Literature DB >> 33646135

Using Fitbit as an mHealth Intervention Tool to Promote Physical Activity: Potential Challenges and Solutions.

Guilherme M Balbim1, Spyros Kitsiou2, Sharmilee M Nyenhuis3, Isabela G Marques4, David X Marquez1, Darshilmukesh Patel5, Lisa K Sharp6.   

Abstract

Consumer-based physical activity (PA) trackers, also known as wearables, are increasingly being used in research studies as intervention or measurement tools. One of the most popular and widely used brands of PA trackers is Fitbit. Since the release of the first Fitbit in 2009, hundreds of experimental studies have used Fitbit devices to facilitate PA self-monitoring and behavior change via goal setting and feedback tools. Fitbit's ability to capture large volumes of PA and physiological data in real time creates enormous opportunities for researchers. At the same time, however, it introduces a number of challenges (eg, technological, operational, logistical), most of which are not sufficiently described in study publications. Currently, there are no technical reports, guidelines, nor other types of publications discussing some of these challenges and offering guidance to researchers on how to best incorporate Fitbit devices in their study design and intervention to achieve their research goals. As a result, researchers are often left alone to discover and address some of these issues during the study through "trial and error." This paper aims to address this gap. Drawing on our cumulative experience of conducting multiple studies with various Fitbit PA trackers over the years, we present and discuss various key challenges associated with the use of Fitbit PA trackers in research studies. Difficulties with the use of Fitbit PA trackers are encountered throughout the entire research process. Challenges and solutions are categorized in 4 main categories: study preparation, intervention delivery, data collection and analysis, and study closeout. Subsequently, we describe a number of empirically tested strategies used in 4 of our interventional studies involving participants from a broad range of demographic characteristics, racial/ethnic backgrounds, and literacy levels. Researchers should be prepared to address challenges and issues in a timely fashion to ensure that the Fitbit effectively assists participants and researchers in achieving research and outcome goals. ©Guilherme M Balbim, Isabela G Marques, David X Marquez, Darshilmukesh Patel, Lisa K Sharp, Spyros Kitsiou, Sharmilee M Nyenhuis. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 01.03.2021.

Entities:  

Keywords:  Fitbit; adults; fitness trackers; intervention; interventional studies; older adults; physical activity; smartphones; wearable

Year:  2021        PMID: 33646135      PMCID: PMC7961407          DOI: 10.2196/25289

Source DB:  PubMed          Journal:  JMIR Mhealth Uhealth        ISSN: 2291-5222            Impact factor:   4.773


  15 in total

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2.  The Situation-Specific Theory of Heart Failure Self-Care: Revised and Updated.

Authors:  Barbara Riegel; Victoria Vaughan Dickson; Kenneth M Faulkner
Journal:  J Cardiovasc Nurs       Date:  2016 May-Jun       Impact factor: 2.083

3.  B.A.I.L.A. - a Latin dance randomized controlled trial for older Spanish-speaking Latinos: rationale, design, and methods.

Authors:  David X Marquez; JoEllen Wilbur; Susan L Hughes; Michael L Berbaum; Robert S Wilson; David M Buchner; Edward McAuley
Journal:  Contemp Clin Trials       Date:  2014-06-24       Impact factor: 2.226

4.  Physical activity in the United States measured by accelerometer.

Authors:  Richard P Troiano; David Berrigan; Kevin W Dodd; Louise C Mâsse; Timothy Tilert; Margaret McDowell
Journal:  Med Sci Sports Exerc       Date:  2008-01       Impact factor: 5.411

Review 5.  Utility of Consumer Physical Activity Trackers as an Intervention Tool in Cardiovascular Disease Prevention and Treatment.

Authors:  Amanda M Hickey; Patty S Freedson
Journal:  Prog Cardiovasc Dis       Date:  2016-03-02       Impact factor: 8.194

6.  Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1·9 million participants.

