Clinical Simulation in Nursing最新文献

{"title":"Interprofessional simulation co-debriefing practices: A systematic review","authors":"Elisabeth Jacob PhD, RN ,&nbsp;Tracy Parrish RN ,&nbsp;Clare Duffy BA, GCETE, GDIM ,&nbsp;Sara Geale PhD, RN ,&nbsp;Scott Stewart PhD ,&nbsp;Kylie Kendrick MPH","doi":"10.1016/j.ecns.2025.101816","DOIUrl":"10.1016/j.ecns.2025.101816","url":null,"abstract":"<div><div>Interprofessional simulation allows healthcare students to practice the role of a professional with students from other professions. Debriefing is essential to the simulation, promoting insight into actions taken and thought processes behind the actions. The impact of co-debrief with interprofessional teams remains in question. This paper aims to explore the impact of co-debriefing on student experiences. This systematic literature review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses checklist (PRISMA). Search terms including “inter-professional education,” “simulation,” “co-debriefing,” and “university students” were undertaken across seven databases. Twenty-seven papers with students from 17 professions were included. Simulations were considered effective, however the impact of co-debriefing on student outcomes was not explored in any studies. Debriefing is imperative to healthcare simulation, yet little evidence is available to support the role of co- debriefing. Further research is required to determine its effectiveness and appropriateness for all inter-professional simulations.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"108 ","pages":"Article 101816"},"PeriodicalIF":2.5,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generative artificial intelligence in healthcare simulation-based education: A scoping review","authors":"Nicholas Wee Siong Neo MSc, RN ,&nbsp;Joko Gunawan PhD, RN ,&nbsp;Tracy Levett-Jones MEd, PhD, RN ,&nbsp;Eng Tat Khoo PhD ,&nbsp;Wei Ling Chua PhD, RN ,&nbsp;Sok Ying Liaw PhD, RN","doi":"10.1016/j.ecns.2025.101819","DOIUrl":"10.1016/j.ecns.2025.101819","url":null,"abstract":"<div><h3>Aims</h3><div>This review aimed to explore the current state of generative artificial intelligence (GenAI) use in simulation-based healthcare education through a comprehensive examination of GenAI types, applications and reported outcomes.</div></div><div><h3>Methods</h3><div>A scoping review was conducted utilizing the Joanna Briggs Institute’s methodological guidance. Six databases were searched from their inception until February 2025.</div></div><div><h3>Results</h3><div>We included 28 articles that were published between 2023 and 2025. Articles were mainly in the fields of medicine (<em>n</em> = 14) and nursing (<em>n</em> = 10). OpenAI’s GPT models were most frequently used to portray simulated characters and deliver automated feedback. GenAI-enhanced simulation was generally perceived as accurate, realistic and feasible, with some evidence supporting its use as a supplement to conventional simulation and to enhance learning outcomes. Perspectives, ethical considerations and recommendations for GenAI-enhanced simulation were also highlighted.</div></div><div><h3>Conclusion</h3><div>GenAI-enhanced simulation is gaining popularity and is likely to evolve alongside human-facilitated simulation. Future developments should focus on building AI expertise among simulation educators and harnessing the synergy between human intelligence and GenAI. Further rigorous research is needed to establish best practices.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"108 ","pages":"Article 101819"},"PeriodicalIF":2.5,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulation in healthcare: Navigating the space between quality improvement and research","authors":"Anders L. Schram MPH","doi":"10.1016/j.ecns.2025.101824","DOIUrl":"10.1016/j.ecns.2025.101824","url":null,"abstract":"<div><div>Simulation-based initiatives are increasingly integrated into healthcare settings, often responding to local concerns while also producing insights that contribute to wider scholarly and professional debates. In this context, the distinction between quality improvement and research is often blurred, and many projects incorporate elements of both. This paper argues that instead of treating quality improvement and research as fixed categories, it is more productive to reflect on how simulation initiatives are positioned in relation to their intended contributions to practice and knowledge. Drawing on insights from implementation science, I outline recurring challenges that arise when this reflection is absent, including difficulties with ethics, contextual transparency, and accessibility of findings. To support a more deliberate approach, the paper introduces a reflective illustration that helps situate simulation work without reducing it to predefined labels, thereby enhancing both its local value and its broader relevance.