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The Implication of Wearables and the Factors Affecting Their Usage among Recreationally Active People

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  • Anna Hendker

    (Department of Neuromotor Behavior and Exercise, Institute of Sport and Exercise Sciences, University of Muenster, 48149 Muenster, Germany)

  • Malte Jetzke

    (Department of Social Sciences of Sport, Institute of Sport and Exercise Sciences, University of Muenster, 48149 Muenster, Germany)

  • Eric Eils

    (Department of Neuromotor Behavior and Exercise, Institute of Sport and Exercise Sciences, University of Muenster, 48149 Muenster, Germany)

  • Claudia Voelcker-Rehage

    (Department of Neuromotor Behavior and Exercise, Institute of Sport and Exercise Sciences, University of Muenster, 48149 Muenster, Germany)

Abstract

Regular physical activity (PA) is associated with health and well-being. Recent findings show that PA tracking using technological devices can enhance PA behavior. Consumer devices can track many different parameters affecting PA (e.g., number of steps, distance, and heart rate). However, it remains unclear what factors affect the usage of such devices. In this study, we evaluated whether there was a change in usage behavior across the first weeks of usage. Further we investigated whether external factors such as weather and day of the week influence usage behavior. Thirty nine participants received a Fitbit Charge 2 fitness tracker for a nine-week period. All participants were asked to wear the device according to their wishes. The usage time and amount of PA were assessed, and the influencing factors, such as weather conditions and day of the week, were analyzed. The results showed that usage behavior differed largely between individuals and decreased after five weeks of usage. Moreover, the steps per worn hour did not change significantly, indicating a similar amount of activity across the nine-week period when wearing the device. Further influencing factors were the day of the week (the tracker was used less on Sundays) and the temperature (usage time was lower with temperatures >25°). Tracking peoples’ activity might have the potential to evaluate different interventions to increase PA.

Suggested Citation

  • Anna Hendker & Malte Jetzke & Eric Eils & Claudia Voelcker-Rehage, 2020. "The Implication of Wearables and the Factors Affecting Their Usage among Recreationally Active People," IJERPH, MDPI, vol. 17(22), pages 1-18, November.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:22:p:8532-:d:446573
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    References listed on IDEAS

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    1. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
    2. Brownson, R.C. & Baker, E.A. & Housemann, R.A. & Brennan, L.K. & Bacak, S.J., 2001. "Environmental and policy determinants of physical activity in the United States," American Journal of Public Health, American Public Health Association, vol. 91(12), pages 1995-2003.
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    1. Tina Auerswald & Anna Hendker & Tiara Ratz & Sonia Lippke & Claudia R. Pischke & Manuela Peters & Jochen Meyer & Kai von Holdt & Claudia Voelcker-Rehage, 2022. "Impact of Activity Tracker Usage in Combination with a Physical Activity Intervention on Physical and Cognitive Parameters in Healthy Adults Aged 60+: A Randomized Controlled Trial," IJERPH, MDPI, vol. 19(7), pages 1-20, March.

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