Evidence map›Paper›PMID 40087638›Full record

ArticleBMC pediatrics2025

Monitoring of child-specific activities in ambulatory children with and without developmental disabilities.

Barbara Engels, Manon A T Bloemen, Richard Felius, Karlijn Damen, Eline A M Bolster, Harriët Wittink, Raoul H H Engelbert, Jan Willem Gorter

Abstract readValidation Study
In one paragraph

Article in BMC pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

8 authors.

Barbara EngelsResearch Centre for Healthy and Sustainable Living, Research Group Lifestyle and Health, Utrecht University of Applied Sciences, Utrecht, The Netherlands.
Manon A T BloemenResearch Centre for Healthy and Sustainable Living, Research Group Lifestyle and Health, Utrecht University of Applied Sciences, Utrecht, The Netherlands. manon.bloemen@hu.nl.
Richard FeliusResearch Centre for Healthy and Sustainable Living, Research Group Lifestyle and Health, Utrecht University of Applied Sciences, Utrecht, The Netherlands.
Karlijn DamenResearch Centre for Healthy and Sustainable Living, Research Group Lifestyle and Health, Utrecht University of Applied Sciences, Utrecht, The Netherlands.
Eline A M BolsterResearch Centre for Healthy and Sustainable Living, Research Group Lifestyle and Health, Utrecht University of Applied Sciences, Utrecht, The Netherlands.
Harriët WittinkResearch Centre for Healthy and Sustainable Living, Research Group Lifestyle and Health, Utrecht University of Applied Sciences, Utrecht, The Netherlands.
Raoul H H EngelbertCentre of Expertise Urban Vitality, Faculty of Health, Amsterdam University of Applied Sciences, Amsterdam, The Netherlands.
Jan Willem GorterUMC Utrecht Brain Center and Center of Excellence for Rehabilitation Medicine, Utrecht, the Netherlands.

Funding

Foundation Innovation Alliance-Regional Attention and Action for Knowledge Circulation (SIA Raak) MKB12.OO2
6 · The paper itself

Abstract

backgroundPediatric healthcare professionals facilitate children to enhance and maintain a physically active lifestyle. Activity monitors (AM) can help pediatric healthcare professionals assess physical activity in everyday life. However, validation research of activity monitors has often been conducted in laboratories and insight into physical activity of children in their own everyday environment is lacking. Our goal was to study the criterion validity of a prototype AM (AM-p) model in a natural setting.

methodsCross-sectional community-based study with ambulatory children (2-19 years) with and without developmental disability. Children wore the AM-p on the ankle and were filmed (gold standard) while performing an activity protocol in a natural setting. We labelled all videos per 5-second epoch with individual activity labels. Raw AM-p data were synchronized with activity labels. Using machine learning techniques, activity labels were subdivided in three pre-defined categories. Accuracy, recall, precision, and F1 score were calculated per category.

resultsWe analyzed data of 93 children, of which 28 had a developmental disability. Mean age was 11 years (SD 4.5) with 55% girls. The AM-p model differentiated between 'stationary', 'cycling' and 'locomotion' activities with an accuracy of 82%, recall of 78%, precision of 75%, and F1 score of 75%, respectively. Children older than 13 years with typical development can be assessed more accurately than younger children (2-12 years) with and without developmental disabilities.

conclusionThe single ankle-worn AM-p model can differentiate between three activity categories in children with and without developmental disabilities with good accuracy (82%). Because the AM-p can be used for a heterogenous group of ambulatory children with and without developmental disabilities, it may support the clinical assessment for pediatric healthcare professionals in the future.

Indexed as

Developmental DisabilitiesExerciseMonitoring, AmbulatoryAdolescentChildChild, PreschoolCross-Sectional StudiesFemaleHumansMachine LearningMaleReproducibility of ResultsYoung AdultAccuracyActivity monitorDevice-measured physical activityPediatric physiotherapyPerformance

Identifiers

PMID40087638
PMCPMC11909815

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.