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 To illustrate cross-reality analytics, we also present hitherto unpublished results from a cross-reality study, analyzing food selection data collected in VR and connecting it with eating behavior data in physical reality.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 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. • We introduce cross-reality analytics for VR behavioral research. • VR studies fall into proxy, intervention, or cross-reality analytical categories. • Cross-reality analytics enables joint analysis of behavior from multiple realities. • A cross-reality virtual buffet-real eating study revealed novel behavioral insights. • Behaviors exclusive to VR and sensory mismatches reveal new behavioral insights.

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Publication Details

Journal
Computers in Human Behavior Reports
Published
2026-04-01
DOI
https://doi.org/10.1016/j.chbr.2026.101053
Primary Topic
Virtual Reality Applications and Impacts
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Travis D. Masterson, Jan Oliver Wallgrün, Jiayan Zhao, Kathleen Keller et al.
Computers in Human Behavior Reports
Virtual Reality Applications and Impacts
article

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

Travis D. Masterson, Jan Oliver Wallgrün, Jiayan Zhao, Kathleen Keller, Alexander Klippel, C. S. Cheah, John W. Long, Barbara J. Rolls, Timothy R. Brick, Lee Boot, Caitlyn Edwards, Nina Rosa, Sara J. Maksi
article en

Abstract

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 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. • We introduce cross-reality analytics for VR behavioral research. • VR studies fall into proxy, intervention, or cross-reality analytical categories. • Cross-reality analytics enables joint analysis of behavior from multiple realities. • A cross-reality virtual buffet-real eating study revealed novel behavioral insights. • Behaviors exclusive to VR and sensory mismatches reveal new behavioral insights.

Computers in Human Behavior ReportsVol. 22
University of Maryland, Baltimore (US), Pennsylvania State University (US), Oldham Council (GB), Wageningen University & Research (NL)
Social Science Research Institute, Pennsylvania State University
Zero hunger
Openalex Percentile: Top 32%
Virtual Reality Applications and Impacts
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