Suk Jeong Lee1, Sang Suk Kim1, Young-Mi Park2. 1. Red Cross College of Nursing, Chung-Ang University (CAU), CAU Healthcare System, Seoul, Korea. 2. Ansan College of Nursing, Ansan, Korea.
Abstract
AIM: This study was conducted to explore first experiences of high-fidelity simulation training in Korean nursing students, in order to develop and establish more effective guidelines for future simulation training in Korea. METHODS: Thirty-three junior nursing students participated in high-fidelity simulation training for the first time. Using both qualitative and quantitative methods, data were collected from reflective journals and questionnaires of simulation effectiveness after simulation training. Descriptive statistics were used to analyze simulation effectiveness and content analysis was performed with the reflective journal data. RESULTS: Five dimensions and 31 domains, both positive and negative experiences, emerged from qualitative analysis: (i) machine-human interaction in a safe environment; (ii) perceived learning capability; (iii) observational learning; (iv) reconciling practice with theory; and (v) follow-up debriefing effect. More than 70% of students scored high on increased ability to identify changes in the patient's condition, critical thinking, decision-making, effectiveness of peer observation, and debriefing in effectiveness of simulation. CONCLUSION: This study reported both positive and negative experiences of simulation. The results of this study could be used to set the level of task difficulty in simulation. Future simulation programs can be designed by reinforcing the positive experiences and modifying the negative results.
AIM: This study was conducted to explore first experiences of high-fidelity simulation training in Korean nursing students, in order to develop and establish more effective guidelines for future simulation training in Korea. METHODS: Thirty-three junior nursing students participated in high-fidelity simulation training for the first time. Using both qualitative and quantitative methods, data were collected from reflective journals and questionnaires of simulation effectiveness after simulation training. Descriptive statistics were used to analyze simulation effectiveness and content analysis was performed with the reflective journal data. RESULTS: Five dimensions and 31 domains, both positive and negative experiences, emerged from qualitative analysis: (i) machine-human interaction in a safe environment; (ii) perceived learning capability; (iii) observational learning; (iv) reconciling practice with theory; and (v) follow-up debriefing effect. More than 70% of students scored high on increased ability to identify changes in the patient's condition, critical thinking, decision-making, effectiveness of peer observation, and debriefing in effectiveness of simulation. CONCLUSION: This study reported both positive and negative experiences of simulation. The results of this study could be used to set the level of task difficulty in simulation. Future simulation programs can be designed by reinforcing the positive experiences and modifying the negative results.