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Fitbit's accuracy to measure short bouts of stepping and sedentary behaviour: validation, sensitivity and specificity study.
Delobelle, Julie; Lebuf, Elien; Dyck, Delfien Van; Compernolle, Sofie; Janek, Michael; Backere, Femke De; Vetrovsky, Tomas.
Afiliação
  • Delobelle J; Physical Activity & Health, Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium.
  • Lebuf E; Research Foundation Flanders (FWO), Brussels, Belgium.
  • Dyck DV; Physical Activity & Health, Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium.
  • Compernolle S; Research Foundation Flanders (FWO), Brussels, Belgium.
  • Janek M; Physical Activity & Health, Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium.
  • Backere F; Physical Activity & Health, Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium.
  • Vetrovsky T; Research Foundation Flanders (FWO), Brussels, Belgium.
Digit Health ; 10: 20552076241262710, 2024.
Article em En | MEDLINE | ID: mdl-38894943
ABSTRACT

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's concordance correlation coefficient and Bland-Altman analyses. Fitbit'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' 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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article