Evidence map›Paper›PMID 31777843›Full record

ArticleACR open rheumatology2019

Validating Fitbit for Evaluation of Physical Activity in Patients with Knee Osteoarthritis: Do Thresholds Matter?

Genevieve S Silva, Heidi Yang, Jamie E Collins, Elena Losina

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Rethinking Measurement of Movement-Evoked Pain with Digital Technology.medRxiv : the preprint server for health sciences · 2025
    Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Genevieve S SilvaBrigham and Women's Hospital Boston Massachusetts.ORCID https://orcid.org/0000-0002-4935-3523
Heidi YangBrigham and Women's Hospital Boston Massachusetts.
Jamie E CollinsBrigham and Women's Hospital and Harvard Medical School Boston Massachusetts.ORCID https://orcid.org/0000-0001-8413-007X
Elena LosinaBrigham and Women's Hospital and Harvard Medical School Boston Massachusetts.ORCID https://orcid.org/0000-0002-3424-0892

Funding

VERITY: Value and Evidence in Rheumatology using bioInformaTics, and advanced analYticsP30AR072577 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI Katherine Phoenix Liao · 2017 to 2026
$9.8M
Optimizing the value of pain management in knee OA patients with comorbiditiesR01AR074290 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI Elena Losina · 2018 to 2026
$5.9M
Patient Oriented Research and Mentoring Program in OrthopedicsK24AR057827 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI LOSINA, ELENA · 2010 to 2019
$1.7M
Studying Physical Activity Rewards and Telephonic Active CoachingU34AR069187 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI LOSINA, ELENA · 2016 to 2017
$465k
Study of Physical Activity Rewards after Knee Surgery (SPARKS)R21AR063913 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI LOSINA, ELENA · 2013 to 2014
$410k
NIAMS NIH HHS K24 AR057827NIAMS NIH HHS P30 AR072577NIAMS NIH HHS R01 AR074290NIAMS NIH HHS R21 AR063913NIAMS NIH HHS U34 AR069187
6 · The paper itself

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.

Identifiers

PMID31777843
PMCPMC6857976

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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.