A quasi-experimental study comparing rapid cycle deliberate practice and end-of-scenario debriefing in undergraduate nursing simulation

Abstract

Background: Debriefing is widely regarded as the most critical component of simulation-based learning, as it promotes reflective thinking, clinical reasoning, and performance improvement. Traditional end-of-scenario debriefing remains the most commonly used approach. However, alternative strategies, such as Rapid-Cycle Deliberate Practice (RCDP), integrates feedback during the simulation to enhance skill acquisition through immediate correction and repeated practice. Although RCDP has demonstrated effectiveness in technical skill training, evidence comparing its impact with traditional debriefing on undergraduate nursing students' learning experiences remains limited. This study aimed to compare the effectiveness of RCDP and end-of-scenario debriefing in nursing simulation education. Methods: This quasi-experimental study was conducted with fourth-year nursing students (n = 39) in a clinical simulation center. Students completed oncology and diabetes scenarios using RCDP and end-of-scenario debriefing, with structured debriefing based on the Promoting Excellence and Reflective Learning in Simulation (PEARLS) framework. Data were collected using validated simulation evaluation scales and open-ended feedback. The data were analyzed using a paired-samples t-test. Results: Students' Debriefing Experience Scale scores were significantly higher for end-of-scenario debriefing than RCDP (p < .05). No significant differences were observed in satisfaction, self-confidence, or total Simulation Design Scale scores. RCDP was associated with higher perceived support but lower fidelity and increased stress levels. Conclusions: Both debriefing approaches produced comparable outcomes in terms of satisfaction and self-confidence. Although RCDP enhanced perceived support, it may reduce perceived scenario fidelity and increase stress levels. Therefore, the selection of a debriefing approach should consider the learning objectives and contextual requirements of the simulation environment. (c) 2026 International Nursing Association for Clinical Simulation and Learning. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.