Advances in simulation (London, England)最新文献

Simulation-based education (SBE) has become an integral part of training in health professions education, offering a safe environment for learners to acquire and refine clinical skills. As a non-ionising imaging modality, ultrasound is a domain of health professions education that is particularly supported by SBE. Central to many simulation programs is the use of animal models, tissues, or body parts to replicate human anatomy and physiology. However, along with its educational benefits, the use of animals in SBE generates a considerable amount of waste, raising important environmental and ethical concerns. Although research indicates that animal models yield comparable educational outcomes to synthetic models, animal models continue to be preferred in surgical and medical training. In response to these challenges, the principles of Replacement, Reduction, and Refinement (the 3Rs) have emerged as guiding standards to minimise the impact of animal use in research and education. Furthermore, synthetic models align with 3R principles, addressing ethical and environmental issues by reducing animal dependence and waste generation. Synthetic models offer key educational benefits over animal models by closely mimicking human anatomy and pathophysiology, providing consistent and anatomically accurate training. Unlike animal models, they eliminate variability in tissue properties, ensuring standardised and reliable experiences. Moreover, synthetic models can simulate specific pathologies, enabling targeted learning that may be difficult with animal tissue. Resistance related to clinical relevance and preference for animal-based SBE is a persisting challenge that might be overcome through the development of clinically and anatomically relevant tissue-mimicking materials, like those previously developed for other applications such as quality assurance phantoms in diagnostic imaging. The involvement of knowledge or end-user engagement, along with evidence-based design solutions, is crucial to catalyse a paradigm shift in a discipline deeply entrenched in tradition. The combined expertise, skills, and perspectives of medical professionals, educators, academic researchers, and industry specialists could collaboratively develop alternative methods to simulate live animal scenarios, replacing and reducing animal tissue dependence in SBE.

Background: We aimed to measure the effect of a 2-day structured paediatric simulation-based training (SBT) on basic and advanced airway management during simulated paediatric resuscitations.

Methods: Standardised paediatric high-fidelity SBT was conducted in 12 of the 15 children's hospitals in Hesse, Germany. Before and after the SBT the study participants took part in two study scenarios (PRE and POST scenario), which were recorded using an audio-video system. Airway management was assessed using a performance evaluation checklist. Time to initiate ventilation, frequency, and timing of endotracheal intubation (ETI), and its influence on other life support interventions were assessed. Differences in airway management between hospitals with and without a PICU were evaluated.

Results: Two hundred twenty-nine participants formed 58 interprofessional resuscitation teams. All teams recognised apnoea in their simulated patients and initiated ventilation during the scenarios. Time to recognition of apnoea and time to initiation of ventilation did not improve significantly after SBT, but teams were significantly more likely to select appropriately sized airway equipment. ETI was attempted in 55% PRE and 40% POST scenarios (p=0.1). The duration of the entire ETI process was significantly shorter in the POST scenarios. Chest compressions (CC) were frequently discontinued during ETI attempts, which improved after SBT (PRE 73% vs. POST 43%, p = 0.035). Adequate resumption of CC after completion of intubation was also significantly more frequent in the POST scenarios (46% vs. 74%, p = 0.048). During ETI attempts, CC were more likely to be adequately continued in teams from hospitals with a PICU (PRE scenarios: PICU 20% vs. NON-PICU 36%; POST scenarios: PICU 79%, NON-PICU 22%; p < 0.01).

Conclusions: Our data suggest an association between airway management complexity and basic life support measures. Although the frequency of ETI was not significantly reduced after a 2-day SBT intervention, the duration of advanced airway management was shortened thus reducing no-ventilation time which led to fewer interruptions in chest compressions during simulated paediatric resuscitations. SBT may be adapted to the participants' workplace to maximize its effect and improve the overall performance in paediatric resuscitation.

Background: Behavioural marker systems are used across several healthcare disciplines to assess behavioural (non-technical) skills, but rater training is variable, and inter-rater reliability is generally poor. Inter-rater reliability provides data about the tool, but not the competence of individual raters. This study aimed to test the inter-rater reliability of a new behavioural marker system (PhaBS - pharmacists' behavioural skills) with clinically experienced faculty raters and near-peer raters. It also aimed to assess rater competence when using PhaBS after brief familiarisation, by assessing completeness, agreement with an expert rater, ability to rank performance, stringency or leniency, and avoidance of the halo effect.

