How virtual urban green spaces influence stress and risk-taking

Frontiers in Psychology. 2026. Vol. 17. Article 1710257.

Dorri Sedeh S., Kosonogov V., Kerimova N., Meidenbauer K. L., Klucharev V.

Introduction: 

As cities continue to grow, access to natural environments is becoming more limited, contributing to increased stress levels in urban populations. Panoramic 360° videos provide a creative and scalable means of simulating natural environments, potentially reducing stress in city residents under controlled settings. Here, we examined whether short immersive experiences in different urban environments support stress recovery and influence risk-taking behavior.

Methods: 

Sixty-six participants were subjected to stress inductions using the threat-of-shock paradigm before viewing 360° monoscopic videos of urban walks through a park or a highway, or a minimal-stimulation control video. While participants watched videos using VR headsets, we recorded their heart rate and skin conductance responses. We also collected self-reported stress ratings and assessed risk-taking behavior using the Balloon Analogue Risk Task.

Results: 

The results showed that self-reported stress was significantly lower following the urban park video compared to both the highway and control conditions. Physiologically, heart rate and skin conductance responses were significantly lower during the park conditions compared to the highway conditions, but did not differ significantly between the park and control conditions. No effects of the 360° video environments were observed on heart rate variability or risk-taking behavior.

Discussion: 

These findings suggest that brief exposure to virtual urban green spaces supports stress recovery following acute stress, particularly relative to highly arousing urban environments.

Keywords: stress, risk-taking, heart rate, Greenery

Publication based on the results of: Multidisciplinary study of behavior and decision-making in health population and patients using behavioral, economic, neurocognitive, neuroeconomic, neurocomputational and neural network approaches (2025)