Validation of the Fitbit One activity monitor device during treadmill walking

Takacs, Judit; Pollock, Courtney L.; Guenther, Jerrad R.; Bahar, Mohammadreza; Napier, Christopher; Hunt, Michael A.

doi:10.1016/j.jsams.2013.10.241

Cited by 294 publications

(226 citation statements)

References 22 publications

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“…Therefore, available evidence suggests that step estimations from CPAMs are both more reliable and more valid than kcal estimations. The correlations obtained in the present study were comparable to those reported by Diaz et al for steps (0.97 vs. 0.99) and kcals (0.94 vs. 0.97), as well as those of Takacs et al [11] for steps (0.96 vs. 1.00), respectively [8,10]. It is important to note the consistently high correlations across various activity protocols indicating that reliability remains high even with the inclusion of a variety of activities, contrasting validity research where inclusion of diverse activities lowers CPAM validity [18].…”

Section: Discussionsupporting

confidence: 92%

“…Intra-monitor MAD and MPD step values for the hip-worn CPAMs were significantly lower (better) than the wrist-worn CPAMs (p < 0.01) without a concurrent difference in kcal estimations (p = 0.46 and 0.53, respectively). The JU had the largest average MAD for steps (11), kcals (2.1), and the highest MPD for kcals (13.9%); the FF had the largest MPD for steps (7.2%). Figure 2 (steps) and Figure 3 (kcals) illustrate that CPAM error was higher in some cases during activities with higher predicted PA; however, these results may be partly influenced by outliers as they were not excluded from analysis.…”

Section: Intra-monitor Reliabilitymentioning

confidence: 98%

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Determining the Reliability of Several Consumer-Based Physical Activity Monitors

et al. 2017

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Limited research exists on the reliability of consumer-based physical activity monitors (CPAMs) despite numerous studies on their validity. Consumers often purchase CPAMs to assess their physical activity (PA) habits over time, emphasizing CPAM reliability more so than their validity; therefore, the purpose of this study was to investigate the reliability of several CPAMs. In this study, 30 participants wore a pair of four CPAM models (Fitbit One, Zip, Flex, and Jawbone Up24) for a total of eight monitors, while completing seven activities in the laboratory. Activities were completed in two consecutive five-minute bouts. Participants then wore either all wrist-or hip-mounted CPAMs in a free-living setting for the remainder of the day. Intra-monitor reliability for steps (0.88-0.99) was higher than kcals (0.77-0.94), and was higher for hip-worn CPAMs than for wrist-worn CPAMs (p < 0.001 for both). Inter-monitor reliability in the laboratory for steps (0.81-0.99) was higher than kcals (0.64-0.91) and higher for hip-worn CPAMs than for wrist-worn CPAMs (p < 0.001 for both). Free-living correlations were 0. 61-0.98, 0.35-0.96, and 0.97-0.98 for steps, kcals, and active minutes, respectively. These findings illustrate that all CPAMs assessed yield reliable estimations of PA. Additionally, all CPAMs tested can provide reliable estimations of physical activity within the laboratory but appear less reliable in a free-living setting.

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Section: Discussionsupporting

confidence: 92%

Section: Intra-monitor Reliabilitymentioning

confidence: 98%

Determining the Reliability of Several Consumer-Based Physical Activity Monitors

et al. 2017

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“…Fitbit™ devices are reported as validated and reliable (Takacs et al, 2013) to receive objectively estimated real time outcome data.…”

Section: Psychology and Health 689mentioning

confidence: 99%

N-of-1 study of weight loss maintenance assessing predictors of physical activity, adherence to weight loss plan and weight change

Kwaśnicka

Dombrowski

White

et al. 2017

Psychology & Health

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Objective: Behaviour change interventions are effective in supporting individuals to achieve clinically significant weight loss, but weight loss maintenance (WLM) is less often attained. This study examined predictive variables associated with WLM. Design: N-of-1 study with daily ecological momentary assessment combined with objective measurement of weight and physical activity, collected with wireless devices (Fitbit™) for six months. Eight previously obese adults who had lost over 5% of their body weight in the past year took part. Data were analysed using time series methods. Main outcomes measures: Predictor variables were based on five theoretical themes: maintenance motives, self-regulation, personal resources, habits, and environmental influences. Dependent variables were: objectively estimated step count and weight, and self-reported WLM plan adherence. Results: For all participants, daily fluctuations in self-reported adherence to their WLM plan were significantly associated with most of the explanatory variables, including maintenance motivation and satisfaction with outcomes, self-regulation, habit, and stable environment. Personal resources were not a consistent predictor of plan adherence. Conclusion: This is the first study to assess theoretical predictions of WLM within individuals. WLM is a dynamic process including the interplay of motivation, self-regulation, habit, resources, and perceptions of environmental context. Individuals maintaining their weight have unique psychological profiles which could be accounted for in interventions.Keywords: behaviour change maintenance; n-of-1 study; theory; weight loss maintenance *Corresponding author. Email: dominika.kwasnicka@curtin.edu.au © 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecom mons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Psychology & Health, 2017 Vol. 32, No. 6, 686-708, http://dx.doi.org/10.1080/08870446.2017 Introduction Weight loss maintenance (WLM) has been defined as a process of sustaining a significant intentional weight loss accomplished by one's own efforts and/or as a result of treatment (Elfhag & Rossner, 2005). The specific criteria used to define WLM vary between research studies. Discrepancies include the percentage of weight loss required and the length of time for maintained weight loss. For instance in terms of percentage weight loss, WLM researchers suggest that a minimum of 3% (Stevens, Truesdale, McClain, & Cai, 2005), 5% (Crawford, Jeffery, & French, 2000) or 10% (Wing & Hill, 2001) is necessary to be classified as successful WLM. The time period requirements for substantial WLM also differ; for example, a minimum of 6 months (Elfhag & Rossner, 2005), 12 months (Wing & Hill, 2001) or 24 months (Stevens et al., 2005) of maintained weight loss have been sugg...

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“…Evenson, Goto, and Furberg (2015) agree that ICCs of consumer-wearable activity trackers with accelerometers are generally high (ICC ≥ .80). Takacs et al (2013) tested the Fitbit fitness bracelet on 30 participants performing PA on a treadmill and found a perfect agreement and interdevice reliability regardless of walking speed or device location. Ferguson, Rowlands, Olds, and Maher (2015) found a perfect step agreement between WAT Withings Pulse and the ActiGraph GT3X+ accelerometer.…”

Section: Of Garmin Vívofit and Polar Loopmentioning

confidence: 99%

Validity of Garmin Vívofit and Polar Loop for measuring daily step counts in free-living conditions in adults

Šimůnek¹,

Dygrýn²,

Gába³

et al. 2016

Acta Gymnica

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Validation of the Fitbit One activity monitor device during treadmill walking

Cited by 294 publications

References 22 publications

Determining the Reliability of Several Consumer-Based Physical Activity Monitors

Determining the Reliability of Several Consumer-Based Physical Activity Monitors

N-of-1 study of weight loss maintenance assessing predictors of physical activity, adherence to weight loss plan and weight change

Validity of Garmin Vívofit and Polar Loop for measuring daily step counts in free-living conditions in adults

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