Improving Pediatric/Neonatology Residents' Newborn Resuscitation Skills With a Digital Serious Game: DIANA.

Background: Serious games, and especially digital game based learning (DGBL) methodologies, have the potential to strengthen classic learning methodology in all medical procedures characterized by a flowchart (e.g., neonatal resuscitation algorithm). However, few studies have compared short- and long-term knowledge retention in DGBL methodologies with a control group undergoing specialist training led by experienced operators. In particular, resident doctors' learning still has limited representation in simulation-based education literature. Objective: A serious computer game DIANA ( Methods: Pediatric/neonatology residents of the Azienda Ospedaliera Universitaria Pisana (AOUP) were invited to take part in the study and were split into a game group or a control group; both groups were homogeneous in terms of previous training and baseline scores. The control group attended a classic 80 min teaching session with a neonatal trainer, while game group participants played four 20 min sessions over four different days. Three written tests (pre/immediately post-training and at 28 days) were used to evaluate and compare the two groups' performances. Results: Forty-eight pediatric/neonatology residents participated in the study. While classic training by a neonatal trainer demonstrated an excellent effectiveness in short/long-term knowledge retention, DGBL methodology proved to be equivalent or better. Furthermore, after each game session, DGBL score improved for both procedure knowledge and ventilation/chest compressions rate. Conclusions: In this study, DGBL was as effective as classic specialist training for neonatal resuscitation in terms of both algorithm memorization and knowledge retention. User appreciation for the methodology and ease of administration, including remotely, support the use of DGBL methodologies for pediatric/neonatology residents education.