Social anxiety disorder (SAD) is a common but often overlooked mental disorder. Its traditional diagnosis combines the assessment of cognitive symptoms with the evaluation of emotional and behavioral patterns. With the widespread use of smart phones and wearable devices, digital biomarkers available through these devices have provided a new objective quantitative method for mental health diagnosis. The aim of this study was to investigate the application of digital biomarkers in the diagnosis of social anxiety disorder. Based on the methodological framework of Arksey and O’Malley, we conducted a review using multiple databases such as PubMed, Web of Science, EMbase, Scopus and ACM Digital Library. From the establishment of each database to August 2025, any original research in the research design will focus on this topic and be published in English, using the following search strategy: (“social phobia” OR “Social Anxiety” OR “Social Anxiety Disorder”) AND (“Smartphone Sensor” OR “digital phenotyping” OR “digital phenotype” OR “digital biomarker” OR “mobile sensing” OR “passive sensing” OR “Wearable devices” OR “APP” OR “Electronic health records” OR “Electronic Medical Record”). We identified a total of 1586 studies in the database and ultimately included 15 of them. The literature mainly focuses on digital biomarkers in digital devices, and all studies have reported a positive association between these biomarkers and the prediction of social anxiety disorders. Although various digital biomarkers such as physiological indicators, behavioral patterns, and language features have shown good value in assisting the early screening and objective monitoring of social anxiety disorders, their overall development is still in its infancy and has not yet formed diagnostic tools with sufficient clinical effectiveness. Not applicable.
Qiao et al. (Thu,) studied this question.