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Fitbit's accuracy to measure short bouts of stepping and sedentary behaviour: validation, sensitivity and specificity study

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11510%2F24%3A10481653" target="_blank" >RIV/00216208:11510/24:10481653 - isvavai.cz</a>

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=OvpMc7f5y1" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=OvpMc7f5y1</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1177/20552076241262710" target="_blank" >10.1177/20552076241262710</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Fitbit's accuracy to measure short bouts of stepping and sedentary behaviour: validation, sensitivity and specificity study

  • Original language description

    Objective This study aims to assess the suitability of Fitbit devices for real-time physical activity (PA) and sedentary behaviour (SB) monitoring in the context of just-in-time adaptive interventions (JITAIs) and event-based ecological momentary assessment (EMA) studies.Methods Thirty-seven adults (18-65 years) and 32 older adults (65+) from Belgium and the Czech Republic wore four devices simultaneously for 3 days: two Fitbit models on the wrist, an ActiGraph GT3X+ at the hip and an ActivPAL at the thigh. Accuracy measures included mean (absolute) error and mean (absolute) percentage error. Concurrent validity was assessed using Lin&apos;s concordance correlation coefficient and Bland-Altman analyses. Fitbit&apos;s sensitivity and specificity for detecting stepping events across different thresholds and durations were calculated compared to ActiGraph, while ROC curve analyses identified optimal Fitbit thresholds for detecting sedentary events according to ActivPAL.Results Fitbits demonstrated validity in measuring steps on a short time scale compared to ActiGraph. Except for stepping above 120 steps/min in older adults, both Fitbit models detected stepping bouts in adults and older adults with sensitivities and specificities exceeding 87% and 97%, respectively. Optimal cut-off values for identifying prolonged sitting bouts achieved sensitivities and specificities greater than 93% and 89%, respectively.Conclusions This study provides practical insights into using Fitbit devices in JITAIs and event-based EMA studies among adults and older adults. Fitbits&apos; reasonable accuracy in detecting short bouts of stepping and SB makes them suitable for triggering JITAI prompts or EMA questionnaires following a PA or SB event of interest.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    30306 - Sport and fitness sciences

Result continuities

  • Project

    <a href="/en/project/NU21-09-00007" target="_blank" >NU21-09-00007: mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Digital Health

  • ISSN

    2055-2076

  • e-ISSN

  • Volume of the periodical

    10

  • Issue of the periodical within the volume

    June

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    16

  • Pages from-to

    20552076241262710

  • UT code for WoS article

    001249697700001

  • EID of the result in the Scopus database

    2-s2.0-85196186298