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Efficacy of digital interventions in social anxiety disorder: a systematic review and Bayesian network meta-analysis

Journal
Frontiers in psychiatry (Q1)
Published
10 July 2026
Study design
Systematic review / meta-analysis of RCTs
Evidence level
Level 1, High (CEBM 1a)
Authors
Yang Li, Zeng-Yun-Ou Zhang, Li-Ping He, Xiao-Qiu Zhou, Bo Yu, Xue-Min Huang, et al.
PMID
42500313
DOI
10.3389/fpsyt.2026.1883150

Why clinicians should know about it

Abstract

BACKGROUND: Social anxiety disorder (SAD) is characterized by a significant and persistent fear of social or performance situations. The prevalence of SAD has gradually increased recently, and the unique advantages of digital interventions (DIs) have gained traction in psychiatric disorders. However, there is currently no comprehensive review comparing the effectiveness of diverse DIs for SAD. METHODS: Randomized controlled trials (RCTs) evaluating DIs for patients with SAD were identified by searching the PubMed, Cochrane Library, and Embase databases from January 1, 1995, to March 31, 2025. The study protocol for this network meta-analysis was registered in PROSPERO. Data were analyzed via Bayesian framework network meta-analysis. RESULTS: Forty-two RCTs were included. The results showed that DIs exerted better efficacy than non-digital interventions and wait-list controls (WLC). Different forms of internet-based cognitive behavioral therapy (ICBT) demonstrated robust effects across all four outcomes. Internet-based cognitive therapy (ICT) yielded favorable effects in reducing social anxiety and depressive symptoms. VR showed relatively large effect sizes for improving quality of life. CONCLUSION: DIs can be recommended as adjunctive or combined treatments for SAD. Different forms of ICBT show consistent efficacy and can serve as the first-line option among digital interventions. We recommend promoting the application of DIs to expand treatment coverage for SAD and overcome the limitations of traditional psychotherapy. SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD420251077835.

Abstract as published, via PubMed.

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For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.