The effect of high-fidelity simulation on nursing students' self-confidence and stress levels during patient intervention: A randomized controlled trial

Abstract

Background High-fidelity simulation provides a safe and effective learning environment in nursing education, supporting the development of clinical competence and patient safety. This randomized controlled trial aimed to examine the effect of high-fidelity simulation on nursing students’ self-confidence and perceived stress levels during patient care interventions. Methods The study included 38 senior nursing students who completed a pretest consisting of the Student Identification Form, the Self-Confidence in Intervening with Patients Scale, and the Perceived Stress Scale. The experimental group participated in a simulated shock scenario using high-fidelity simulation, while the control group received routine theoretical instruction. Posttests were administered to both groups two weeks after the intervention. The data obtained in the study were statistically analyzed using SPSS (Statistical Package for the Social Sciences) version 25.0 for Windows. The study adhered to the CONSORT 2010 guidelines. Results No statistically significant differences were found between the experimental and control groups in posttest total scores of self-confidence or perceived stress (p>0.05). However, within-group analysis indicated significant improvements in the experimental group’s self-confidence total score and in the subdimensions of clinical practice and psychological support (p<0.05). These improvements demonstrate that students’ clinical performance during patient care interventions is supported. Conclusion High-fidelity simulation training significantly enhanced nursing students’ self-confidence during patient care interventions, whereas perceived stress levels did not differ significantly within or between groups. These findings support the integration of high-fidelity simulation into nursing curricula to enhance students’ clinical preparedness. Further studies with larger and diverse samples are recommended to strengthen the evidence base.