Validation of the Intu-VR-Vention Program for Enhancing Medical Training Through Virtual Reality (VR) Storyboard Integration for Intubation

EasyChair Preprint no. 11816

Abstract

This study introduces a new approach to enhance intubation medical training by developing an immersive Virtual Reality (VR) storyboard. Focused on practicality, our research aims to enhance medical education by leveraging the impact of VR technology. The hypothesized benefits include heightened trainee engagement, improved procedural knowledge retention, and enhanced critical decision-making skills. The VR storyboard comprises ten scenes, each representing a key step in the intubation procedure, aligning with recent developments and incorporating real-life complexities.

Developed collaboratively with board-certified physicians, medical students, and software programmers, our methodology integrates practice-based guidelines and fosters interdisciplinary collaboration. The scenes, spanning from patient interaction to handover to the surgical team, create an authentic yet simulated learning environment. Preliminary results from comprehensive focus group assessments, combining quantitative metrics and qualitative insights, demonstrate positive impacts on trainee engagement, procedural knowledge retention, and critical decision-making skills.

In summary, this systematic and transformative approach to intubation training offers a tailored learning experience. The VR storyboard method holds promise for reshaping medical training beyond intubation education, marking a significant advancement in immersive educational technology.

Keyphrases: focus group, Intubation Training, medical education, medical simulation, Storyboard, Virtual Reality

@Booklet{EasyChair:11816,
  author = {Sophia Jensen and Mcguire Leiting and Bo-Dee Romero and Noah Wester and Henry J. Runge and Carl A. Nelson and Ka-Chun Siu},
  title = {Validation of the Intu-VR-Vention Program for Enhancing Medical Training Through Virtual Reality (VR) Storyboard Integration for Intubation},
  howpublished = {EasyChair Preprint no. 11816},

  year = {EasyChair, 2024}}