Methods: Clinically experienced faculty raters and near-peer raters attended a 30-min PhaBS familiarisation session. This was immediately followed by a marking session in which they rated a trainee pharmacist's behavioural skills in three scripted immersive acute care simulated scenarios, demonstrating good, mediocre, and poor performances respectively. Inter-rater reliability in each group was calculated using the two-way random, absolute agreement single-measures intra-class correlation co-efficient (ICC). Differences in individual rater competence in each domain were compared using Pearson's chi-squared test.

Results: The ICC for experienced faculty raters was good at 0.60 (0.48-0.72) and for near-peer raters was poor at 0.38 (0.27-0.54). Of experienced faculty raters, 5/9 were competent in all domains versus 2/13 near-peer raters (difference not statistically significant). There was no statistically significant difference between the abilities of clinically experienced versus near-peer raters in agreement with an expert rater, ability to rank performance, stringency or leniency, or avoidance of the halo effect. The only statistically significant difference between groups was ability to compete the assessment (9/9 experienced faculty raters versus 6/13 near-peer raters, p = 0.0077).

Conclusions: Experienced faculty have acceptable inter-rater reliability when using PhaBS, consistent with other behaviour marker systems; however, not all raters are competent. Competence measures for other assessments can be helpfully applied to behavioural marker systems. When using behavioural marker systems for assessment, educators must start using such rater competence frameworks. This is important to ensure fair and accurate assessments for learners, to provide educators with information about rater training programmes, and to provide individual raters with meaningful feedback.

Background: Increasingly, virtual simulations are being integrated into higher education. A successful experience goes far beyond simply offering learners access to a virtual simulation; it requires a facilitator who understands the learners' needs and course objectives, choses the right virtual simulation for the learner, creates a welcoming space that promotes learning, and evaluates the experience.

Methods: Facilitators from three different healthcare programs and six educational institutions and students from two different healthcare programs were included in this exploratory qualitative research study. Interviews and focus groups and thematic analysis were conducted to understand the role of the facilitator when using virtual simulations and their impact on student learning.

Results: The facilitator themes were supported by the student focus groups. The first theme, the facilitator experience, included sub-themes of simulation pedagogy and debriefing with a practice partner. The second theme was virtual simulation: impact on learning and included sub-themes on student outcomes, technology and design, and repetitive play.

Conclusion: Effective facilitation skills are integral to quality virtual simulation experiences. Trained facilitators help students achieve virtual simulation learning outcomes and prepare for clinical practice.

Simulation-based education often involves learners or teams attempting to manage situations at the limits of their abilities. As a result, it can elicit emotional reactions in participants. These emotions are not good or bad, they simply are. Their value at any given moment is determined by their utility in meeting the goals of a particular situation. When emotions are particularly intense, or a given emotion is not aligned with the situation, they can impede learners' ability to engage in a simulation activity or debriefing session, as well as their ability to retain knowledge and skills learned during the session. Building on existing guidance for simulation educators seeking to optimize the learning state/readiness in learners, this paper explores the theory and research that underpins the practical application of how to recognize and support learners' emotions during simulation sessions. Specifically, we describe the impact of various emotions on the cognitive processes involved in learning and performance, to inform practical guidance for simulation practitioners: (1) how to recognize and identify emotions experienced by others, (2) how to determine whether those emotional reactions are problematic or helpful for a given situation, and (3) how to mitigate unhelpful emotional reactions and leverage those that are beneficial in achieving the goals of a simulation session.

Impactful learning through simulation-based education involves effective planning and design. This can be a complex process requiring educators to master a varied toolkit of analysis tools, learning methodologies, and evaluative strategies; all to ensure engagement of learners in a meaningful and impactful way. Where there is a lack of thoughtful design, simulation-based education programmes may be inefficiently deployed at best, and completely ineffective or even harmful to learning and learners at worst. This paper presents a useful sense-making framework, designed to support simulation educators in designing their learning activities in a systematic, stepwise, and learner centred way.

Background: Regular training for mass casualty incidents at physical simulation events is vital for emergency services. The preparation and execution of these simulations consume huge amounts of time, personnel, and money. It is therefore important to gather as much information as possible from each simulation while minimizing any influence on the participants, so as to keep the simulation as realistic as possible. In this paper, an analysis of GPS-based remote motion measurements of participants in a mass casualty incident simulation is presented. A combination of different evaluation methods is used to analyze the data. This could reduce the potential bias of the measurement methods.

Methods: Movement patterns of participants of mass casualty incident simulations, measured by GPS loggers, were analyzed. The timeline of the simulation was segmented into event sections, based on movement patterns of participants entering or leaving defined areas. Movement patterns of participants working closely together were correlated to analyze their cooperation. Written logs created by observers on the ground were used to reconstruct the events of the simulation, to provide a comparative reference to validate the motion analysis.

