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Immersive Nature: How Virtual Landscapes Influence Subjective and Physiological Stress Levels
University of Skövde, School of Bioscience.
2025 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

As urbanization increases and natural access decreases, stress levels among individuals are rising. Previous literature suggests that nature exposure, whether real or simulated, can improve both physiological well-being. This study explored whether short-term exposure to immersive virtual reality environments, specifically nature-based versus urban landscapes, could influence stress levels. A within-subject design was used in which 20 participants experienced both nature and an urban VR condition. Stress was measured using self-reported data from the State-Trait Anxiety Inventory and physiological data from heart rate variability. Participants reported significantly lower subjective stress following the nature VR condition compared to both the baseline and urban VR conditions. However, no significant differences in heart rate variability were observed between the nature and baseline conditions, nor between the nature and urban VR conditions.

Place, publisher, year, edition, pages
2025. , p. 40
Keywords [en]
virtual reality, stress reduction, neuroscience, nature exposure, heart rate variability
National Category
Neurosciences
Identifiers
URN: urn:nbn:se:his:diva-25677OAI: oai:DiVA.org:his-25677DiVA, id: diva2:1986368
Subject / course
Cognitive Neuroscience
Educational program
Kognitiv neurovetenskap: Medvetandet och hjärnan - magisterprogram
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Examiners
Available from: 2025-07-31 Created: 2025-07-31 Last updated: 2025-09-29Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf