CRAVE: Cross-Reality Analytics for Virtual Environments — deepening insights into human food selection and eating behavior

Virtual reality (VR) has long been hailed as an effective tool for behavioral research studies combining experimental control with ecological validity. Two frequently used categories of behavioral studies using VR can be distinguished: behavior in VR is studied as a proxy for behavior in physical reality, or behavior change in physical reality is studied after experiencing interventions in VR. In this paper, we explore and discuss a third category: behavior in VR and behavior in physical reality are analytically combined to leverage the experiential differences between the two, and to better understand human behavior. For this approach, we coin the term cross-reality analytics , where behavior in multiple realities is observed, combined and analyzed. We place these three categories in a proposed conceptual framework, and discuss similarities and differences between cross-reality analytical studies, proxy and interventions studies. To illustrate cross-reality analytics, we also present hitherto unpublished results from a cross-reality study, analyzing food selection data collected in VR and connecting it with eating behavior data in physical reality. Results show that data on virtual food choices (e.g., virtual fruit or vegetable first) are associated with physical eating behavior (e.g., total physical food consumed), and that additional insights were gained about human behavior by analyzing unique behavior in VR (e.g., physically impossible portion size manipulation) and combining it with data from physical reality (e.g., total physical food consumed). The results illustrate the potential of cross-reality analytics for developing a deeper understanding of behavioral traits, and show promise for future behavioral research.