Harnessing immersive virtual reality: A comprehensive scoping review of its applications in assessing, understanding, and treating eating disorders
Open accessAbstract
BACKGROUND: Immersive Virtual Reality (IVR) has shown promise in the assessment, understanding, and treatment of eating disorders (EDs), providing a dynamic platform for clinical innovation. This scoping review aims to synthesize the recent advancements and applications of IVR in addressing these complex psychological disorders. METHODS: This review followed the Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols, focusing on studies published in the past five years. It included peer-reviewed papers that used IVR for ED assessment, examination, or treatment. A comprehensive database search provided a selection of relevant articles, which were then methodically screened and analyzed. RESULTS: Twenty studies met the inclusion criteria, with a primary focus on Anorexia Nervosa (AN), Bulimia Nervosa (BN), and Binge Eating Disorder (BED). The application of IVR was categorized into three areas: assessment, understanding, and treatment. IVR was found to be an effective tool in assessing body image distortions and emotional responses to food, providing insights that are less accessible through traditional methods. Furthermore, IVR offers innovative treatment approaches by facilitating exposure therapy, modifying body-related biases, and enabling emotional regulation through embodied experiences. The studies demonstrate IVR's potential to improve body image accuracy, reduce food-related anxieties, and support behavioral changes in ED patients. CONCLUSION: IVR stands out as a transformative technology in the field of EDs, offering comprehensive benefits across diagnostic, therapeutic, and experiential domains. The IVR's ability to simulate the brain's predictive coding mechanisms provides a powerful avenue for delivering embodied, experiential interventions that can help recalibrate distorted body representations and dysfunctional affective predictive models implicated in EDs. Future research should continue to refine these applications, ensuring consistent methodologies and wider clinical trials to fully harness IVR's potential in clinical settings.
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Taken together, the initial findings suggest a possible trend toward anxiety reduction following the intervention, particularly in trait anxiety.
“Taken together, these initial findings suggest a possible trend toward anxiety reduction following the intervention, particularly in trait anxiety [10].”
From Immersive Virtual Reality in Psychotherapeutic Interventions for Youth with Eating Disorders: A Pilot Study in a Rural Context (2025) · cites this paper as [10]
The Synthesis of Results > Treatment section reports reduced virtual food-related anxiety after exposure, and the Synthesis of Results table reports reduced body-related anxiety after VR body-exposure therapy (page numbers unavailable). These findings support a possible reduction in anxiety following intervention, but the review does not identify trait anxiety as the outcome particularly affected. (LLM, conf=0.85)
Experimental — accuracy not yet measuredThe potential of the VR technique is reinforced by the key role of prediction errors, which emerge when discrepancies occur between the patient's expectations and real experiences in the virtual environment.
“Additionally, the potential of this technique is reinforced by the key role of prediction errors, which emerge when discrepancies occur between the patient's expectations and real experiences in the virtual environment.”
From Immersive Virtual Reality in Psychotherapeutic Interventions for Youth with Eating Disorders: A Pilot Study in a Rural Context (2025) · cites this paper as [10]
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- Authors
- Di Natale, A. F., Pizzoli, S. F. M., Brizzi, G., Di Lernia, D., Frisone, F., Gaggioli, A., Rabarbari, E., Oasi, O., Repetto, C., Rossi, C., Scerrati, E., Villani, D., & Riva, G.
- Affiliations
- Università Cattolica del Sacro Cuore (IT)
- ORCID
- Venue
- Current Psychiatry Reports
- Published
- 2024-07-31
- Volume
- 26
- Issue
- 9
- Pages
- 470-486
- ISSN
- 1523-3812 (ISSN-L)
- 1535-1645
- PMC
- PMC11344702
- OpenAlex
- W4401179548
- Cited by
- 37
- References
- 48
- Citations by year
- 2026: 20 · 2025: 16 · 2024: 1
- FWCI
- 3.29
- Type
- journal article
- Language
- en
- Update notices
- correction (2024-11-12)
- Open access
- hybrid
- doi.org
- Locations
- Current Psychiatry Reports (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- IRIS eCampus Telematic University (Università degli Studi eCampus) (acceptedVersion)
- BOA (University of Milano-Bicocca) (submittedVersion, cc-by)
- PubliCatt (Università Cattolica del Sacro Cuore) (submittedVersion, cc-by)
- Funders
- Università Cattolica del Sacro Cuore
- Topics
- Social Sciences › Psychology › Clinical Psychology › Eating Disorders and Behaviors
- Physical Sciences › Computer Science › Human-Computer Interaction › Virtual Reality Applications and Impacts
- Social Sciences › Psychology › Clinical Psychology › Body Image and Dysmorphia Studies
- Keywords
- immersive virtual reality, eating disorders, anorexia nervosa, bulimia nervosa, binge eating disorder, body image distortion, exposure therapy, emotion regulation, embodied experience, predictive coding, food-related anxiety
- MeSH terms
- Virtual Reality, Feeding and Eating Disorders, Humans, Bulimia Nervosa, Virtual Reality Exposure Therapy
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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