NursingXR: Advancing Nursing Education Through Virtual Reality-Based Training

The increasing complexity of healthcare delivery and the advancements in medical technology have highlighted the necessity for improved training in nursing education. While traditional training methods have their merits, they often encounter challenges such as limited access to clinical placements, static physical simulations, and performance anxiety during hands-on practice. Virtual reality (VR) has been increasingly adopted for immersive and interactive training environments, allowing nursing students to practice essential skills repeatedly in realistic, risk-free settings. This study presents NursingXR, a VR-based platform designed to help nursing students master essential clinical skills. With a scalable and flexible architecture, NursingXR is tailored to support a variety of nursing lessons and adapt to evolving curricula. The platform has a modular design and offers two interactive modes: Training Mode, which provides step-by-step guided instruction, and Evaluation Mode, which allows for independent performance assessment. This article details the development process of the platform, including key design principles, system architecture, and implementation strategies, while emphasizing its utility and scalability. A mixed-methods evaluation involving 78 participants—both novices and experts—was conducted to evaluate the platform’s usability and user satisfaction. The results underscore NursingXR’s effectiveness in fostering an effective and engaging learning environment as well as its potential as a supplementary resource for nursing training.

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Institutions

Publication Details

Journal
Applied Sciences
Published
2025-03-09
DOI
https://doi.org/10.3390/app15062949
Citations
4
Primary Topic
Virtual Reality Applications and Impacts
Type
article
Field-Weighted Citation Impact
7.74

Funders

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article

NursingXR: Advancing Nursing Education Through Virtual Reality-Based Training

Mohammad F. Obeid, Ahmed Ewais, Mohammad Asia
4 citations
Applied Sciences
Virtual Reality Applications and Impacts
7.74
article

NursingXR: Advancing Nursing Education Through Virtual Reality-Based Training

Mohammad F. Obeid, Ahmed Ewais, Mohammad Asia
article en
4 citations

Abstract

The increasing complexity of healthcare delivery and the advancements in medical technology have highlighted the necessity for improved training in nursing education. While traditional training methods have their merits, they often encounter challenges such as limited access to clinical placements, static physical simulations, and performance anxiety during hands-on practice. Virtual reality (VR) has been increasingly adopted for immersive and interactive training environments, allowing nursing students to practice essential skills repeatedly in realistic, risk-free settings. This study presents NursingXR, a VR-based platform designed to help nursing students master essential clinical skills. With a scalable and flexible architecture, NursingXR is tailored to support a variety of nursing lessons and adapt to evolving curricula. The platform has a modular design and offers two interactive modes: Training Mode, which provides step-by-step guided instruction, and Evaluation Mode, which allows for independent performance assessment. This article details the development process of the platform, including key design principles, system architecture, and implementation strategies, while emphasizing its utility and scalability. A mixed-methods evaluation involving 78 participants—both novices and experts—was conducted to evaluate the platform’s usability and user satisfaction. The results underscore NursingXR’s effectiveness in fostering an effective and engaging learning environment as well as its potential as a supplementary resource for nursing training.

Applied SciencesVol. 15(6)
Shenandoah University (US), Arab American University (PS)
U.S. Department of State
Openalex Percentile: Top 3%
Virtual Reality Applications and Impacts
7.74
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NursingXR: Advancing Nursing Education Through Virtual Reality-Based Training — Mohammad F. Obeid, Ahmed Ewais, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS