Advances in simulation (London, England)最新文献

Background: The rise in virtual reality (VR) applications in healthcare has introduced immersive VR simulations as a valuable training tool for medical professionals. Despite its advantages, VR use can induce cybersickness, characterized by symptoms such as nausea and disorientation. This study examines the relationship between cybersickness and the degree of physical movement in VR simulations used for psychiatric education.

Methods: The study involved two VR simulations offered at a Canadian mental health hospital: an opioid overdose response (OO) (high movement VR) and suicide risk assessment (SRA) (low movement VR). Participants' experiences were measured using the Simulator Sickness Questionnaire (SSQ) before and after the training sessions. A nonparametric Mann-Whitney U-test was conducted to compare SSQ scores between the two VR simulations.

Results: A total of 91 participants, including healthcare practitioners and students, were involved. The mean SSQ score for the OO training was 4.59/48 (SD = 5.78), while for the SRA, it was 3.10/48 (SD = 3.48). Mann-Whitney U-test revealed a significant increase in nausea scores in OO simulation compared to SRA simulation (p = 0.0275), with higher nausea reported in the OO simulation. No significant increases were found in oculomotor symptoms.

Conclusions: Participants in the OO training experienced higher levels of nausea compared to those in the SRA simulation, likely due to increased need for physical movement. These findings underscore the importance of considering the degree of physical movement in the VR training design, specifically the educational value of these movements and the risk of cybersickness negatively impacting VR tolerability for learners.

In response to Cheng et al.'s article on ethical recommendations for artificial intelligence (AI)-assisted academic writing, we propose an expanded ethical discourse to address the evolving role of AI in scholarly communication. While applauding the authors' foundational framework, we argue for greater disciplinary specificity, clearer thresholds for AI contribution, and broader consideration of systemic risks including linguistic bias, environmental impact, and corporate concentration. We advocate for the development of a graded typology of AI involvement, institution-led regulatory mechanisms, and integration of ethical AI use into editorial and research training practices. These enhancements are essential for building equitable, transparent, and sustainable AI governance in academic publishing.

Background: Research shows that simulation-based training can increase knowledge and skills among pregraduate healthcare students, that simulation-based training of technical skills places the participants higher on the learning curve in practice, and that simulation-based training can improve participants' social and cognitive skills. Nevertheless, how cognitive and social knowledge and skills are transferred into clinical practice competency remains unknown. This study aims to explore qualified in-hospital health professionals transfer of social and cognitive skills from a simulation-based training course to competency in everyday clinical practice.

Method: A qualitativeResearch shows that simulation-based training can increase phenomenological-hermeneutic methodology and an ethnographic study investigate qualified health professionals' social and cognitive skills transfer before, during, and after a simulation-based training course. The data collection comprises three phases: a clinical phase, a simulation-based training phase and a transfer phase; each phase is based on a subsequent analysis of the previous phase. Data consist of approximately 107 h of video recordings, field notes and reflections within the research team. Data are analysed with RICEA, a qualitative hybrid method of a Ricɶur-Inspired Analysis and Cognitive Event Analysis.

Findings: The analysis reveals three key themes: individual transfer of learning, intercollegiate transfer of learning and organisational transfer of learning. The findings imply that transfer of social and cognitive skills happens on an individual and intercollegiate level. Still, transfer needs to be scaffolded on an organisational level so that cognitive and social knowledge becomes competency in clinical practice. Further, the findings imply that transferring social and cognitive skills needs a different focus from transferring technical skills. Transfer, internalisation and retention of social and cognitive skills are inadequate because of insufficient organisational focus on transferring social and cognitive skills.

Conclusion: Findings suggest a need for a broader and more profound focus on transferring social and cognitive skills to competency in clinical practice. Involving local ambassadors and increased collaboration between simulation centres and organisations around the transfer phase could optimise social and cognitive skills transfer. However, further research is needed in this area.

Trial registration: N/A.

Healthcare simulation scenario design remains a resource-intensive process, demanding significant time and expertise from educators. This article presents an innovative AI-driven agentic workflow for healthcare simulation scenario development, bridging technical capability with pedagogical effectiveness. The system evolved from an initial ChatGPT-based prototype to a sophisticated platform implementation utilizing multiple specialized AI agents. Each agent addresses specific sub-tasks, including objective formulation, patient narrative generation, diagnostic data creation, and debriefing point development. The workflow employs advanced AI methodologies including decomposition, prompt chaining, parallelization, retrieval-augmented generation, and iterative refinement, all orchestrated through a user-friendly conversational interface. Critical to implementation was the demonstration that healthcare professionals with modest technical skills could develop these complex workflows without specialized AI expertise. The system ensures consistent adherence to established simulation guidelines, including INACSL Standards of Best Practice and ASPiH Standards Framework, while significantly reducing scenario development time by approximately 70-80%. Designed for broad applicability across diverse clinical settings and learner levels, the workflow incorporates multilingual capabilities for global application. Potential pitfalls include the necessity for rigorous review of AI-generated content and awareness of bias in model outputs. Key lessons learned emphasize interdisciplinary collaboration, systematic prompt refinement, essential human oversight, and the democratization of AI tools in healthcare education. This innovation demonstrates how sophisticated agentic AI implementations can transform healthcare simulation through enhanced efficiency, consistency, and accessibility without sacrificing pedagogical integrity.

