Using Virtual Reality for Detection and Intervention of Depression -- A Systematic Literature Review

TL;DR

This systematic review examines the use of Virtual Reality (VR) for detection and intervention of depression, synthesizing 31 studies published between 2000 and 2022. It details the VR scenes employed, the external hardware and physiological/behavioral metrics used to measure responses, and compares VR-based approaches to conventional methods and CBT, with several studies reporting positive effects but overall evidence remaining preliminary due to small samples and heterogeneity. The authors provide a practical framework, including a sensor-to-scene mapping and a design checklist, to guide future VR depression research and practice. The work highlights VR's potential to offer ecologically valid, immersive interventions while underscoring the need for robust, high-quality trials to establish generalizability and safety across diverse populations.

Abstract

The use of emerging technologies like Virtual Reality (VR) in therapeutic settings has increased in the past few years. By incorporating VR, a mental health condition like depression can be assessed effectively, while also providing personalized motivation and meaningful engagement for treatment purposes. The integration of external sensors further enhances the engagement of the subjects with the VR scenes. This paper presents a comprehensive review of existing literature on the detection and treatment of depression using VR. It explores various types of VR scenes, external hardware, innovative metrics, and targeted user studies conducted by researchers and professionals in the field. The paper also discusses potential requirements for designing VR scenes specifically tailored for depression assessment and treatment, with the aim of guiding future practitioners in this area.

Figures (2)

• Figure 1: Paper Finalization after Search Strategy
• Figure 2: Categorization of the Hardware used in detection and intervention of depression