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Virtual reality ideological and political games on students’ anxiety disorders

Published online by Cambridge University Press:  27 October 2023

Xu Zheng*
Affiliation:
Xizang Minzu University, Xianyang 712082, China
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Abstract

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Background

Anxiety Disorder (AD) is a disorder characterised by excessive fear anxiety and related disturbing behaviour. Virtual reality (VR) technology has been applied in many fields because of its multi-sensory, visualisation and immersive interactivity. Therefore, the study proposes to combine VR technology with Civic Education and help students to better improve their anxiety disorders by designing Civic Games under VR experience.

Subjects and Methods

Students suffering from anxiety disorders were taken as research objects and randomly divided into an experimental group (VR teaching experience group) and a control group (conventional Civics teaching group). Both groups of patients were guided by classroom education to control students’ psychological conditions and emotions. In the experimental group, VR teaching is assisted by VR games or VR scene experience. The experimental intervention time was six weeks, and the experimental data were statistically analysed with the help of the Self-Assessment Scale of Anxiety (SAS) and the Hamilton Anxiety Scale (HAMA). The difference was statistically significant at P<0.05.

Results

After the experimental intervention, it was found that there was a significant statistical difference in SAS scores between the two groups of students (P<0.05), and the relief of anxiety disorder symptoms in the experimental group was significantly better than that in the control group.

Conclusions

The use of VR technology has broad development prospects. It can effectively help students alleviate their anxiety state, and its combination with ideological and political education also enables students to have a clearer understanding of their emotional changes.

Acknowledgement

Scientific Research Program Funded by Shaanxi Provincial Education Department (No.22JK0587).

Type
Abstracts
Copyright
© The Author(s), 2023. Published by Cambridge University Press