Cited by 74Physical Activity and HealthMobile Health and mHealth ApplicationsContext-Aware Activity Recognition Systems

Use of Fitbit Devices in Physical Activity Intervention Studies Across the Life Course: Narrative Review

Open access
St Fleur, Ruth Gaelle, St George, Sara Mijares, Leite, Rafael, Kobayashi, Marissa, Agosto, Yaray, Jake-Schoffman, Danielle E·2021·JMIR mHealth and uHealth

Published version of a preprint

Abstract

Background: Commercial off-the-shelf activity trackers (eg, Fitbit) allow users to self-monitor their daily physical activity (PA), including the number of steps, type of PA, amount of sleep, and other features. Fitbits have been used as both measurement and intervention tools. However, it is not clear how they are being incorporated into PA intervention studies, and their use in specific age groups across the life course is not well understood. Objective: This narrative review aims to characterize how PA intervention studies across the life course use Fitbit devices by synthesizing and summarizing information on device selection, intended use (intervention vs measurement tool), participant wear instructions, rates of adherence to device wear, strategies used to boost adherence, and the complementary use of other PA measures. This review provides intervention scientists with a synthesis of information that may inform future trials involving Fitbit devices. Methods: We conducted a search of the Fitabase Fitbit Research Library, a database of studies published between 2012 and 2018. Of the 682 studies available on the Fitabase research library, 60 interventions met the eligibility criteria and were included in this review. A supplemental search in PubMed resulted in the inclusion of 15 additional articles published between 2019 and 2020. A total of 75 articles were reviewed, which represented interventions conducted in childhood; adolescence; and early, middle, and older adulthood. Results: There was considerable heterogeneity in the use of Fitbit within and between developmental stages. Interventions for adults typically required longer wear periods, whereas studies on children and adolescents tended to have more limited device wear periods. Most studies used developmentally appropriate behavior change techniques and device wear instructions. Regardless of the developmental stage and intended Fitbit use (ie, measurement vs intervention tool), the most common strategies used to enhance wear time included sending participants reminders through texts or emails and asking participants to log their steps or synchronize their Fitbit data daily. The rates of adherence to the wear time criteria were reported using varying metrics. Most studies supplemented the use of Fitbit with additional objective or self-reported measures for PA. Conclusions: Overall, the heterogeneity in Fitbit use across PA intervention studies reflects its relative novelty in the field of research. As the use of monitoring devices continues to expand in PA research, the lack of uniformity in study protocols and metrics of reported measures represents a major issue for comparability purposes. There is a need for increased transparency in the prospective registration of PA intervention studies. Researchers need to provide a clear rationale for the use of several PA measures and specify the source of their main PA outcome and how additional measures will be used in the context of Fitbit-based interventions.

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  • The majority of studies that assess how wearable devices affect health outcomes are small.

    “However, most studies evaluating the impact of wearable devices on health outcomes are small and further studies and standardized evaluation are required.118,119”

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References 109 · Cited by 74

Research works printed but not linked: 2

  1. [9]Fitbit reports 2019 fourth quarter and full year results Fitbit, Inc 2020 2021-05-05 https://investor.fitbit.com/press-releases/press-release-details/2020/Fitbit-Reports-2019-Fourth-Quarter-and-Full-Year-Results/default.aspx
  2. [88]Schmidt LI Gabrian M Jansen CP Wahl HW Sieverding M Extending research on self-regulation of physical activity in older age: role of views on aging within an intensive ambulatory assessment scheme J Self-regul Regul 2018 4 43 59 10.11588/josar.2018.0.49362 · DOI

Authors
St Fleur, R. G., St George, S. M., Leite, R., Kobayashi, M., Agosto, Y., & Jake-Schoffman, D. E.
Affiliations
University of Miami (US)
Venue
JMIR mHealth and uHealth
Published
2021-05-28
Volume
9
Issue
5
Pages
e23411
ISSN
2291-5222 (ISSN-L)
OpenAlex
W3146033000
Cited by
74
References
109
Citations by year
2026: 14 · 2025: 20 · 2024: 19 · 2023: 15 · 2022: 5 · 2021: 1
FWCI
1.33
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR mhealth and uhealth (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Health Sciences › Medicine › Physiology › Physical Activity and Health
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
Keywords
Fitbit, wearable activity trackers, physical activity interventions, self-monitoring, behaviour change techniques, children and adolescents, older adults, life course, wearable devices, measurement validity, sleep monitoring, step counting
MeSH terms
Fitness Trackers, Adolescent, Adult, Aged, Child, Humans, Prospective Studies, Sleep, Exercise, Text Messaging

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