Randomized Trial of a Fitbit-Based Physical Activity Intervention for Women
Open accessAbstract
Introduction Direct-to-consumer mHealth devices are a potential asset to behavioral research but rarely tested as intervention tools. This trial examined the accelerometer-based Fitbit tracker and website as a low-touch physical activity intervention. The purpose of this study is to evaluate, within an RCT, the feasibility and preliminary efficacy of integrating the Fitbit tracker and website into a physical activity intervention for postmenopausal women.Methods Fifty-one inactive, postmenopausal women with BMI ≥25.0 were randomized to a 16-week web-based self-monitoring intervention (n=25) or comparison group (n=26). The Web-Based Tracking Group received a Fitbit, instructional session, and follow-up call at 4 weeks. The comparison group received a standard pedometer. All were asked to perform 150 minutes/week of moderate to vigorous physical activity (MVPA). Physical activity outcomes were measured by the ActiGraph GT3X+ accelerometer.Results Data were collected and analyzed in 2013-2014. Participants were aged 60 (SD=7) years with BMI of 29.2 (3.5) kg/m(2). Relative to baseline, the Web-Based Tracking Group increased MVPA by 62 (108) minutes/week (p<0.01); 10-minute MVPA bouts by 38 (83) minutes/week (p=0.008); and steps by 789 (1,979) (p=0.01), compared to non-significant increases in the Pedometer Group (between-group p=0.11, 0.28, and 0.30, respectively). The Web-Based Tracking Group wore the tracker on 95% of intervention days; 96% reported liking the website and 100% liked the tracker.Conclusions The Fitbit was well accepted in this sample of women and associated with increased physical activity at 16 weeks. Leveraging direct-to-consumer mHealth technologies aligned with behavior change theories can strengthen physical activity interventions.
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A total of 26 studies were included across all meta-analyses.
“A total of 26 studies were included across all meta-analyses [21,22,29-48,50-53].”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [21]
17 studies specified that participants must have regular access to the internet, a computer, tablet, and/or smartphone.
“Furthermore, 17 studies specified that the participant must have regular access to the internet, a computer, tablet, and/or smartphone [21,30,33,35-37,39,41-47,51-53]”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [21]
3 studies required participants to be proficient at using the internet and/or smartphones.
“with 3 studies requiring participants to be proficient at using the internet and/or smartphones [21,22,45].”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [21]
17 studies reported activity tracker adherence data, with 13 of these reporting activity tracker wear on at least 50% of the study intervention days.
“Moreover, 17 studies reported activity tracker adherence data [21,22,30,32,34,35, 37,38,40,41,43-45,50-52,54], with 13 of these studies [21,22,30,34,35,40,41,43,44,50-52,54] reporting activity tracker wear on at least 50% of the study intervention days.”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [21]
Randomized controlled trials have shown that consumer-based wearable activity trackers have promise in relation to increasing physical activity participation.
“Randomized controlled trials have shown that these devices have promise in relation to increasing physical activity participation [21,22]”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [21]
Actual wear time of the activity tracker varied, ranging from over 90% wear time to all participants ceasing to wear the device by the end of the intervention.
“Actual wear time of the activity tracker varied, ranging from over 90% wear time [21,22] to all participants ceasing to wear the device by the end of the intervention [32] as the study design allowed self-directed wear of the activity tracker.”
From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [21]
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- Authors
- Cadmus-Bertram, L. A., Marcus, B. H., Patterson, R. E., Parker, B. A., & Morey, B. L.
- Affiliations
- University of California San Diego (US)
- Venue
- American Journal of Preventive Medicine
- Publisher
- Elsevier BV
- Published
- 2015-09
- Volume
- 49
- Issue
- 3
- Pages
- 414-418
- ISSN
- 0749-3797 (ISSN-L)
- PMC
- PMC4993151
- OpenAlex
- W1587923037
- Cited by
- 469
- References
- 15
- Citations by year
- 2026: 33 · 2025: 26 · 2024: 21 · 2023: 32 · 2022: 46 · 2021: 53 · 2020: 45 · 2019: 63 · 2018: 58 · 2017: 57 · 2016: 32 · 2015: 3
- FWCI
- 91.42
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Preventive Medicine (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (1R03CA168450)
- National Cancer Institute (1R03CA168450)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- Fitbit, wearable accelerometers, physical activity interventions, postmenopausal women, mobile health, self-monitoring, pedometers, moderate-to-vigorous physical activity, step count, online intervention, feasibility, behavior change
- MeSH terms
- Aged, Equipment Design, Feasibility Studies, Female, Follow-Up Studies, Humans, Middle Aged, Motor Activity, Exercise, Internet, Actigraphy, Accelerometry
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