ArticleACR open rheumatology2019
Validating Fitbit for Evaluation of Physical Activity in Patients with Knee Osteoarthritis: Do Thresholds Matter?
Article in ACR open rheumatology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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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.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- 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
- Rethinking measurement of movement-evoked pain with digital technology.The journal of pain · 2026Article
- Rethinking Measurement of Movement-Evoked Pain with Digital Technology.medRxiv : the preprint server for health sciences · 2025Article
- Trajectories of mHealth-Tracked Mental Health and Their Predictors in Female Chronic Pelvic Pain Disorders.Journal of pain research · 2025Article
- Aerobic Fitness as an Important Moderator Risk Factor for Loneliness in Physically Trained Older People: An Explanatory Case Study Using Machine Learning.Life (Basel, Switzerland) · 2023Article
- Article
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Authors and funding
4 authors.
Funding
Abstract
objectiveWe sought to evaluate the performance of Fitbit in estimating ActiGraph-derived moderate-to-vigorous physical activity (MVPA) and sedentary time in the knee osteoarthritis (OA) population.
methodsWe used data from two weeks of Fitbit and ActiGraph wear among knee OA subjects. In primary analyses, we used literature-based ActiGraph thresholds of 200 and 1924 counts/min (triaxial vector magnitude) for sedentary and MVPA time as the gold standard to which we compared three sets of Fitbit thresholds informed by literature and data (Youden index). We also considered personalized, stride length-based Fitbit thresholds. In sensitivity analyses, we used uniaxial, vertical axis-based as well as personalized, BMI-based ActiGraph thresholds. We calculated agreement, sensitivity, and specificity of Fitbit in classifying sedentary and MVPA time.
resultsIn the primary analysis (vector magnitude thresholds), maximum agreement for sedentary and MVPA time was 67.0% from the Youden index-based and 91.1% from the stride length-based Fitbit thresholds. For sedentary time, the 20 strides/min threshold had the highest sensitivity (97.6%), and Youden-derived 1 stride/min had the highest specificity (51.6%). For MVPA, Youden-derived 14 strides/min yielded 72.8% sensitivity, and using stride length yielded 98.6% specificity. MVPA time ranged from 49-323 min/d, depending on threshold used, with literature-based and personalized thresholds leading to more conservative estimates of MVPA than Youden-derived thresholds.
conclusionUsing Fitbit for MVPA and sedentary time assessment may lead to inaccurate estimates of both. Fitbit MVPA estimates were generally more conservative than ActiGraph estimates. Incorporating individuals' characteristics did not meaningfully improve Fitbit performance. Caution should be exercised when measuring activity using Fitbit.
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Registered trials
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