Virtual reality analytics map (VRAM): A conceptual framework for detecting mental disorders using virtual reality data

Abstract

Virtual reality (VR) is an emerging tool in mental health care yet its potential in diagnostic assessments remains underexplored. Recognizing the growing need of technological advancements that support traditional methods for mental health assessment, this paper introduces the Virtual Reality Analytics Map (VRAM), a novel conceptual framework designed to leverage VR analytics for the detection of symptoms of mental disorders. The VRAM framework integrates psychological constructs with VR technology, systematically mapping and quantifying behavioral domains through specific VR tasks. This approach potentially allows for the precise capture and identification of nuanced behavioral, cognitive, and affective digital biomarkers associated with symptoms of mental disorders. The benefits of the VRAM framework are demonstrated with its example application across various mental disorders ensuring the utility and versatility of the framework. By bridging the gap between psychology and technology, the VRAM framework aims to contribute to the early detection and assessment of mental disorders.