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"108 ","pages":"Article 101824"},"PeriodicalIF":2.5,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictors of satisfaction and self-confidence in simulation learning among healthcare students in Vietnam","authors":"Tran Thi Ngoc Tho ,&nbsp;Tran Thi My ,&nbsp;Tran Cong Huyen Trang","doi":"10.1016/j.ecns.2025.101828","DOIUrl":"10.1016/j.ecns.2025.101828","url":null,"abstract":"<div><h3>Background</h3><div>Simulation-based learning is increasingly used in healthcare education to enhance students’ clinical competence, satisfaction, and self-confidence. While simulation has been widely adopted in Vietnam, evidence on its effectiveness and the factors influencing learner outcomes remains limited.</div></div><div><h3>Purpose</h3><div>This study aimed to assess the levels of satisfaction and self-confidence among healthcare students following simulation-based learning and to identify key predictors of these outcomes.</div></div><div><h3>Methods</h3><div>A cross-sectional study was conducted among 284 undergraduate healthcare students from various disciplines at a private university in Vietnam. Data were collected using the Student Satisfaction and Self-Confidence in Learning Scale and the Simulation Design Scale. Descriptive statistics, Mann-Whitney U, Kruskal-Wallis tests, and multiple linear regression were used to analyze the data.</div></div><div><h3>Results</h3><div>Participants reported high satisfaction (4.31 ± 0.77) and self-confidence (4.24 ± 0.67) scores. The Simulation Design Scale was the strongest predictor of both satisfaction (β = 0.823, <em>p</em> &lt; .001) and self-confidence (β = 0.819, <em>p</em> &lt; .001). Academic performance also significantly predicted satisfaction (β = 0.083, <em>p</em> = .013) and self-confidence (β = 0.096, <em>p</em> = .004). Additionally, students’ perception of the debriefing session significantly influenced satisfaction (β = 0.083, <em>p</em> = .017). The regression models explained 71.6% and 71.3% of the variance in satisfaction and self-confidence, respectively.</div></div><div><h3>Conclusion</h3><div>Simulation-based learning is an effective strategy for enhancing satisfaction and self-confidence among healthcare students. Simulation design quality, academic performance, and the debriefing experience are critical elements influencing student outcomes. These findings support the continued integration and refinement of simulation in health professions education in Vietnam.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"108 ","pages":"Article 101828"},"PeriodicalIF":2.5,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing empathy and understanding: Developing a virtual reality simulation to educate healthcare students on deaf patient experiences","authors":"J. Terry,&nbsp;J. Davies,&nbsp;R. Wilks,&nbsp;T. Thomas,&nbsp;S. Vowles,&nbsp;J. Hunt,&nbsp;D. Rowberry,&nbsp;M. Nosek,&nbsp;I. Humphreys","doi":"10.1016/j.ecns.2025.101825","DOIUrl":"10.1016/j.ecns.2025.101825","url":null,"abstract":"<div><h3>Background</h3><div>Deaf patients face challenges in healthcare settings, with limited deaf awareness in health professional programs, due to a lack of training. Healthcare professional students lack preparation about how to communicate effectively with deaf people and may not understand or empathize with their experiences in healthcare settings. The aim of the study was to co-design and develop a 360-degree VR simulation, informed by deaf patient experiences, to enhance health professional students’ empathy and understanding when working with deaf patients.</div></div><div><h3>Sample</h3><div>Study sample was comprised of a purposive sample of preregistration healthcare professional students (n = 8) enrolled in an undergraduate degree at one university in Wales, UK. Participants were recruited through email invitation to all students in one School of Health and Social Care.</div></div><div><h3>Methods</h3><div>A user-centered design approach was used across three phases: gathering feedback from deaf communities on healthcare experiences, design and development of an immersive 360-degree video VR, and evaluating it with health professional students (n = 8), through a pre/post survey and focus group. The survey was analyzed using descriptive statistics and the focus group transcript analyzed using thematic analysis.</div></div><div><h3>Results</h3><div>Positive feedback from participating students emphasized the benefits of the simulation and its engaging, impactful nature with a focus on lived experience.</div></div><div><h3>Conclusion</h3><div>Simulation education is an effective tool in preparing students for working with deaf patients and in enhancing empathy.