Clinical Simulation in Nursing最新文献_第4页

Improving baccalaureate nursing students’ cultural sensitivity with LGBTQIA+ patients using theater students as standardized patients 以戏剧专业学生为标准化患者，提高本科护生对LGBTQIA+患者的文化敏感性

IF 2.5 3区医学

Clinical Simulation in Nursing Pub Date : 2025-09-09 DOI: 10.1016/j.ecns.2025.101804

Virginia Oates DNP, RN , Daniel McWeeney DNP, FNP-C, RN , Mary T. Hickey Ed.D., WHNP-BC, FNP-BC, RN

引用次数: 0

Conversational AI in tactical combat casualty care: Baseline GPT-4o improves medic decision-making 战术战斗伤亡护理中的会话AI：基线gpt - 40改善医疗决策

IF 2.5 3区医学

Clinical Simulation in Nursing Pub Date : 2025-09-08 DOI: 10.1016/j.ecns.2025.101803

Jan Páleník MD , Michal Soták PhD , Martin Černý MD , Martin Komarc PhD , Norbert Svoboda PhD , Daor Hayu , Tomáš Tyll PhD , David Netuka PhD , Václav Masopust PhD , Karel Roubík PhD , Martin Májovský PhD

{"title":"Conversational AI in tactical combat casualty care: Baseline GPT-4o improves medic decision-making","authors":"Jan Páleník MD , Michal Soták PhD , Martin Černý MD , Martin Komarc PhD , Norbert Svoboda PhD , Daor Hayu , Tomáš Tyll PhD , David Netuka PhD , Václav Masopust PhD , Karel Roubík PhD , Martin Májovský PhD","doi":"10.1016/j.ecns.2025.101803","DOIUrl":"10.1016/j.ecns.2025.101803","url":null,"abstract":"<div><h3>Background</h3><div>Mechanical ventilation is vital in Tactical Combat Casualty Care (TCCC), yet many combat medics lack sufficient training in ventilator management. Although artificial intelligence (AI) shows promise in emergency medicine, its use in combat scenarios remains largely unexplored. This study evaluated AI-assisted ventilator management under simulated battlefield conditions.</div></div><div><h3>Methods</h3><div>This prospective, simulation-based observational study using a within-subject design was conducted in February 2025 in the Czech Republic with 42 Czech Armed Forces combat medics from four units. Participants adjusted ventilator settings (Vt, RR, FiO₂, PEEP, I:E) across ten scenarios, five with GPT-4o AI assistance and five without. The AI was customized to TCCC protocols and Joint Trauma System guidelines. Performance was scored objectively and analyzed using two-way repeated-measures ANOVA.</div></div><div><h3>Results</h3><div>AI assistance significantly improved parameter accuracy (<em>p</em> < 0.001), with an overall performance increase of 79.7%. The greatest gains were observed in Vt selection (164.2%), followed by FiO₂ (105.9%) and PEEP (60.6%), while I:E ratio adjustments showed marginal improvement (19%). Less experienced and female medics benefited most. Notably, AI-generated recommendations outperformed AI-assisted human decisions.</div></div><div><h3>Conclusions</h3><div>AI-enhanced support significantly improved ventilator management in combat simulations, suggesting potential to optimize real-time decision-making in austere environments. However, this system is not ready for operational deployment, and results should be interpreted as exploratory pending further field validation. Human oversight and medic accountability remain essential.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"107 ","pages":"Article 101803"},"PeriodicalIF":2.5,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010683","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}

引用次数: 0

Exploring extended immersive simulation-based education to prepare undergraduate nursing students for professional practice: A scoping review 探索扩展沉浸式模拟教育为护理本科学生的专业实践做准备：范围综述

IF 2.5 3区医学

Clinical Simulation in Nursing Pub Date : 2025-09-04 DOI: 10.1016/j.ecns.2025.101799

Caitlin Morse , Lin Zhao , Karen Livesay

{"title":"Exploring extended immersive simulation-based education to prepare undergraduate nursing students for professional practice: A scoping review","authors":"Caitlin Morse , Lin Zhao , Karen Livesay","doi":"10.1016/j.ecns.2025.101799","DOIUrl":"10.1016/j.ecns.2025.101799","url":null,"abstract":"<div><h3>Background</h3><div>Extended immersive simulation (EIS), a subset of simulation-based education (SBE), provides prolonged simulation experiences that replicate real-world professional practice. While extensive research exists on SBE, no scoping reviews have mapped EIS-based education's impact on undergraduate nursing education.</div></div><div><h3>Aim</h3><div>To investigate the literature on EIS related to undergraduates' learning experiences and engagement. It evaluates teaching modalities and learner-centred approaches in EIS, exploring their impact on student engagement and learning outcomes.</div></div><div><h3>Method</h3><div>Following the Joanna Briggs Institute framework, this review analysed 684 publications from PubMed and ProQuest (2012-2024). Two authors independently screened titles, abstracts, and full texts, using detailed analysis and thematic categorisation.</div></div><div><h3>Results</h3><div>Fifteen papers met the criteria. Thematic analysis revealed three themes: Student-Centred Learning Approaches, Structure of EIS, and Simulation Outcomes in nursing programs.</div></div><div><h3>Conclusion</h3><div>EIS and student-centred approaches improve nursing students' learning and readiness. Despite limited literature, EIS boosts engagement and prepares students in a controlled environment. More research is needed on student support, facilitator training, and academic guidance. Combining EIS with traditional methods is recommended for optimal development.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"107 ","pages":"Article 101799"},"PeriodicalIF":2.5,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989288","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}

