Effectiveness of simulation debriefing methods in nursing education: A systematic review and meta-analysis

Objective This systematic review and meta-analysis aimed to evaluate debriefing methods' effectiveness on learning outcomes for nursing students. Design A systematic review and meta-analysis were applied according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement. Data sources Publications were searched in PubMed, EMBASE, The Cochrane Library, Web of Science, China National Knowledge Infrastructure, and WANFANG (China) databases from inception to 2020. Review methods Two researchers independently retrieved articles and evaluated their quality. Review Manager version 5.3 software was used to conduct the meta-analysis, following the PRISMA guidelines. Bias risk was assessed using the Joanna Briggs Institute manual. Heterogeneity was assessed by I2 statistics. Standardized mean difference (SMD) and 95% confidence intervals (CIs) were used for effect size analysis based on learning outcomes. Results Sixteen studies were selected in the systematic review and 13 studies with 1637 nursing students were included in the meta-analysis. Five debriefing methods were used in the intervention group. The analysis showed that Debriefing for Meaningful Learning was more effective on the debriefing quality (SMD = 0.52, 95%CI [0.32, 0.72]), and that video-assisted debriefing was more effective on nursing students' experiences (SMD = 0.30, 95%CI [0.02, 0.58]) and critical thinking (SMD = 0.90, 95%CI [0.65, 1.15]) compared with the usual debriefing. However, written debriefing did not show better effects on students' experiences (SMD = −0.22, 95%CI [−0.51, 0.07]), and peer-led debriefing did not show better effects on the debriefing quality compared with the usual debriefing (SMD = −0.15, 95%CI [−1.43, −0.67]). Conclusions The study indicated that Debriefing for Meaningful Learning and video-assisted debriefing showed a positive impact on nursing education. Future studies that have larger sample sizes, high-quality debriefing methods, robust study designs, and other learning outcomes are required.