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"108 ","pages":"Article 101825"},"PeriodicalIF":2.5,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a prompt template to support simulation design: Maximizing the potential of generative artificial intelligence","authors":"Elizabeth Robison EdD, MSN, RN, CNE, CHSE-A ,&nbsp;Theresa Cooney MSN, RN ,&nbsp;Tammy Schwaab DNP, RN, CHSE ,&nbsp;Sami Rahman MEd, MSN, RN","doi":"10.1016/j.ecns.2025.101822","DOIUrl":"10.1016/j.ecns.2025.101822","url":null,"abstract":"<div><h3>Background</h3><div>Generative AI tools like ChatGPT are rapidly changing academia and healthcare, particularly in nursing education through their ability to assist in creating clinical simulation scenarios. The key to effectively using these tools lies in prompt engineering, the careful crafting of inputs to guide AI outputs.</div></div><div><h3>Aim</h3><div>An initiative by nurse educators explored how prompt engineering, aligned with established simulation standards, could streamline scenario design.</div></div><div><h3>Findings</h3><div>The findings revealed variations in output quality and focus among different AI platforms (ChatGPT, CoPilot, Claude), highlighting the need for careful selection and human oversight to ensure accuracy and relevance in AI-generated simulation content.</div></div><div><h3>Conclusions</h3><div>This iterative process of prompt refinement holds significant promise for creating more engaging and effective learning experiences, but AI serves as a tool that augments, not replaces, the expertise of nursing simulationists.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"108 ","pages":"Article 101822"},"PeriodicalIF":2.5,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utilization, application and effectiveness of metaverse in simulation-based nursing education: A systematic review","authors":"Carley Jans RN, MTeach, PhD Candidate ,&nbsp;Cherie Lucas PhD, BPharm ,&nbsp;Tracy Levett-Jones RN, PhD","doi":"10.1016/j.ecns.2025.101807","DOIUrl":"10.1016/j.ecns.2025.101807","url":null,"abstract":"<div><h3>Background</h3><div>The Metaverse is an emerging technological innovation with potential applications for healthcare education.</div></div><div><h3>Aim</h3><div>The objective of this systematic review was to evaluate the utilization, application, and effectiveness of the Metaverse in simulation-based nursing education.</div></div><div><h3>Methods</h3><div>A comprehensive search was conducted across eight electronic databases, yielding 32 studies that met the inclusion criteria. The studies, conducted between 2016 and 2023, were predominantly quantitative, with some employing mixed methods and qualitative approaches.</div></div><div><h3>Findings</h3><div>The review identified two main themes: learning outcomes and learner experiences. Learning outcomes included knowledge acquisition, clinical skill development, self-efficacy, confidence, and motivation. Use of Metaverse components, particularly virtual reality (VR), generally improved knowledge and technical skill acquisition, especially in areas such as infection control and neonatal resuscitation. Gains in nontechnical skills, including problem-solving and critical thinking, were also observed. However, evidence on motivation and confidence was mixed, with some studies reporting significant improvements and others finding no difference compared to traditional teaching methods. Learner experiences encompassed satisfaction, presence and immersion, usability, acceptability, and anxiety reduction. Learner satisfaction was consistently high, with VR perceived as visually appealing, interactive, and conducive to engaging learning environments. VR also enhanced presence and immersion, creating realistic and interactive simulations. Usability was typically rated as good, though challenges such as cybersickness were noted. Overall, participants viewed Metaverse technologies positively for their ability to create immersive, enjoyable, and effective learning experiences.</div></div><div><h3>Conclusions</h3><div>This review highlights the potential of the Metaverse in nursing education, particularly for enhancing learning outcomes and learner experiences. However, the lack of studies on the full application of the Metaverse, including social connectedness, suggests the need for further research to explore its comprehensive role in simulation-based learning.