引用次数: 0

Utilization of metaverse environment for education among nursing students based on personality traits and digital literacy 基于人格特质与数位素养的护生元环境教育运用

IF 2.5 3区医学

Clinical Simulation in Nursing Pub Date : 2025-09-02 DOI: 10.1016/j.ecns.2025.101801

Hyeongsuk Lee PhD, RN , Hye Jin Yoo PhD, RN , Hyeongju Ryu PhD, RN

{"title":"Utilization of metaverse environment for education among nursing students based on personality traits and digital literacy","authors":"Hyeongsuk Lee PhD, RN , Hye Jin Yoo PhD, RN , Hyeongju Ryu PhD, RN","doi":"10.1016/j.ecns.2025.101801","DOIUrl":"10.1016/j.ecns.2025.101801","url":null,"abstract":"<div><h3>Background</h3><div>The metaverse, a virtual reality space that enables real-time interaction, is increasingly being integrated into education, as traditional classrooms often fail to meet the diverse student needs. This study examined nursing students’ satisfaction, self-efficacy, and learning experiences within a metaverse-based collaborative learning environment, focusing on the influence of personality traits and digital literacy.</div></div><div><h3>Methods</h3><div>A quasi-experimental, one-group post-test design was employed with 40 nursing students. Additionally, 15 students participated in focus group interviews (FGI). The relationships between personality traits, digital literacy, and metaverse satisfaction were analyzed using t-tests, chi-square tests, and Pearson’s correlation coefficients. Interview data were examined using content analysis.</div></div><div><h3>Results</h3><div>Digital literacy was positively correlated with self-efficacy and course satisfaction. Introverted students reported reduced presentation anxiety, whereas extroverted students exhibited lower platform satisfaction. The interviews identified usability issues and emphasized the need for structured guidance for students with high neuroticism.</div></div><div><h3>Conclusion</h3><div>While, the metaverse can support diverse learning needs, careful integration is essential to address usability concerns and to provide structured guidance tailored for certain students.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"107 ","pages":"Article 101801"},"PeriodicalIF":2.5,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926562","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}

引用次数: 0

“It felt real”: Nursing students’ experiences of mental health simulation utilizing service users as standardized patients “感觉真实”：护生以服务使用者为标准化病人的心理健康模拟体验

IF 2.5 3区医学

Clinical Simulation in Nursing Pub Date : 2025-08-30 DOI: 10.1016/j.ecns.2025.101794

Jiyoung Kim PMH-APN, PhD , Suyoun Ahn RN, PhD , Jaewon Joung PMH-APN, PhD

{"title":"“It felt real”: Nursing students’ experiences of mental health simulation utilizing service users as standardized patients","authors":"Jiyoung Kim PMH-APN, PhD , Suyoun Ahn RN, PhD , Jaewon Joung PMH-APN, PhD","doi":"10.1016/j.ecns.2025.101794","DOIUrl":"10.1016/j.ecns.2025.101794","url":null,"abstract":"<div><h3>Background</h3><div>Involving service users as standardized patients in mental health simulation enhances the authenticity of learning and fosters recovery-oriented, person-centered nursing values. This study explored nursing students’ experiences of a simulation involving a person with lived experience of mental illness as a standardized patient.</div></div><div><h3>Methods</h3><div>A simulation scenario depicting a patient with schizophrenia who refused medication due to delusions and auditory hallucinations was implemented. A trained service user acted as a standardized patient. Eighty-nine fourth-year nursing students participated and submitted written reflections. Data were analyzed using inductive content analysis.</div></div><div><h3>Results</h3><div>Three main themes emerged: (a) learning effectiveness enhanced by realistic situations, (b) challenges arising from unfamiliar and innovative instructional approaches, and (c) growing a caring attitude. Reflections revealed increased empathy toward individuals with mental illness, strengthening students’ commitment to compassionate care.</div></div><div><h3>Conclusion</h3><div>Involving service users as standardized patients in mental health simulations can bridge the gap between theoretical learning and real-world practice, enriching mental health nursing education.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"107 ","pages":"Article 101794"},"PeriodicalIF":2.5,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144917920","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}