Results: Recorded motion patterns of the participants were found to be qualitatively related to observer logs and triage allocations, allowing a partial reconstruction of the behavior of the participants during the simulation. By analyzing the times the simulation patients left the site of events some possible misjudgments in the triage decisions were indicated.

Conclusions: Analysis of movement patterns from GPS loggers and comparison with observations made on the ground showed that accurate information about the events during the simulation can be automatically delivered. Although the records of observers on the ground are vital to assess details, delegation of the automated analysis of individual and group motion could perhaps allow observers to concentrate on more specific tasks. The partially automated motion analysis methods presented should simplify the process of analyzing mass casualty incident simulations.

Simulation program staff and leadership often struggle to partner with front-line healthcare workers, their managers, and health system leaders. Simulation-based learning programs are too often seen as burdensome add-ons rather than essential mechanisms supporting clinical workforce readiness. Healthcare system leaders grappling with declining morale, economic pressure, and too few qualified staff often don't see how simulation can help them, and we simulation program leaders can't seem to bridge this gap. Without clear guidance from front-line clinicians and leaders, the challenge of building and maintaining sustainably relevant simulation offerings can seem overwhelming. We argue that three blind spots have limited our ability to see the path to collaborations that support front-line workforce readiness: We wrongly assume that our rigor in designing and delivering programs will lead to front-line participant engagement and positive impact, we overestimate the existence of shared priorities, mindsets, and expertise with our would-be partners, and we contribute to building a façade of superficial education compliance that distracts from vital skill development. How do we design simulation-based training programs that are valued, supported, and sustained by key partners over time? (1) By seeing ourselves as partners first and designers second; (2) by using a boundary spanning design process that shifts the primary psychological ownership of training outcomes to our partners; and (3) by focusing this shared design process on workforce readiness for the situations that our healthcare partners care about most. Drawing on lessons from more than 800 readiness plans developed by participants in our courses and the authors' successes and mistakes in partnering with healthcare teams for front-line readiness, we introduce the concepts, commitments, and practices of "readiness planning" along with three detailed examples of readiness planning in action.

Addressing health inequities in health professions education is essential for preparing healthcare workers to meet the demands of diverse communities. While simulation has become a widely recognized and effective method for providing safe and authentic clinical learning experiences, there has been limited attention towards the power of simulation in preparing health practitioners to work with groups who experience health disparities due to systems of inequality. Balancing technical proficiency with educational approaches that foster critical reflection and inform action oriented towards social accountability is essential. Transformational learning promotes the development of critical consciousness through critical reflection. Debriefing plays a crucial role in fostering learning in this direction by providing a structured opportunity to critically reflect on taken for granted assumptions, examine power and privilege embedded within systems and structures, and empower learners to take action toward changing those conditions. Building on the Promoting Excellence and Reflective Learning in Simulation (PEARLS) Healthcare Debriefing Tool, we propose a PEARLS Debriefing for Social Justice and Equity (DSJE) Tool that specifically directs attention to systems of inequality that contribute to health disparities for vulnerable groups across a range of simulation scenarios. This approach has two aims: (a) to transform debriefings into a critically reflective space by engaging learners in dialogue about social and structural determinants of health that may create or perpetuate inequities and (b) to foster critical reflection on what actions can be taken to improve the health and well-being of identified at risk and vulnerable groups. From this perspective, we can use the adapted PEARLS Tool to incorporate conversations about systems of inequality, equity, diversity, and inclusion (EDI) into our existing educational practices, and make concentrated efforts towards community-driven and socially conscious simulation-based education (SBE).

Healthcare debriefing is a cognitively demanding conversation after a simulation or clinical experience that promotes reflection, underpinned by psychological safety and attention to learner needs. The process of debriefing requires mental processing that engages both "fast" or unconscious thinking and "slow" intentional thinking to be able to navigate the conversation. "Fast" thinking has the potential to surface cognitive biases that impact reflection and may negatively influence debriefer behaviors, debriefing strategies, and debriefing foundations. As a result, negative cognitive biases risk undermining learning outcomes from debriefing conversations. As the use of healthcare simulation is expanding, the need for faculty development specific to the roles bias plays is imperative. In this article, we hope to build awareness about common cognitive biases that may present in debriefing conversations so debriefers have the chance to begin the hard work of identifying and attending to their potential detrimental impacts.