disease Risk Reduction.

Authors:  Felipe Lobelo; Heval M Kelli; Sheri Chernetsky Tejedor; Michael Pratt; Michael V McConnell; Seth S Martin; Gregory J Welk
Journal:  Prog Cardiovasc Dis       Date:  2016-02-26       Impact factor: 8.194

3.  Physical activity in U.S.: adults compliance with the Physical Activity Guidelines for Americans.

Authors:  Jared M Tucker; Gregory J Welk; Nicholas K Beyler
Journal:  Am J Prev Med       Date:  2011-04       Impact factor: 5.043

4.  Pedometer-measured physical activity and health behaviors in U.S. adults.

Authors:  David R Bassett; Holly R Wyatt; Helen Thompson; John C Peters; James O Hill
Journal:  Med Sci Sports Exerc       Date:  2010-10       Impact factor: 5.411

5.  "Spatial Energetics": Integrating Data From GPS, Accelerometry, and GIS to Address Obesity and Inactivity.

Authors:  Peter James; Marta Jankowska; Christine Marx; Jaime E Hart; David Berrigan; Jacqueline Kerr; Philip M Hurvitz; J Aaron Hipp; Francine Laden
Journal:  Am J Prev Med       Date:  2016-08-12       Impact factor: 5.043

6.  Accelerometer-Measured Physical Activity and Sedentary Behavior in Relation to All-Cause Mortality: The Women's Health Study.

Authors:  I-Min Lee; Eric J Shiroma; Kelly R Evenson; Masamitsu Kamada; Andrea Z LaCroix; Julie E Buring
Journal:  Circulation       Date:  2017-11-06       Impact factor: 29.690

7.  When a Step Is Not a Step! Specificity Analysis of Five Physical Activity Monitors.

Authors:  Sandra O'Connell; Gearóid ÓLaighin; Leo R Quinlan
Journal:  PLoS One       Date:  2017-01-13       Impact factor: 3.240

8.  Patterns of Fitbit Use and Activity Levels Throughout a Physical Activity Intervention: Exploratory Analysis from a Randomized Controlled Trial.

Authors:  Sheri J Hartman; Sandahl H Nelson; Lauren S Weiner
Journal:  JMIR Mhealth Uhealth       Date:  2018-02-05       Impact factor: 4.773

9.  Accuracy of consumer-level and research-grade activity trackers in ambulatory settings in older adults.

Authors:  Salvatore Tedesco; Marco Sica; Andrea Ancillao; Suzanne Timmons; John Barton; Brendan O'Flynn
Journal:  PLoS One       Date:  2019-05-21       Impact factor: 3.240

10.  Use of the Fitbit to Measure Adherence to a Physical Activity Intervention Among Overweight or Obese, Postmenopausal Women: Self-Monitoring Trajectory During 16 Weeks.

Authors:  Lisa Cadmus-Bertram; Bess H Marcus; Ruth E Patterson; Barbara A Parker; Brittany L Morey
Journal:  JMIR Mhealth Uhealth       Date:  2015-11-19       Impact factor: 4.773

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