Background: Nursing trained faculty often work as embedded simulated participants (ESPs) in interprofessional simulations. Blending and switching their professional identities as educators, nurses, and role players in ESP roles can be challenging. How they balance tensions in their role portrayal is poorly understood. New and experienced faculty may benefit from clearer guidance about how to approach this task.

Methods: Using a descriptive phenomenological approach, we explored the experience of nurses working as ESPs in a medical student simulation-based education program. We were sensitised by Dace's "blended boundaries" model of professional identity for simulation educators. We performed 9 semi-structured interviews with nurses who work as ESPs in our simulation program and undertook a thematic analysis of the transcribed data employing Braun and Clarke's (2006) six phase approach.

Results: We identified five themes: (1) role complexity, (2) influences and tensions in role portrayal, (3) judgement and flexibility, (4) perceived interprofessional outcomes, and (5) personal and professional impacts.

Discussion: Role portrayal of ESP nurses, by nurses, in interprofessional simulations is a complex and nuanced task. Carefully planned and reflected upon role portrayal offers powerful opportunities for medical students to gain a deeper understanding of interprofessional healthcare teamwork and the unique role of nurses in those teams. Thoughtful role portrayal supports highly authentic scenario delivery and clinical learning outcomes and can have positive professional impacts for the nurses undertaking this role. We suggest simulation programs should be highly intentional when recruiting, training, and supporting nurses to work as faculty in interprofessional simulations.

Background: In light of growing environmental concerns, this article examines the often-overlooked environmental impact of simulation-based education (SBE) within healthcare. We position simulation professionals as agents for environmentally sustainable change and seek to empower achievable, meaningful, measurable action. As a high-value yet resource-intensive pedagogical tool, SBE frequently relies on energy-intensive technologies and single-use materials that contribute to carbon emissions and waste. This article explores the environmental impact of SBE, detailing how it contributes to the healthcare sector's impact on the triple planetary crisis; climate change, pollution, and biodiversity loss.

Main messages: Within the simulation community, we have observed a high level of motivation to respond to the triple planetary crisis and make sustainable change. However, there is limited information available to simulation educators about practical changes that can be made. We have responded with an article that can help move from rhetoric to action, from inertia to empowerment. Understanding the environmental impact of simulation activities provides a useful starting point. We explain how to estimate a carbon footprint for SBE and how this relates to its wider environmental impact. Recognising the urgent need for change, we then present a comprehensive toolkit of practical strategies that can improve the environmental impact of SBE. Part one of our toolkit focuses on resource management, waste reduction and efficient session delivery. In part two, we highlight how principles of sustainable healthcare can be incorporated into scenario design and local strategy. This more holistic approach shows how SBE can be leveraged beyond immediate educational goals to foster sustainable practice in healthcare. We present evidence for our toolkit, detailing the principles and frameworks on which the suggestions are based. Additionally, we discuss how change can be measured and what risks educators should be aware of.

Conclusion: By embedding sustainability into SBE, educators can not only mitigate their own environmental impact but also model sustainable healthcare practices for learners. Through these steps, the simulation community can play a pivotal role in addressing healthcare's environmental impact and contribute to a healthier planet.

Background: Simulation-based medical education (SBME) is a critical training tool in healthcare, shaping learners' skills, professional identities, and inclusivity. Leadership demographics in SBME, including age, gender, race/ethnicity, and medical specialties, influence program design and learner outcomes. Artificial intelligence (AI) platforms increasingly generate demographic data, but their biases may perpetuate inequities in representation. This study evaluated the demographic profiles of simulation instructors and heads of simulation labs generated by three AI platforms-ChatGPT, Gemini, and Claude-across nine global locations.

Methods: A global cross-sectional study was conducted over 5 days (November 2024). Standardized English prompts were used to generate demographic profiles of simulation instructors and heads of simulation labs from ChatGPT, Gemini, and Claude. Outputs included age, gender, race/ethnicity, and medical specialty data for 2014 instructors and 1880 lab heads. Statistical analyses included ANOVA for continuous variables and chi-square tests for categorical data, with Bonferroni corrections for multiple comparisons: P significant < 0.05.

Results: Significant demographic differences were observed among AI platforms. Claude profiles depicted older heads of simulation labs (mean: 57 years) compared to instructors (mean: 41 years), while ChatGPT and Gemini showed smaller age gaps. Gender representation varied, with ChatGPT and Gemini generating balanced profiles, while Claude showed a male predominance (63.5%) among lab heads. ChatGPT and Gemini outputs reflected greater racial diversity, with up to 24.4% Black and 20.6% Hispanic/Latin representation, while Claude predominantly featured White profiles (47.8%). Specialty preferences also differed, with Claude favoring anesthesiology and surgery, whereas ChatGPT and Gemini offered broader interdisciplinary representation.

