A Validation Study of the Fitbit One in Daily Life Using Different Time Intervals

Middelweerd, Anouk; Ploeg, Hidde P. van der; Halteren, Aart van; Twisk, Jos W. R.; Brug, Johannes; Velde, Saskia J. te

doi:10.1249/mss.0000000000001225

Cited by 29 publications

(16 citation statements)

References 24 publications

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“…The detected magnitude of the deviation of 23.8% from the gold standard at 3.2 km/h is comparable to the 26.7% deviation Riel et al found in healthy college students (mean age 27.9 years) and thus clearly questions the suitability of the ActiGraph to be used for step detection in slow walking speeds. In addition, the confirmed inaccuracy of the hip‐worn ActiGraph seriously contests the use of this device as the reference method for step counting during activities of daily life and thus puts even most recent research findings into question. When worn on the wrist, the ActiGraph appeared to be entirely inaccurate for all walking conditions (deviations of up to 47% from the gold standard), making it utterly unsuitable for clinical use.…”

Section: Discussionmentioning

confidence: 99%

Validity of activity trackers, smartphones, and phone applications to measure steps in various walking conditions

Höchsmann

Knaier

Eymann

et al. 2018

Scandinavian Med Sci Sports

103

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To examine the validity of popular smartphone accelerometer applications and a consumer activity wristband compared to a widely used research accelerometer while assessing the impact of the phone's position on the accuracy of step detection. Twenty volunteers from 2 different age groups (Group A: 18-25 years, n = 10; Group B 45-70 years, n = 10) were equipped with 3 iPhone SE smartphones (placed in pants pocket, shoulder bag, and backpack), 1 Samsung Galaxy S6 Edge (pants pocket), 1 Garmin Vivofit 2 wristband, and 2 ActiGraph wGTX+ devices (worn at wrist and hip) while walking on a treadmill (1.6, 3.2, 4.8, and 6.0 km/h) and completing a walking course. All smartphones included 6 accelerometer applications. Video observation was used as gold standard. Validity was evaluated by comparing each device with the gold standard using mean absolute percentage errors (MAPE). The MAPE of the iPhone SE (all positions) and the Garmin Vivofit was small (<3) for treadmill walking ≥3.2 km/h and for free walking. The Samsung Galaxy and hip-worn ActiGraph showed small MAPE only for treadmill walking at 4.8 and 6.0 km/h and for free walking. The wrist-worn ActiGraph showed high MAPE (17-47) for all walking conditions. The iPhone SE and the Garmin Vivofit 2 are accurate tools for step counting in different age groups and during various walking conditions, even during slow walking. The phone's position does not impact the accuracy of step detection, which substantially improves the versatility for physical activity assessment in clinical and research settings.

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Section: Discussionmentioning

confidence: 99%

Validity of activity trackers, smartphones, and phone applications to measure steps in various walking conditions

Höchsmann

Knaier

Eymann

et al. 2018

Scandinavian Med Sci Sports

103

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“…Collecting these data at the time of the study would have allowed us to have full hourly data for all participants and preempted the need to contact participants years later. Additionally, we could have more directly measured Fitbit wear-time via self-report as has been done in some past studies [ 23 , 37 – 38 ]. The addition of explicit wear-time information would have allowed us to utilize the minimum 10 hours per day criterion from the Actigraph research literature.…”

Section: Discussionmentioning

confidence: 99%

Successful adherence and retention to daily monitoring of physical activity: Lessons learned

Tupy

Robertson

et al. 2018

PLoS ONE

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Research utilizing repeated-measures such as daily assessments with self-report and/or objective measures [e.g., physical activity (PA) monitors] are important in understanding health behaviors and informing practice and policy. However, studies that utilize daily assessment often encounter issues with attrition and non-compliance. The current research yielded high levels of retention and adherence with both self-report and objective daily measures. The purpose of this paper is to highlight and discuss strategies utilized in maximizing retention, minimizing missing data, and some lessons learned from the research experience. Fifty community participants took part in a 4-week study utilizing both daily self-report questionnaires and daily use of PA monitors (Fitbit One™). This study focused on typical daily PA and was not an intervention study (e.g., participants were not randomized nor asked to change their PA behavior). Participants completed the study in two waves (wave 1 n = 10, wave 2 n = 40). The research team utilized several retention strategies including automating the data collection process, a prorated incentive structure, having a dedicated and responsive study staff, and utilizing the 2-wave process to optimize data collection during the 2nd wave. The study had 100% retention and generally positive anonymous feedback post-study. Overall, participants completed the vast majority of daily surveys (97%) and wore their Fitbits (for at least part of the day) on almost all days (99.57%) of the study, although there were individual differences. The strategies discussed and lessons learned may be useful to other researchers using daily measurements for whom adherence and retention are important issues. Future research employing these strategies in different populations, with different measurements, and for longer durations is warranted to determine generalizability.

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“…As a further limitation, measurement errors might have occurred when participants rode a bike over uneven surfaces or, as in our case, engaged in horseback riding. Nevertheless, multiple Fitbit devices were validated [ 56 , 57 , 58 , 59 ] and shown to be useful and valid tools to track activity correctly.…”

Section: Discussionmentioning

confidence: 99%

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

Hendker

Jetzke

Eils

et al. 2020

IJERPH

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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.

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A Validation Study of the Fitbit One in Daily Life Using Different Time Intervals

Cited by 29 publications

References 24 publications

Validity of activity trackers, smartphones, and phone applications to measure steps in various walking conditions

Validity of activity trackers, smartphones, and phone applications to measure steps in various walking conditions

Successful adherence and retention to daily monitoring of physical activity: Lessons learned

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

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