ArticlePloS one2020
Performance of a commercial multi-sensor wearable (Fitbit Charge HR) in measuring physical activity and sleep in healthy children.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 68 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.
Optimizing a Mobile Health Platform for Sleep Promotion and Obesity Prevention in Children
Physical Activity in Adolescents With Chronic Kidney Disease
Who cites it
68 citing papers in PubMed, 2 syntheses or guidelines pooled it, 103 citations in OpenAlex.
- Accuracy and Precision of Consumer-Grade Wearable Activity Monitors for Assessing Time Spent in Sedentary Behavior in Children and Adolescents: Systematic Review.JMIR mHealth and uHealth · 2022Pooled it
- Assessment of 24-hour physical behaviour in children and adolescents via wearables: a systematic review of free-living validation studies.BMJ open sport & exercise medicine · 2022Pooled it
- Evaluation of a Consumer Wearable Smartwatch for Cardiac Interval Measurement in Healthy Adults: Cross-Sectional Method Comparison Study.JMIR formative research · 2026Article
- Associations of Fitbit measured physical activity and sedentary behavior with mental health in U.S. youth: a quantile regression analysis.Child and adolescent mental health · 2026Article
- Precision sleep signatures to predict mental health outcomes in youth.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026Review
- The Relationship Between ADHD Symptom Severity and Sleep Disturbance Using Accelerometer and the Subjective Sleep Disturbance Scale.Journal of attention disorders · 2026Article
- 24-h Movement Behaviors and Incident Hypertension Among Adolescents: A Prospective Study From the ABCD Study.Scandinavian journal of medicine & science in sports · 2026Article
- Associations of Screen Time and Physical Activity With Body Mass Index in Early Adolescence: A Prospective Cohort Study.Obesity (Silver Spring, Md.) · 2026Article
- Connectome-Based Predictive Models Optimized for Sleep Differentiate Patients With Depression From Psychiatrically Healthy Controls.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026Article
- Higher recreational screen time and lower step count are associated with higher cardiovascular disease risk in early adolescence.BMC public health · 2026Article
- Who's counting? Discrepancies between caregiver-reported, youth-reported, and Fitbit sleep in the ABCD study.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2026Article
- Agreement Between Consumer and Research-Grade Physical Activity Monitors in a Public Health Intervention for Adolescent Latinas.International journal of environmental research and public health · 2025Article
- Changes in Rest-Activity Rhythms in Adolescents as They Age: Associations With Brain and Behavioral Changes in the ABCD Study.Journal of the American Academy of Child and Adolescent Psychiatry · 2025Article
- Biorhythms derived from consumer wearables predict postoperative complications in children.Science advances · 2025Article
- Somatomotor Disconnection Links Sleep Duration With Socioeconomic Context, Screen Time, Cognition, and Psychopathology.Biological psychiatry global open science · 2025Article
- Adolescent smartphone use, sleep, and physical activity: daily associations between sensor-based measures in the adolescent brain cognitive development (ABCD) study.Psychiatry research · 2025Article
- The relationship between sleep and problem behaviors in children with attention-deficit/hyperactivity disorder.European journal of pediatrics · 2025Article
- Cognition and behavior in neurofibromatosis type 1: report and perspective from the Cognition and Behavior in NF1 (CABIN) Task Force.Genes & development · 2025Article
- Latent Default Mode Network Connectivity Patterns: Associations With Sleep Health and Adolescent Psychopathology.Brain and behavior · 2025Article
- Enhancing artificial intelligence-driven sleep apnea diagnosis: The critical importance of input signal proficiency with a focus on mandibular jaw movements.Journal of prosthodontics : official journal of the American College of Prosthodontists · 2025Article
8 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 3 institutions in 1 country.
Funding
Abstract
purposeThis study sought to assess the performance of the Fitbit Charge HR, a consumer-level multi-sensor activity tracker, to measure physical activity and sleep in children.
methods59 healthy boys and girls aged 9-11 years old wore a Fitbit Charge HR, and accuracy of physical activity measures were evaluated relative to research-grade measures taken during a combination of 14 standardized laboratory- and field-based assessments of sitting, stationary cycling, treadmill walking or jogging, stair walking, outdoor walking, and agility drills. Accuracy of sleep measures were evaluated relative to polysomnography (PSG) in 26 boys and girls during an at-home unattended PSG overnight recording. The primary analyses included assessment of the agreement (biases) between measures using the Bland-Altman method, and epoch-by-epoch (EBE) analyses on a minute-by-minute basis.
resultsFitbit Charge HR underestimated steps (~11.8 steps per minute), heart rate (~3.58 bpm), and metabolic equivalents (~0.55 METs per minute) and overestimated energy expenditure (~0.34 kcal per minute) relative to research-grade measures (p< 0.05). The device showed an overall accuracy of 84.8% for classifying moderate and vigorous physical activity (MVPA) and sedentary and light physical activity (SLPA) (sensitivity MVPA: 85.4%; specificity SLPA: 83.1%). Mean estimates of bias for measuring total sleep time, wake after sleep onset, and heart rate during sleep were 14 min, 9 min, and 1.06 bpm, respectively, with 95.8% sensitivity in classifying sleep and 56.3% specificity in classifying wake epochs.
conclusionsFitbit Charge HR had adequate sensitivity in classifying moderate and vigorous intensity physical activity and sleep, but had limitations in detecting wake, and was more accurate in detecting heart rate during sleep than during exercise, in healthy children. Further research is needed to understand potential challenges and limitations of these consumer devices.
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What OpenQuestion holds
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.