Conclusions: AI-generated demographic profiles of SBME leadership reveal biases that may reinforce inequities in healthcare education. ChatGPT and Gemini demonstrated broader diversity in age, gender, and race, while Claude skewed towards older, White, and male profiles, particularly for leadership roles. Addressing these biases through ethical AI development, enhanced AI literacy, and promoting diverse leadership in SBME are essential to fostering equitable and inclusive training environments.

Trial registration: Not applicable. This study exclusively used AI-generated synthetic data.

Background: Healthcare students are taught teamwork and collaboration through interprofessional simulation-based education (IPSE). However, the complex nature of healthcare and the ability to react resiliently to the unexpected is usually not actively addressed. This study explores how complexity and resilience can be addressed in IPSE debriefing for pre-graduate healthcare students.

Methods: A focus group of nine facilitators in an IPSE course for nursing and medical students was introduced to the characteristics of complex systems, Safety-II, solution-focused approach, and appreciative inquiry. In five iterations, the facilitators discussed how these theories and methods could be applied, tested, evaluated, and adjusted in debriefings supported by video clips of their own debriefings. Video recordings of debriefings (n = 56) and focus group interviews (n = 6) were collected. Focus group interviews were transcribed and reviewed to explore the basis for final recommendations.

Results: Facilitators identified and tested 22 debriefing techniques that potentially could address complexity and resilience in IPSE. In total, 17 of the tested techniques were found to be able to make students aware of the complex nature of interprofessional teamwork and collaboration in acute dynamic healthcare situations, their existing capacities for resilience, potentially increasing their capacity for resilience.

Conclusions: Learning needs around resilience and complexity could be addressed successfully in IPSE debriefings, but further studies are needed to assess the effect of resilience-focused debriefing techniques on teamwork in IPSE.

Background: Given the increasing complexity of contemporary clinical practice, there has never been a more important time to provide interprofessional educational (IPE) activities across the learning continuum to develop collaborative practice. From the outset of health professional training, it is crucial that students not only develop their own professional skills but also gain an awareness of the capabilities of other healthcare professionals and how best to work collaboratively. Despite simulation being a common teaching modality in many undergraduate curricula, little is known about the range of interprofessional activities within these settings. Therefore, this study aims to address the following research question: What is known about undergraduate in-person (IP) simulation-based education (SBE)?

Methods: We conducted a scoping literature review, adhering to the PRISMA-ScR extension guidelines, and used the Arksey and O'Malley framework. Our search covered three electronic databases: Web of Science (WOS), MEDLINE, and Embase. We utilised Covidence systematic review software to assist in screening articles. To support data charting, we developed a data extraction tool and employed both qualitative and quantitative techniques through numerical and thematic analysis to ensure a comprehensive representation of our data.

Results: A total of 97 studies were included, with most publications originating from the USA, UK, and Australia. Two main themes emerged regarding the impact of IP SBE at an individual level: confidence and role identification. Several themes related to the impact on teams included knowledge of other professional roles/values, communication, and teamwork. The studies identified various barriers and enablers to simulation, particularly logistical barriers and financial challenges associated with complex technologically enabled simulation. Faculty collaboration and resources were reported as primary enablers in facilitating the delivery of simulation activities.

Conclusions: The impact of IP-SBE on learners and interprofessional teams is predominantly positive, with reported benefits including increased confidence, enhanced role identification, and improved communication and teamwork skills. However, challenges such as logistical barriers and resource constraints highlight the need for collaborative faculty efforts and adequate infrastructure to support IP-SBE implementation. Despite the growing interest in IP-SBE, there remains a notable lack of standardised reporting on simulation design and debriefing processes in both teaching practice and research.

The increase in adoption of Electronic Health records (EHR) in healthcare can be overwhelming to users and pose hidden safety threats and inefficiencies if the system is not well aligned with workflows. This quality improvement study, facilitated from September 2023-April 2024, aimed to proactively test a new EHR using systems focused simulation and Human factors methods, prior to go-live, in a peri-operative children's hospital setting to improve safety, efficiency and usability of the EHR. The project was conducted at a large, academic, quaternary care children's hospital undergoing a transition from one EHR to another. Two cycles of usability testing followed by in situ simulations focused on testing the new EHR with interprofessional peri-operative team members prior to go live. Usability testing, using relevant clinical workflows, was completed over zoom using the EHR "testing" environment with individual care providers across multiple peri-operative roles. In situ simulations were facilitated in the actual peri-operative and Otolaryngology clinic spaces with full interprofessional teams. Qualitative data was collected and summarized through debriefing and recordings of the sessions. Human factors and patient safety principles were integrated throughout the recommendations. A total of 475 recommendations were made to improve the safety, efficiency, usability, and optimization of the EHR. The outcomes included a range of usability and system issues including latent safety threats and their impact on safe and quality patient care. There was a plethora of usability improvements, including some critical issues that were uncovered and mitigated prior to the go live date.