Immersive Virtual Nature Environments for Stress Reduction: A Between‐Subjects Experimental Study

Immersive virtual nature (IVN) is an effective strategy for mitigating anxiety and stress associated with prolonged indoor lifestyles. This study evaluated stress recovery differences across various IVN scenes that incorporate different combinations of natural elements. Initial identification of key elements for creating relaxing digital environments was conducted through an online survey. Subsequently, a between-subjects experiment involving six distinct scenario configurations was implemented with a participant pool of 61 individuals. Following stress induction, recovery was assessed, measuring physiological indices such as heart rate, the root mean square of successive differences (RMSSD), skin conductance level (SCL), and the electroencephalography alpha/beta power ratio. Psychological responses were evaluated using the State-Trait Anxiety Inventory-State form and Subjective Coordinate Scale. The results indicated that IVN scenes featuring both water and plants significantly improved RMSSD and SCL recovery compared to scenarios devoid of any elements. Each element uniquely influenced the alpha/beta ratio, with notable variations in recovery rates across different scenarios. Participants reported enhanced emotional relaxation following exposure to IVN settings. This study substantiates the differential restorative effects of various element combinations and underscores the pivotal roles of water, plants, sunlight, and color-material-finish in the optimized design and development of digital nature scenes.

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Publication Details

Journal
Annals of the New York Academy of Sciences
Published
2025-12-07
DOI
https://doi.org/10.1111/nyas.70145
Citations
1
Primary Topic
Urban Green Space and Health
Type
article
Field-Weighted Citation Impact
1.20
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article

Immersive Virtual Nature Environments for Stress Reduction: A Between‐Subjects Experimental Study

Yidan Qiao, Jiahui Wu, Lin Ma, Qiyuan An et al.
1 citations
Annals of the New York Academy of Sciences
Urban Green Space and Health
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article

Immersive Virtual Nature Environments for Stress Reduction: A Between‐Subjects Experimental Study

Yidan Qiao, Jiahui Wu, Lin Ma, Qiyuan An, Dengkai Chen, Xinggang Hou, Jing Chen, Yizhou Li, Qiuyuan Zhu
article en
1 citations

Abstract

Immersive virtual nature (IVN) is an effective strategy for mitigating anxiety and stress associated with prolonged indoor lifestyles. This study evaluated stress recovery differences across various IVN scenes that incorporate different combinations of natural elements. Initial identification of key elements for creating relaxing digital environments was conducted through an online survey. Subsequently, a between-subjects experiment involving six distinct scenario configurations was implemented with a participant pool of 61 individuals. Following stress induction, recovery was assessed, measuring physiological indices such as heart rate, the root mean square of successive differences (RMSSD), skin conductance level (SCL), and the electroencephalography alpha/beta power ratio. Psychological responses were evaluated using the State-Trait Anxiety Inventory-State form and Subjective Coordinate Scale. The results indicated that IVN scenes featuring both water and plants significantly improved RMSSD and SCL recovery compared to scenarios devoid of any elements. Each element uniquely influenced the alpha/beta ratio, with notable variations in recovery rates across different scenarios. Participants reported enhanced emotional relaxation following exposure to IVN settings. This study substantiates the differential restorative effects of various element combinations and underscores the pivotal roles of water, plants, sunlight, and color-material-finish in the optimized design and development of digital nature scenes.

Annals of the New York Academy of SciencesVol. 1556(1)
Northwestern Polytechnical University (CN), Wuhan Ship Development & Design Institute (CN)
Openalex Percentile: Top 16%
Urban Green Space and Health
1.20
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