Evidence map›Paper›PMID 40003420›Full record

ReviewInternational journal of environmental research and public health2025

The Role of Virtual Reality in Childhood Obesity Treatment: A Narrative Review.

Qutaibah Oudat, Sarah E Messiah, Alia Dawlat Ghoneum

Abstract readReview
In one paragraph

Review in International journal of environmental research and public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

3 authors.

Qutaibah OudatDepartment of Population Health, College of Nursing, University of Cincinnati, Cincinnati, OH 45221, USA.ORCID 0000-0003-2167-7371
Sarah E MessiahPeter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
Alia Dawlat GhoneumDepartment of Family Medicine, East Carolina University, 101 Heart Drive, Greenville, NC 27834, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Childhood obesity is a critical public health issue linked to long-term complications like type 2 diabetes and cardiovascular disease. This narrative review aimed to examine the effectiveness of virtual reality (VR)-based interventions in supporting key components of obesity treatment-physical activity (PA), nutrition education, and behavior change-particularly in children under 12. Using the intensive health behavior and lifestyle treatment (IHBLT) approach, we synthesized findings from studies published between 2014 and 2024. Of the studies reviewed, only one study met inclusion criteria, showing that VR-based interventions effectively increased light-intensity PA and reduced sedentary behavior in children, though these effects were not sustained long-term. The scarcity of studies limits the generalizability of these findings, emphasizing the need for caution in interpretation. Our review highlights a significant gap in the literature regarding VR's role in childhood obesity treatment. Future research should explore the efficacy of VR in promoting PA, enhancing nutrition education, and supporting sustained behavior changes. Expanding this evidence base is vital for developing accessible and engaging interventions tailored to young children. Addressing this gap could enhance obesity treatment options, offering innovative and effective strategies to improve health outcomes in this vulnerable population.

Indexed as

Pediatric ObesityVirtual RealityChildExerciseHealth BehaviorHumanschildhood obesitylifestyle treatmentobesity treatmentreviewvirtual reality

Identifiers

PMID40003420
PMCPMC11855200

What OpenQuestion holds

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Registered trials

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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.