Objective: Every year, millions of newborns around the world need the help of health professionals to take their first breath. Healthcare professionals need to have comprehensive knowledge and skills of specified in the neonatal resuscitation algorithm to perform life-saving interventions quickly and accurately. However, since neonatal resuscitation is a rather complicated task, deviations from this algorithm are common. In this article, it is aimed to review the current evidence of simulation used to improve neonatal resuscitation training. Methods: This research is the systematic review design and is a qualitative research based on document analysis of the articles. The universe of the study consisted of 116 articles from 2015-2020, accessed from databases such as Medline Complete, Academic Search Complete, Academic Search Ultimate, CINAHL Complete, Directory of Open Access Journals, Google Scholar and Google Scholar. Nine articles that satisfy the criteria for inclusion in this study were evaluated within the scope of the study. Results: Eight of the nine studies included in the study were reported to be in use high reality simulations. In all studies, educational content ranging from theoretical lessons based on neonatal resuscitation guidance and simulated resuscitation training to scenario-based practices were reported. In simulations to evaluate skill performances Megacode scenario was used in five studies, simulator software in one study, and a standard evaluation form in three studies. Conclusion: In the current studies, despite the improvement in knowledge and skill performance immediately after neonatal resuscitation training, the protection of knowledge and skills in the long term is controversial. For this reason, it may be recommended to conduct refresher trainings for the protection of newborn resuscitation knowledge and skills of health care professionals.
Educational efficacy of high-fidelity simulation in neonatal resuscitation training: a systematic review and meta-analysis
