Lisa A Cadmus-Bertram1, Bess H Marcus2, Ruth E Patterson3, Barbara A Parker4, Brittany L Morey5. 1. Department of Kinesiology, University of Wisconsin-Madison, Madison, Wisconsin. Electronic address: cadmusbertra@wisc.edu. 2. Department of Family Medicine and Public Health, University of California, San Diego, San Diego, California. 3. Department of Family Medicine and Public Health, University of California, San Diego, San Diego, California; Department of Medicine, University of California, San Diego, San Diego, California. 4. Department of Medicine, University of California, San Diego, San Diego, California. 5. Moores Cancer Center, University of California, San Diego, San Diego, California.
Abstract
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.
RCT Entities:
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.
Authors: Paul A Harris; Robert Taylor; Robert Thielke; Jonathon Payne; Nathaniel Gonzalez; Jose G Conde Journal: J Biomed Inform Date: 2008-09-30 Impact factor: 6.317
Authors: J F Sallis; W L Haskell; P D Wood; S P Fortmann; T Rogers; S N Blair; R S Paffenbarger Journal: Am J Epidemiol Date: 1985-01 Impact factor: 4.897
Authors: Warren G Thompson; Carol L Kuhle; Gabriel A Koepp; Shelly K McCrady-Spitzer; James A Levine Journal: Arch Gerontol Geriatr Date: 2014-01-15 Impact factor: 3.250
Authors: Judith Hsia; Lieling Wu; Catherine Allen; Albert Oberman; William E Lawson; Javier Torréns; Monika Safford; Marian C Limacher; Barbara V Howard Journal: Am J Prev Med Date: 2005-01 Impact factor: 5.043
Authors: William L Haskell; I-Min Lee; Russell R Pate; Kenneth E Powell; Steven N Blair; Barry A Franklin; Caroline A Macera; Gregory W Heath; Paul D Thompson; Adrian Bauman Journal: Med Sci Sports Exerc Date: 2007-08 Impact factor: 5.411
Authors: Lisa Cadmus-Bertram; Amye J Tevaarwerk; Mary E Sesto; Ronald Gangnon; Brittany Van Remortel; Preshita Date Journal: J Cancer Surviv Date: 2019-07-01 Impact factor: 4.442
Authors: Darryl Somayaji; Amanda C Blok; Laura L Hayman; Yolanda Colson; Michael Jaklisch; Mary E Cooley Journal: Support Care Cancer Date: 2019-01-14 Impact factor: 3.603
Authors: Sheri J Hartman; Shira I Dunsiger; Beth C Bock; Britta A Larsen; Sarah Linke; Dori Pekmezi; Becky Marquez; Kim M Gans; Andrea S Mendoza-Vasconez; Bess H Marcus Journal: J Behav Med Date: 2016-10-17