Evidence map›Paper›PMID 38894943›Full record

ArticleDigital health

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

Julie Delobelle, Elien Lebuf, Delfien Van Dyck, Sofie Compernolle, Michael Janek, Femke De Backere, Tomas Vetrovsky

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–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

15 citing papers in PubMed.

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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

7 authors.

Julie DelobellePhysical Activity & Health, Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium.ORCID https://orcid.org/0000-0003-3771-2848
Elien LebufPhysical Activity & Health, Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium.
Delfien Van DyckPhysical Activity & Health, Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium.
Sofie CompernollePhysical Activity & Health, Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium.
Michael JanekFaculty of Physical Education and Sport, Charles University, Prague, Czech Republic.
Femke De BackereFaculty of Engineering and Architecture, Department of Information Technology, Ghent University, Ghent, Belgium.
Tomas VetrovskyFaculty of Physical Education and Sport, Charles University, Prague, Czech Republic.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

accelerometryecological momentary assessmentevent-based ecological momentary assessment (EMA)FitbitJITAIjust-in-time adaptive interventionphysical activitysedentary behaviourstepwearable

Identifiers

PMID38894943
PMCPMC11185038

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.