-
Something wrong with this record ?
Fitbit's accuracy to measure short bouts of stepping and sedentary behaviour: validation, sensitivity and specificity study
J. Delobelle, E. Lebuf, DV. Dyck, S. Compernolle, M. Janek, F. Backere, T. Vetrovsky
Status not-indexed Language English Country United States
Document type Journal Article
NLK
Directory of Open Access Journals
from 2015
Free Medical Journals
from 2015
PubMed Central
from 2015
Europe PubMed Central
from 2015
ProQuest Central
from 2018-01-01
Open Access Digital Library
from 2015-12-01
Health & Medicine (ProQuest)
from 2018-01-01
ROAD: Directory of Open Access Scholarly Resources
from 2015
- Publication type
- Journal Article MeSH
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.
References provided by Crossref.org
- 000
- 00000naa a2200000 a 4500
- 001
- bmc24012529
- 003
- CZ-PrNML
- 005
- 20240726151358.0
- 007
- ta
- 008
- 240723e20240617xxu f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1177/20552076241262710 $2 doi
- 035 __
- $a (PubMed)38894943
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a xxu
- 100 1_
- $a Delobelle, Julie $u Physical Activity & Health, Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium $u Research Foundation Flanders (FWO), Brussels, Belgium $1 https://orcid.org/0000000337712848
- 245 10
- $a Fitbit's accuracy to measure short bouts of stepping and sedentary behaviour: validation, sensitivity and specificity study / $c J. Delobelle, E. Lebuf, DV. Dyck, S. Compernolle, M. Janek, F. Backere, T. Vetrovsky
- 520 9_
- $a 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.
- 590 __
- $a NEINDEXOVÁNO
- 655 _2
- $a časopisecké články $7 D016428
- 700 1_
- $a Lebuf, Elien $u Physical Activity & Health, Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium $u Research Foundation Flanders (FWO), Brussels, Belgium
- 700 1_
- $a Dyck, Delfien Van $u Physical Activity & Health, Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium
- 700 1_
- $a Compernolle, Sofie $u Physical Activity & Health, Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium $u Research Foundation Flanders (FWO), Brussels, Belgium
- 700 1_
- $a Janek, Michael $u Faculty of Physical Education and Sport, Charles University, Prague, Czech Republic
- 700 1_
- $a Backere, Femke De $u Faculty of Engineering and Architecture, Department of Information Technology, Ghent University, Ghent, Belgium
- 700 1_
- $a Vetrovsky, Tomas $u Faculty of Physical Education and Sport, Charles University, Prague, Czech Republic
- 773 0_
- $w MED00209356 $t Digital health $x 2055-2076 $g Roč. 10 (20240617), s. 20552076241262710
- 856 41
- $u https://pubmed.ncbi.nlm.nih.gov/38894943 $y Pubmed
- 910 __
- $a ABA008 $b sig $c sign $y - $z 0
- 990 __
- $a 20240723 $b ABA008
- 991 __
- $a 20240726151351 $b ABA008
- 999 __
- $a ok $b bmc $g 2125399 $s 1224392
- BAS __
- $a 3
- BAS __
- $a PreBMC-PubMed-not-MEDLINE
- BMC __
- $a 2024 $b 10 $c - $d 20552076241262710 $e 20240617 $i 2055-2076 $m Digital health $n Digit Health $x MED00209356
- LZP __
- $a Pubmed-20240723
