Virtual reality interventions in obesity and eating disorders: a systematic review of biomarker, clinical, and behavioral outcomes
Abstract
Obesity and eating disorders (EDs) are major public health challenges associated with high morbidity and mortality. This systematic review evaluated the effects of immersive virtual reality (VR) interventions on clinical outcomes and biomarker-domain outcomes in obesity and EDs. Following PRISMA 2020 guidelines, PubMed, Web of Science, and PsycINFO were searched through to April 2025. Eligible studies included immersive VR interventions targeting obesity or EDs and reporting at least one biomarker-domain outcome (anthropometric, physiological/autonomic, endocrine/metabolic, or neurocognitive/eye-tracking). Risk of bias was assessed using Joanna Briggs Institute tools. When at least three RCTs reported comparable outcomes, random-effects meta-analyses were performed. Twenty-three studies met the inclusion criteria (11 obesity, 12 EDs). ED studies included anorexia nervosa, bulimia nervosa, and binge-eating disorder. In obesity, VR-enhanced cognitive-behavioral therapy (VR-CBT) was associated with weight-loss maintenance, while VR-based exercise interventions were associated with short-term reductions in BMI and body weight. A meta-analysis of four RCTs showed a significant pooled effect of VR compared with control on anthropometric outcomes (Hedges' g = - 0.35, 95% CI [-0.61, - 0.09], p = .009; I² = 0%), with a numerically larger effect for VR-CBT. In EDs, VR-CBT was associated with reductions in body image disturbance and fear of weight gain, while VR cue-exposure therapy…
How strong is the evidence?
Evidence Hub reads this as a systematic review. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.