Evidence map›Paper›PMID 41264348›Full record

ArticleJMIR formative research2025

Three Body-Worn Accelerometers in the French NutriNet-Santé Cohort: Feasibility and Acceptability Study.

Abdouramane Soumaré, Léopold K Fezeu, Jérôme Bouchan, Fabienne Delestre, Alice Bellicha, Greet Cardon, Alan Donnelly, Antje Hebestreit, Mathilde Touvier, Jean-Michel Oppert and 1 more

Abstract read
In one paragraph

Article in JMIR formative research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Abdouramane SoumaréUniversité Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Centre for Research in Epidemiology and StatisticS (CRESS), Nutritional Epidemiology Research Team (EREN), F-93017, Bobigny, Paris, France.ORCID 0009-0001-2587-3508
Léopold K FezeuUniversité Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Centre for Research in Epidemiology and StatisticS (CRESS), Nutritional Epidemiology Research Team (EREN), F-93017, Bobigny, Paris, France.ORCID 0000-0002-7589-3179
Jérôme BouchanUniversité Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Centre for Research in Epidemiology and StatisticS (CRESS), Nutritional Epidemiology Research Team (EREN), F-93017, Bobigny, Paris, France.ORCID 0000-0003-0560-894X
Fabienne DelestreDepartment of Nutrition, Human Nutrition Research Center Ile-de-France (CRNH IdF), Pitié-Salpêtrière Hospital (AP-HP), Sorbonne University, Paris, null, France.ORCID 0000-0002-5027-5059
Alice BellichaUniversité Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Centre for Research in Epidemiology and StatisticS (CRESS), Nutritional Epidemiology Research Team (EREN), F-93017, Bobigny, Paris, France.ORCID 0000-0002-5572-487X
Greet CardonDepartment of Movement and Sports Sciences, Ghent University, Ghent, Belgium.ORCID 0000-0003-4983-6557
Alan DonnellyHealth Research Institute, University of Limerick, Limerick, Ireland.ORCID 0000-0002-6874-0991
Antje HebestreitLeibniz Institute for Prevention Research and Epidemiology-BIPS, Bremen, Germany.ORCID 0000-0001-7354-5958
Mathilde TouvierUniversité Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Centre for Research in Epidemiology and StatisticS (CRESS), Nutritional Epidemiology Research Team (EREN), F-93017, Bobigny, Paris, France.ORCID 0000-0002-8322-8857
Jean-Michel Oppert *Université Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Centre for Research in Epidemiology and StatisticS (CRESS), Nutritional Epidemiology Research Team (EREN), F-93017, Bobigny, Paris, France.ORCID 0000-0003-0324-4820
Jérémy Vanhelst *Université Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Centre for Research in Epidemiology and StatisticS (CRESS), Nutritional Epidemiology Research Team (EREN), F-93017, Bobigny, Paris, France.ORCID 0000-0002-0570-1522

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate assessment of physical activity (PA) in large population-based cohorts remains a major methodological challenge. Self-reported questionnaires, although commonly used due to low cost and simplicity, are prone to recall and social desirability biases, causing misclassification and weakened associations with health outcomes. Body-worn accelerometers provide more objective and reliable measurements, but their acceptability and feasibility in large-scale epidemiological studies must be carefully evaluated to ensure compliance, data quality, and scalability.

objectiveThe primary objective was to assess the acceptability of using 3 body-worn accelerometer devices (Fitbit, ActivPAL, and ActiGraph) among healthy middle-aged adults participating in the NutriNet-Santé cohort. The secondary objective was to assess the feasibility of these devices in terms of wear-time compliance under free-living conditions.

methodsThis is an ancillary study of the European WEALTH (WEarable sensor Assessment of physicaL and eaTing beHaviors) project that was conducted between 2023 and 2024 in a subsample of participants of the NutriNet-Santé surveillance in France. This sample included 126 healthy participants (62 men), with a mean age of 46.3 (SD 11.3) years. Participants wore simultaneously 3 body-worn accelerometer devices (Fitbit [wrist], ActivPAL [thigh], and ActiGraph [waist]) for 7 consecutive days. After the wear period, participants completed a specific 22-item web-based questionnaire, regarding their acceptability of using each device. This questionnaire was based on the Technology Acceptance Model, which identifies perceived usefulness and ease of use as key determinants of technology acceptance. Items were rated on a 5-point Likert scale (1=strongly disagree to 5=strongly agree). Feasibility was assessed based on the accelerometer wear time data reported in a log diary by participants. A valid day was defined as ≥600 minutes per day of wear time, and a valid week as at least 4 of such days. Acceptability scores were compared between devices using ANOVA, and feasibility outcomes were compared using Kruskal-Wallis tests.

resultsThe acceptability assessment based on the questionnaire revealed significant differences among the 3 devices (P<.001). The Fitbit achieved the highest acceptability score (mean 80.5/100, SD 8.13) across most criteria such as comfort, ease of use, and social acceptability, while the ActiGraph received the lowest score (mean 71.7, SD 8.68), mainly due to challenges with stability and interference during PA. In terms of feasibility, the 3 accelerometers demonstrated high compliance, with the ActivPAL recording the highest daily wear time, followed by the Fitbit and the ActiGraph (P<.001).

conclusionsResults from our study showed that the Fitbit watch appears as the most accepted device for measuring PA in free-living conditions in the NutriNet-Santé study. The large-scale use of such a device must now be evaluated in terms of logistics, cost, and data privacy.

Indexed as

AccelerometryExerciseWearable Electronic DevicesAdultCohort StudiesFeasibility StudiesFemaleFranceHumansMaleMiddle Agedaccelerometeracceptabilitycohort studyfeasibility

Identifiers

PMID41264348
PMCPMC12679073

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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.