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Application of mixed reality in prehospital emergency nursing education: A scoping review
Lu Li1, Sisi Fan2, Yuxin Xing2
1Nursing Department, the Third Xiangya Hospital, Central South University, Changsha, Hunan, China; Xiangya Nursing School, Central South University, Changsha, Hunan, China.
Aim:
This paper provides a scoping review of the literature on prehospital emergency mixed reality (MR) nursing education and explores the impact of MR devices in prehospital emergency nursing education.
Background:
The timely intervention of prehospital paramedics plays a critical role in emergency situations. Training in a real environment requires significant resource consumption and allows only limited training frequency and variability. Therefore, MR training environments with realistic simulations are necessary. Currently, little is known regarding which MR devices are appropriate for prehospital emergency nursing education and how their design meets various educational goals.
Methods:
A scoping review was conducted following the Joanna Briggs Institute scoping review methodology. Peer-reviewed articles were searched across MEDLINE, EMBASE, CINAHL, Web of Science, SCOPUS, PUBMED and the Cochrane Library. Studies had to include MR simulations in the field of prehospital emergency nursing education.
Results:
Twenty-one articles were identified. The analysis revealed that MR devices can be divided into three categories, desktop VR simulations, immersive VR simulations and MR simulations. MR is mostly used to simulate small accident scenes and disaster emergency response training. MR can obviously improve students' enthusiasm and learning efficiency but cannot change the learning results.
Conclusions:
Various MR devices are widely used in prehospital emergency nursing education. This practice can obviously improve students' enthusiasm and learning efficiency. However, a gap remains between MR simulations and real simulations. Nevertheless, MR can be used as an auxiliary teaching resource. In the future, attempts can be made to develop MR devices combined with artificial intelligence.
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