引用次数: 0

Barriers to breakthroughs: A scoping review of generative AI in healthcare simulation 突破的障碍：医疗保健模拟中生成人工智能的范围审查

IF 2.5 3区医学

Clinical Simulation in Nursing Pub Date : 2025-08-28 DOI: 10.1016/j.ecns.2025.101791

Erika Janssen PhD, MSN, RN , Rebecca McLagan MS. Ed , Jessica Habeck DNP , Seon Yoon Chung PhD., RN, CHSE , Erin C. McArthur MLIS , Polly Anderson MSN

{"title":"Barriers to breakthroughs: A scoping review of generative AI in healthcare simulation","authors":"Erika Janssen PhD, MSN, RN , Rebecca McLagan MS. Ed , Jessica Habeck DNP , Seon Yoon Chung PhD., RN, CHSE , Erin C. McArthur MLIS , Polly Anderson MSN","doi":"10.1016/j.ecns.2025.101791","DOIUrl":"10.1016/j.ecns.2025.101791","url":null,"abstract":"<div><h3>Background</h3><div>Generative artificial intelligence (AI) is an emerging technology in healthcare education with potential to enhance simulation by addressing logistical barriers and by providing increased access to diverse settings in healthcare education, leading to improved learning outcomes. This rapid scoping review explores the use of generative AI in simulation-based education.</div></div><div><h3>Methods</h3><div>Searches were conducted in CINAHL, Medline, PsycINFO, ScienceDirect, and Web of Science using terms such as “generative artificial intelligence” and “healthcare simulation.” The review followed the World Health Organization (WHO) Rapid Review Guide and was structured using Arksey and O'Malley's five-stage framework for scoping reviews.</div></div><div><h3>Results</h3><div>After applying inclusion and exclusion criteria, 15 articles were included. Five themes emerged: (1) removal of logistical barriers, (2) authentic practice, (3) distinctive value, (4) limitations of generative AI, and (5) potential with human oversight. Generative AI improves access to simulation by creating cost-effective, scalable, and realistic scenarios while fostering critical thinking through reflective learning. However, challenges such as misinformation and ethical concerns remain.</div></div><div><h3>Conclusions</h3><div>This scoping review identified growing momentum around generative AI's role in healthcare simulation. While early studies highlight its potential to support scalable, adaptive, and authentic training experiences, effective integration requires strong governance, ethical safeguards, and human oversight.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"107 ","pages":"Article 101791"},"PeriodicalIF":2.5,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144908805","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}

引用次数: 0

Strategies to incorporate generative artificial intelligence in simulation-based education among undergraduate students of healthcare professions: A scoping review 将生成人工智能纳入医疗保健专业本科生模拟教育的策略：范围审查

IF 2.5 3区医学

Clinical Simulation in Nursing Pub Date : 2025-08-25 DOI: 10.1016/j.ecns.2025.101795

Jackie Hoi Man Chan , Ken Hok Man Ho , Jacqueline Maria Dias

{"title":"Strategies to incorporate generative artificial intelligence in simulation-based education among undergraduate students of healthcare professions: A scoping review","authors":"Jackie Hoi Man Chan , Ken Hok Man Ho , Jacqueline Maria Dias","doi":"10.1016/j.ecns.2025.101795","DOIUrl":"10.1016/j.ecns.2025.101795","url":null,"abstract":"<div><h3>Background</h3><div>Complex prompting and unreadiness among faculty and students are some of the reported challenges when incorporating generative artificial intelligence (GenAI) into simulation-based education (SBE) in undergraduate healthcare programmes. However, strategies for incorporating GenAI into SBE are unclear. This scoping review identified current evidence on GenAI technology, its role, study outcomes, and strategies to incorporate GenAI into the SBE of undergraduate healthcare programmes.</div></div><div><h3>Methods</h3><div>The Joanna Briggs Institute methodology for scoping reviews was adopted. Eight electronic databases were searched from inception to January 21, 2025. Two authors independently screened and extracted data. The PAGER framework collated, critiqued, and reported the results.</div></div><div><h3>Results</h3><div>Eight studies were included. ChatGPT was the most frequently employed GenAI technology in SBE of undergraduate healthcare programmes, to enhance the students’ cognitive and affective learning. Study outcomes focused on usability. Five core strategies were synthesized: (a) establish guidelines on GenAI use; (b) enhance GenAI literacy; (c) enhance competency in GenAI prompting in simulation; (d) ensure pedagogical alignment; and (e) conduct pilot tests.</div></div><div><h3>Conclusions</h3><div>The findings provide insights into GenAI integration in SBE in undergraduate healthcare programmes. Further studies on the benefits of GenAI when applied to SBE are needed to demonstrate its impact on student learning.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"106 ","pages":"Article 101795"},"PeriodicalIF":2.5,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895885","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}

