Comparing the Effectiveness of Large Language Model-Based and Video-Based Refresher Education on Knowledge Retention After Simulation-Based Pediatric Cardiopulmonary Resuscitation Training: A Six-Month Follow-Up Study

This study aims to compare the effectiveness of large language model (LLM)-based refresher education and video-based refresher education for maintaining knowledge and performance after simulation-based Pediatric Advanced Life Support (PALS) training. Healthcare professionals will be randomly assigned to either an LLM-based refresher education group or a video-based refresher education group. After randomization, all participants will receive simulation-based PALS training. Three months after the initial training, participants will receive refresher education according to their assigned group. The LLM-based group will use a generative AI and virtual reality-based educational platform that allows interactive practice of pediatric emergency scenarios, while the video-based group will receive video-based refresher education. At six months after the initial training, knowledge retention, simulation-based PALS performance, and self-efficacy will be assessed. The primary objective is to compare simulation-based performance between the two groups at six months. Secondary outcomes include knowledge test scores, self-efficacy, and measures related to completion of the refresher education.

Inclusion Criteria: * Healthcare professionals at Samsung Medical Center * Healthcare professionals who have previously received BLS or cardiopulmonary resuscitation training * Individuals who voluntarily agree to participate in the study * Individuals who are able to complete follow-up assessments during the study period Exclusion Criteria: * Individuals who do not wish to participate in the study * Individuals who do not provide consent to participate in the study