Virtual reality-based therapy for substance use disorder: a systematic review and Bayesian meta-analysis

This Bayesian meta-analysis evaluated virtual reality (VR) therapy for substance use disorder (SUD). A total of 22 studies involving 2648 participants were included. VR-based therapy reduced substance craving compared to controls (standardized mean difference (SMD) = − 0.75, 95% credible intervals (CrI): −1.72 to 0.00, posterior probability (PP) = 83.30%, inclusion Bayes factor (BF) = 5.00, tau(τ) = 1.26).

Subgroup analyses showed that VR aversion therapy (VR-AT), the illicit substance use disorder (ISUD) subgroup, and single-session within 30 minutes each demonstrated significant reductions in craving. Craving reductions showed little difference across immersion levels, and meta-regression found no reliable linear/non‑linear relationship between total VR duration and efficacy. Leave-one-out and prior sensitivity analyses confirmed the robustness of the results.

VR improved executive function (SMD = −0.53, 95% CrI: −1.89 to 0.00, PP = 79.70%, inclusion BF = 3.94, τ = 0.11) and reduced anxiety symptoms (SMD = −0.33, 95% CrI: −0.72 to 0.00, PP = 85.90%, inclusion BF = 6.11, τ = 0.08). Evidence quality was low for all outcomes. No credible evidence supported its superiority over controls in abstinence rate, self-efficacy, depression, or dropout rate.

Substantial heterogeneity across effect estimates highlights the need for additional high-quality RCTs. This work was supported by the National Natural Science Foundation of China (grant number: 8247154447) and Chengdu Municipal Health Commission (WXLH202402020). The funders played no role in study design, data collection, analysis and interpretation of data, or the writing of this manuscript.

The Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China Qiao-Mei Wu, Hong-Lin Mei, Lu Yuan, Yu-Xin Zhang, Bei Lv, Kulachai Pantila & Hui Zheng The authors declare no competing interests. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material.

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