引用次数: 0

Scalpel-bougie surgical airway simulation workshop for nurse anesthesia students—Focused curriculum with structured assessment 面向护士麻醉学生的手术刀-布基手术气道模拟工作坊——以结构化评估为重点的课程

IF 2.5 3区医学

Clinical Simulation in Nursing Pub Date : 2025-08-25 DOI: 10.1016/j.ecns.2025.101800

Charles J. Lin MD, MSc , Emily Baldwin DNP, CRNA , Anna Breedlove DNP, CRNA , Joseph Goode PhD, CRNA , Paul W. Scott PhD , John M. O'Donnell DrPH, CRNA

引用次数: 0

Interprofessional simulation: Preparing health sciences students to navigate incivility 跨专业模拟：准备健康科学的学生导航不文明

IF 2.5 3区医学

Clinical Simulation in Nursing Pub Date : 2025-08-25 DOI: 10.1016/j.ecns.2025.101796

Danielle Yocom DNP, Nancy Barker Ed.D, Patrick Heagey MPAS, Alexa Moran BS, Katherine D. Pheysey MS

{"title":"Interprofessional simulation: Preparing health sciences students to navigate incivility","authors":"Danielle Yocom DNP, Nancy Barker Ed.D, Patrick Heagey MPAS, Alexa Moran BS, Katherine D. Pheysey MS","doi":"10.1016/j.ecns.2025.101796","DOIUrl":"10.1016/j.ecns.2025.101796","url":null,"abstract":"<div><div>Healthcare workers face uncivil behaviors from patients, families, and visitors that may impact their well-being. Students in the health sciences may be less likely to experience incivility in the clinical setting, making them less prepared to deal with these stressful situations until after graduation. A convenience sample of 54 students from respiratory therapy, nursing, and physician associate programs participated in the simulation. A simulation exposing health sciences students to uncivil behavior was designed and implemented based on International Nursing Association for Clinical Simulation and Learning (INASCL) standards. To determine student exposure to prior uncivil behavior, the Negative Acts Questionnaire-Revised (NAQ-R) was instituted before and after the simulation. Areas that showed an increase in awareness post-simulation focused on person-related and physically intimidating bullying. This study sought to introduce incivility in an interprofessional simulation to provide students with the opportunity to understand the definitions of incivility and strategies to help navigate such exposures in the future.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"106 ","pages":"Article 101796"},"PeriodicalIF":2.5,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895766","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}

引用次数: 0

Enhancing learning outcomes through AI-driven simulation in nursing education: A systematic review 通过人工智能驱动的模拟在护理教育中提高学习成果：系统综述

IF 2.5 3区医学

Clinical Simulation in Nursing Pub Date : 2025-08-22 DOI: 10.1016/j.ecns.2025.101797

Tuba Sengul RN, PhD, CWON, Seda Sarıköse RN, PhD

{"title":"Enhancing learning outcomes through AI-driven simulation in nursing education: A systematic review","authors":"Tuba Sengul RN, PhD, CWON, Seda Sarıköse RN, PhD","doi":"10.1016/j.ecns.2025.101797","DOIUrl":"10.1016/j.ecns.2025.101797","url":null,"abstract":"<div><h3>Background</h3><div>Artificial intelligence (AI) is increasingly integrated into simulation-based nursing education to enhance scalability, personalisation, and interactivity. This review systematically examined the impact of AI-driven simulations on learning outcomes in nursing education.</div></div><div><h3>Method</h3><div>This systematic review adhered to PRISMA guidelines and included empirical studies published between 2015 and 2025. A comprehensive search was conducted across six databases, and study quality was appraised using RoB 2, ROBINS-I, JBI, and MMAT tools. Methodological heterogeneity precluded meta-analysis; findings were instead synthesised through deductive categorisation to ensure a structured and critical integration.</div></div><div><h3>Results</h3><div>Sixteen studies met the inclusion criteria. AI-driven simulations were associated with improved communication, clinical reasoning, knowledge acquisition, self-efficacy, and empathy. Most studies reported high levels of learner satisfaction and engagement. However, limitations included challenges in interpreting nuanced emotional cues, limited cultural adaptability of AI systems, and technological constraints affecting responsiveness.</div></div><div><h3>Conclusions</h3><div>AI-driven simulation supports the development of diverse learning outcomes in nursing education. Further research is needed to explore long-term effects and optimise implementation strategies.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"106 ","pages":"Article 101797"},"PeriodicalIF":2.5,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144886973","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}

引用次数: 0