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"108 ","pages":"Article 101807"},"PeriodicalIF":2.5,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness of chatbot iCAN on reporting of child and adolescent abuse and neglect among emergency nurses: A pilot study","authors":"Li-Cheng Kao RN, MSN ,&nbsp;Su-Fen Cheng RN, PhD ,&nbsp;Wei-Chuan Chang MPH ,&nbsp;Pei-Fang Lai MD, PhD ,&nbsp;Mei-Lin Hsieh RN, MSN","doi":"10.1016/j.ecns.2025.101827","DOIUrl":"10.1016/j.ecns.2025.101827","url":null,"abstract":"<div><h3>Background</h3><div>Child and adolescent abuse and neglect (CAN) can lead to long-term trauma. These experiences can also contribute to cycles of family violence. Emergency nurses frequently encounter suspected cases, making it essential to strengthen their recognition and reporting competencies. This study examined the effectiveness of chatbot-facilitated education in improving CAN-related knowledge, attitudes, and reporting intention.</div></div><div><h3>Methods</h3><div>A two-group repeated-measures design was used with 32 emergency nurses recruited through purposive sampling. Both groups received CAN education; the experimental group additionally interacted with a chatbot named iCAN. Assessments were conducted at pre-test, post-test (week 1), and follow-up test (week 4).</div></div><div><h3>Results</h3><div>The experimental group showed significantly greater improvement in CAN knowledge and reporting intention (<em>p</em> &lt; .001) compared to the control group. While reporting attitudes improved in the experimental group and declined in the control group, between-group differences were not statistically significant (<em>p</em> &gt; .05).</div></div><div><h3>Conclusions</h3><div>Chatbot-facilitated education significantly enhanced emergency nurses’ CAN knowledge and intention to report. Optimizing chatbot design may further support nurses in identifying and reporting suspected cases.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"108 ","pages":"Article 101827"},"PeriodicalIF":2.5,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generative AI in simulation-based SBIRT training: Enhancing content validity and educational impact","authors":"Nicole Kroll PhD, APRN, ANP-C, FNP-BC, PMHNP-BC ,&nbsp;Lauren Thai MEd, CHSOS ,&nbsp;Jinsil Hwaryoung Seo PhD ,&nbsp;Mihir Sunil Godbole ,&nbsp;Cindy Weston DNP, APRN, FNP-BC, CHSE, FNAP, FAANP, FAAN ,&nbsp;Elizabeth Wells-Beede PhD, RN, C-EFM, CHSE-A, CNE, ACUE, FSSH, FAAN","doi":"10.1016/j.ecns.2025.101811","DOIUrl":"10.1016/j.ecns.2025.101811","url":null,"abstract":"<div><div>Background: Traditional SBIRT (Screening, Brief Intervention, and Referral to Treatment) training is limited by subjective assessments and resource constraints. Integrating generative AI into simulation offers scalable, consistent, and objective learning for addressing substance use disorders. Method: A web-based AI-enabled SBIRT simulation using large language models was piloted with content experts to evaluate usability, content validity, and educational impact via mixed-methods feedback and survey analysis. Results: Most evaluators rated the simulation as highly relevant and natural, with enhanced consistency and accessibility. The platform was easy to use and improved therapeutic communication skills. Conclusion(s): Generative AI in SBIRT simulation increases training reliability, scalability, and learner engagement for healthcare providers.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"108 ","pages":"Article 101811"},"PeriodicalIF":2.5,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A global survey of distress in simulation: Definition, frequency, and description","authors":"Efrem Violato PhD ,&nbsp;Thomas Waring CHSOS ,&nbsp;Emilio Violato MSc ,&nbsp;Gulshat Kemelova MD, PhD","doi":"10.1016/j.ecns.2025.101818","DOIUrl":"10.1016/j.ecns.2025.101818","url":null,"abstract":"<div><h3>Background</h3><div>In healthcare, simulation-based education distress can impair cognitive performance and psychological well-being. However, its frequency and contributing factors remain underexplored.</div></div><div><h3>Methods</h3><div>To understand the frequency and occurrence of distress in simulation, a survey was distributed globally to simulationists, utilizing convenience and snowball sampling across global regions.</div></div><div><h3>Results</h3><div>The final sample included 143 participants from 27 countries. Distress was reported to occur occasionally (46.2%), with respondents witnessing a mean of 13.3 distress events during their career and 9.15 in their centre. A set of causes of distress was identified, distress was generally managed effectively, and no significant differences were found across accreditation status, years of experience, or global regions.</div></div><div><h3>Conclusion</h3><div>Distress occurs regularly, though is not a high-frequency event. Further systematic measurement can help to better understand the conditions and frequency of distress.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"108 ","pages":"Article 101818"},"PeriodicalIF":2.5,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}