Development and validation of a design model of virtual-reality therapeutic landscapes for anxiety reduction and emotion regulation

Background: Exposure to therapeutic landscapes has been consistently associated with reduced stress, improved affect, and enhanced emotion regulation among young adults. However, access to such environments is often limited on urban campuses where anxiety is prevalent. In response, this study conceptualizes the virtual therapeutic landscape (VTL) and proposes a design and evaluation model that translates therapeutic landscape theory into immersive virtual reality (VR). Methods: A three-stage mixed-methods design was employed. Semi-structured interviews (n = 18) were thematically analyzed to identify core experiential dimensions that informed VTL model development. Expert analytic hierarchy process (AHP) ratings (n = 12) yielded weights for domains and sub-criteria with acceptable consistency. On this basis, a standardized VTL exposure was administered to university students (n = 60), who completed psychometric questionnaires. Text-mined features from open-ended responses were integrated with these outcomes to refine the expert-weighted model. Results: The calibrated model produced a coherent weighting structure, with sensory experience receiving the highest weight among the experiential dimensions. Brief VTL exposure significantly reduced state anxiety (p < 0.001, d = 1.040) and negative affect (p < 0.001, d = 0.570) and increased subjective vitality (p < 0.001, d = 0.794). Text mining supported an architecture in which sensory-narrative coupling and low-friction interaction experience act as primary levers, while personalization experience moderates these effects. Conclusions: This study develops a design and evaluation model for VTL targeting anxiety and emotion regulation in university students. Brief VTL exposure has shown measurable psychometric change; long-term effects and variation across VTL types remain priorities for future research.