Enhancing nursing students' self-reported self-efficacy and professional competence in basic life support: the role of virtual simulation prior to high-fidelity training

被引:0
|
作者
Brix, Lone Dragnes [1 ,2 ]
Skjodt-Jensen, Anne Mette [1 ]
Jensen, Thomas Holdgard [3 ]
Aarkrog, Vibe [3 ]
机构
[1] Horsens Reg Hosp, Dept Anaesthesiol, Horsens, Denmark
[2] Aarhus Univ, Dept Clin Med, Aarhus, Denmark
[3] Aarhus Univ, Danish Sch Educ, Aarhus, Denmark
关键词
virtual reality; simulation; nursing; education; basic life support; CARDIOPULMONARY-RESUSCITATION; KNOWLEDGE; CONFIDENCE; RETENTION; SKILLS;
D O I
10.1016/j.teln.2024.10.020
中图分类号
R47 [护理学];
学科分类号
1011 ;
摘要
Background: In-hospital cardiac arrests often result in poor outcomes. Effective basic life support (BLS) relies on the competence of responders, yet nursing students often lack these skills. This study aimed to assess the impact of virtual reality (VR) BLS simulation on nursing students' self-reported self-efficacy and professional competence. Methods: An intervention study using a convergent mixed-methods approach was conducted, using questionnaires, interviews, and observations. Third-year nursing students (fifth term) were invited to participate. Qualitative and quantitative data were analysed separately and then integrated. Results: Fifty-nine students were randomised: 30 to the VR group and 29 to the control group. Interviews were conducted with 10 VR group students and eight control group students. VR simulation enhanced self- reported self-efficacy and professional competence in high fidelity (HF) simulation. Three themes emerged from the interviews: perception of time, awareness of competences, and use of professional language. Overall, VR simulation had a positive impact on self-efficacy in general, particularly for BLS. Conclusion: VR simulation is an effective supplement to BLS training for nursing students, enhancing self- reported self-efficacy and professional competence before HF simulation. (c) 2024 Organization for Associate Degree Nursing. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:e236 / e243
页数:8
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