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Artificial intelligence-enabled virtual reality simulation for clinical deterioration training: An

Sok Ying Liaw1, Khairul Dzakirin Bin Rusli1, Jian Zhi Tan1

  • 1Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.

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Summary
This summary is machine-generated.

Artificial intelligence in virtual reality simulation (AI-enabled VRS) shows promise for improving nursing students' clinical deterioration knowledge. Further integration of generative AI is recommended to enhance learning effectiveness and program acceptance.

Keywords:
Artificial intelligenceClinical deteriorationImplementation outcomeImplementation scienceImplementation strategiesInterprofessional educationSimulationVirtual reality

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Area of Science:

  • Nursing Education
  • Medical Simulation
  • Artificial Intelligence

Background:

  • AI-enabled VRS was integrated into nursing education to aid the transition to clinical practice.
  • Evaluating its effectiveness and implementation is crucial for wider adoption.
  • This study addresses the need to assess this innovative educational tool.

Purpose of the Study:

  • To evaluate the effectiveness of AI-enabled VRS in enhancing nursing students' knowledge of clinical deterioration.
  • To assess the implementation outcomes of AI-enabled VRS in nursing education.
  • To determine the acceptability, adoption, appropriateness, and feasibility of AI-enabled VRS.

Main Methods:

  • A wait-list quasi-experimental, type 2 hybrid study design was used.
  • 147 graduating nursing students were divided into experimental (AI-enabled VRS) and control groups.
  • Implementation outcomes were measured via survey questionnaires post-intervention.

Main Results:

  • The experimental group showed higher mean scores in recognizing/responding to clinical deterioration and interprofessional communication.
  • Participants reported positive perceptions of AI-enabled VRS's acceptability, adoption, appropriateness, and feasibility.
  • Areas for improvement included AI-human conversations, usability, and technical stability.

Conclusions:

  • AI-enabled VRS demonstrates potential in improving nursing students' clinical knowledge and preparedness.
  • Further strategies, including integrating generative AI, are needed to optimize learning and acceptance.
  • The study highlights the need for refinement to maximize the benefits of AI-enabled VRS in nursing education.