ArticleJMIR mHealth and uHealth2016
Physical Activity Assessment Between Consumer- and Research-Grade Accelerometers: A Comparative Study in Free-Living Conditions.
Article in JMIR mHealth and uHealth, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
59 citing papers in PubMed, 2 syntheses or guidelines pooled it, 107 citations in OpenAlex.
- Quality Evaluation of Free-living Validation Studies for the Assessment of 24-Hour Physical Behavior in Adults via Wearables: Systematic Review.JMIR mHealth and uHealth · 2022Pooled it
- Reliability and Validity of Commercially Available Wearable Devices for Measuring Steps, Energy Expenditure, and Heart Rate: Systematic Review.JMIR mHealth and uHealth · 2020Pooled it
- Improving Outcomes for Care Partners of Individuals With Traumatic Brain Injury: Results for a mHealth Randomized Control Trial of the CareQOL App.Archives of physical medicine and rehabilitation · 2025Trial
- An app-based just-in-time-adaptive self-management intervention for care partners: The CareQOL feasibility pilot study.Rehabilitation psychology · 2022Trial
- Examining the Impact of an mHealth Behavior Change Intervention With a Brief In-Person Component for Cancer Survivors With Overweight or Obesity: Randomized Controlled Trial.JMIR mHealth and uHealth · 2021Trial
- Use of consumer monitors for estimating energy expenditure in youth.Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme · 2020Trial
- The utility of personal activity trackers (Fitbit Charge 2) on exercise capacity in patients post acute coronary syndrome [UP-STEP ACS Trial]: a randomised controlled trial protocol.BMC cardiovascular disorders · 2017Trial
- The Association between Neighborhood Walkability and Physical Activity in a Behavioral Weight Loss Trial Testing the Addition of Remotely Delivered Feedback Messages to Self-Monitoring.Behavioral medicine (Washington, D.C.)Trial
- Using network science to examine temporal relationships between 24-hour movement behaviors and depression during the transition to college: protocol for a prospective cohort study.Journal of activity, sedentary and sleep behaviors · 2026Article
- Using Network Science to Examine Temporal Relationships between 24-Hour Movement Behaviors and Depression During the Transition to College: Protocol for a Prospective Cohort Study.Research square · 2026Article
- Using an Adult-Designed Wearable for Pediatric Monitoring: Practical Tutorial and Application in School-Aged Children With Obesity.Journal of medical Internet research · 2026Article
- Daily step-count and sleep metrics across pregnancy: an observational analysis of the LEAP cluster randomized clinical trial.Sleep advances : a journal of the Sleep Research Society · 2026Article
- Criterion and Construct Validity of the Pocket-Worn RISE Device to Assess Movement Behaviour in Community-Dwelling People with Stroke.Sensors (Basel, Switzerland) · 2025Article
- Heart Rate Monitoring Among Breast Cancer Survivors: Quantitative Study of Device Agreement in a Community-Based Exercise Program.JMIR cancer · 2024Article
- Agreement between Fitbit and ActiGraph Estimates of Physical Activity in Young Children.Measurement in physical education and exercise science · 2023Article
- Comparison of free-living physical activity measurements between ActiGraph GT3X-BT and Fitbit Charge 3 in young people with haemophilia.Haemophilia : the official journal of the World Federation of Hemophilia · 2022Article
- Comparison of Wrist- and Hip-Worn Activity Monitors When Meeting Step Guidelines.Preventing chronic disease · 2022Article
- Accelerometry Data Delineate Phases of Recovery and Supplement Patient-Reported Outcome Measures Following Lumbar Laminectomy.World neurosurgery · 2022Article
- [The first steps after a proximal femoral fracture : Sensor-based mobility exploration in geriatric trauma patients].Zeitschrift fur Gerontologie und Geriatrie · 2021Article
- Effectiveness of the mHealth intervention 'MyDayPlan' to increase physical activity: an aggregated single case approach.The international journal of behavioral nutrition and physical activity · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundWearable activity monitors such as Fitbit enable users to track various attributes of their physical activity (PA) over time and have the potential to be used in research to promote and measure PA behavior. However, the measurement accuracy of Fitbit in absolute free-living conditions is largely unknown.
objectiveTo examine the measurement congruence between Fitbit Flex and ActiGraph GT3X for quantifying steps, metabolic equivalent tasks (METs), and proportion of time in sedentary activity and light-, moderate-, and vigorous-intensity PA in healthy adults in free-living conditions.
methodsA convenience sample of 19 participants (4 men and 15 women), aged 18-37 years, concurrently wore the Fitbit Flex (wrist) and ActiGraph GT3X (waist) for 1- or 2-week observation periods (n=3 and n=16, respectively) that included self-reported bouts of daily exercise. Data were examined for daily activity, averaged over 14 days and for minutes of reported exercise. Average day-level data included steps, METs, and proportion of time in different intensity levels. Minute-level data included steps, METs, and mean intensity score (0 = sedentary, 3 = vigorous) for overall reported exercise bouts (N=120) and by exercise type (walking, n=16; run or sports, n=44; cardio machine, n=20).
resultsMeasures of steps were similar between devices for average day- and minute-level observations (all P values > .05). Fitbit significantly overestimated METs for average daily activity, for overall minutes of reported exercise bouts, and for walking and run or sports exercises (mean difference 0.70, 1.80, 3.16, and 2.00 METs, respectively; all P values < .001). For average daily activity, Fitbit significantly underestimated the proportion of time in sedentary and light intensity by 20% and 34%, respectively, and overestimated time by 3% in both moderate and vigorous intensity (all P values < .001). Mean intensity scores were not different for overall minutes of exercise or for run or sports and cardio-machine exercises (all P values > .05).
conclusionsFitbit Flex provides accurate measures of steps for daily activity and minutes of reported exercise, regardless of exercise type. Although the proportion of time in different intensity levels varied between devices, examining the mean intensity score for minute-level bouts across different exercise types enabled interdevice comparisons that revealed similar measures of exercise intensity. Fitbit Flex is shown to have measurement limitations that may affect its potential utility and validity for measuring PA attributes in free-living conditions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.