Learning Effects of Mechanical Ventilator/Tracheal Suctioning XR Simulators and Extracting Decision Making Criteria to Introduce a Novel Simulator

Abstract

Researchers have developed Simmar+ESTE-SIM, a XR simulator that can train the multitask of “endotracheal suctioning for a patient with a mechanical-ventilator’’ as part of support for Technology-dependent children in the community. In this study, we conducted a questionnaire after using the simulator with the aim of extracting the learning effects of the simulator and judgment indicators when introducing a new simulator, based on feedback from 4th grade university students and the faculty members. As a result, both groups tended to score low on the question of whether the content was appropriate for learning in the third year, but the scores were generally high, at 3.0 or higher. The training task “endotracheal suctioning for a patient with mechanical respirator” was slightly early in 3rd grade students, and the appropriate timing was shown to be for 4th grade students. Principal component analysis extracts two principal components: “Balance between learning content difficulty and motivation (Achievability)” and “Balance between learning time, cost, and learning effect (Feasibility)”. These two factors were thought to be the promoting and inhibiting factors when introducing a simulator. The future challenge is to popularize the simulator education program which is both achievable and feasible to improve the quality of care for children with home-ventilators and their families.