Abstract
The therapeutic use of virtual reality (VR) is well established in the treatment of anxiety disorders. As an early step to develop a VR environment to desensitize people suffering from eco-anxiety, we created an “emotion-to-picture match” task to characterize their behavioral and physiological responses during exposure to neutral and threatening environmental stimuli. Twenty-nine participants who were identified as “high” or “low” scorers in the Hogg Eco-Anxiety Scale (Hogg et al. 2021) were exposed to three blocks of randomized “eco-anxiety” and “neutral” images, while their electrocardiogram and skin conductance level was recorded. In each trial, participants had to choose from six emotions the one that would closely match their feelings towards the image. During “eco-anxiety” images, the “high” scorers addressed significantly more “anger” than the “low” scorers, whereas “seeking” emotions were more frequent among the latter. In addition, “neutral” images also evoked significantly more “panic” among the “high” eco-anxiety participants, whereas “seeking” emotions were more frequently experienced by the “low” eco-anxiety participants. Surprisingly, “high” eco-anxiety participants displayed higher heart rate variability and lower electrodermal activity than “low” eco-anxiety participants throughout the task, a finding that is at odds with the current understanding of physiological symptoms of anxiety. The design of therapeutic VR environments should forecast all sorts of discomfort that patients are willing to tolerate during VR exposure therapy.
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Acknowledgments
This study was supported by UNIDCOM under a grant from the Fundação para a Ciência e Tecnologia (FCT) No. UIDB/00711/2020 attributed to UNIDCOM – Unidade de Investigação em Design e Comunicação, Lisbon, Portugal.
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Quelhas Martins, A., Ferrajão, P., Revés, B., Torres, N. (2025). Towards a VR Environment for Desensitization of Ecological Anxiety. In: Chen, J.Y.C., Fragomeni, G., Streitz, N.A., Konomi, S., Fang, X. (eds) HCI International 2024 – Late Breaking Papers. HCII 2024. Lecture Notes in Computer Science, vol 15377. Springer, Cham. https://doi.org/10.1007/978-3-031-76812-5_11
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