Authors:  Regina Guthold; Gretchen A Stevens; Leanne M Riley; Fiona C Bull
Journal:  Lancet Glob Health       Date:  2018-09-04       Impact factor: 26.763

7.  The Physical Activity Guidelines for Americans.

Authors:  Katrina L Piercy; Richard P Troiano; Rachel M Ballard; Susan A Carlson; Janet E Fulton; Deborah A Galuska; Stephanie M George; Richard D Olson
Journal:  JAMA       Date:  2018-11-20       Impact factor: 157.335

8.  Identifying Barriers to Physical Activity Among African American Women with Asthma.

Authors:  S M Nyenhuis; N Shah; J Ma; D X Marquez; J Wilbur; A Cattamanchi; L K Sharp
Journal:  Cogent Med       Date:  2019-02-27

Review 9.  Privacy and Security in Mobile Health (mHealth) Research.

Authors:  Shifali Arora; Jennifer Yttri; Wendy Nilse
Journal:  Alcohol Res       Date:  2014

10.  A Walking Intervention Supplemented With Mobile Health Technology in Low-Active Urban African American Women With Asthma: Proof-of-Concept Study.

Authors:  Sharmilee M Nyenhuis; Guilherme Moraes Balbim; Jun Ma; David X Marquez; JoEllen Wilbur; Lisa K Sharp; Spyros Kitsiou
Journal:  JMIR Form Res       Date:  2020-03-11
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  8 in total

1.  Validity of a Global Positioning System-Based Algorithm and Consumer Wearables for Classifying Active Trips in Children and Adults.

Authors:  Chelsea Steel; Katie Crist; Amanda Grimes; Carolina Bejarano; Adrian Ortega; Paul R Hibbing; Jasper Schipperijn; Jordan A Carlson
Journal:  J Meas Phys Behav       Date:  2021-10-25

2.  The Collaborative Lifestyle Intervention Program in Knee Osteoarthritis Patients (CLIP-OA) trial: Design and methods.

Authors:  Brian C Focht; W Jack Rejeski; Kevin Hackshaw; Walter T Ambrosius; Erik Groessl; Zachary L Chaplow; Victoria R DeScenza; Jessica Bowman; Ciaran M Fairman; Beverly Nesbit; Kathryn Dispennette; Xiaochen Zhang; Marissa Fowler; Marcy Haynam; Stephanie Hohn
Journal:  Contemp Clin Trials       Date:  2022-03-11       Impact factor: 2.261

3.  The Effect of Tailored, Daily, Smartphone Feedback to Lifestyle Self-Monitoring on Weight Loss at 12 Months: the SMARTER Randomized Clinical Trial.

Authors:  Lora E Burke; Susan M Sereika; Zhadyra Bizhanova; Bambang Parmanto; Jacob Kariuki; Jessica Cheng; Britney Beatrice; Maribel Cedillo; I Wayan Pulantara; Yuhan Wang; India Loar; Molly B Conroy
Journal:  J Med Internet Res       Date:  2022-07-05       Impact factor: 7.076

4.  Consumer Willingness to Share Personal Digital Information for Health-Related Uses.

Authors:  David Grande; Nandita Mitra; Raghuram Iyengar; Raina M Merchant; David A Asch; Meghana Sharma; Carolyn C Cannuscio
Journal:  JAMA Netw Open       Date:  2022-01-04

Review 5.  Wearable activity trackers and artificial intelligence in the management of rheumatic diseases : Where are we in 2021?

Authors:  Thomas Davergne; Joanna Kedra; Laure Gossec
Journal:  Z Rheumatol       Date:  2021-10-11       Impact factor: 1.372

6.  Smartphone Ownership and Interest in Mobile Health Technologies for Self-care Among Patients With Chronic Heart Failure: Cross-sectional Survey Study.

Authors:  Jonathan W Leigh; Ben S Gerber; Christopher P Gans; Mayank M Kansal; Spyros Kitsiou
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Review 7.  Use of Fitbit Devices in Physical Activity Intervention Studies Across the Life Course: Narrative Review.

Authors:  Ruth Gaelle St Fleur; Sara Mijares St George; Rafael Leite; Marissa Kobayashi; Yaray Agosto; Danielle E Jake-Schoffman
Journal:  JMIR Mhealth Uhealth       Date:  2021-05-28       Impact factor: 4.773

8.  A Remote Health Coaching, Text-Based Walking Program in Ethnic Minority Primary Care Patients With Overweight and Obesity: Feasibility and Acceptability Pilot Study.

Authors:  Mary H Smart; Nadia A Nabulsi; Ben S Gerber; Itika Gupta; Barbara Di Eugenio; Brian Ziebart; Lisa K Sharp
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  8 in total

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