Effectiveness analysis of traditional and mixed reality simulations in medical training: a methodological approach for the assessment of stress, cognitive load and performance

La simulazione nell'educazione in medicina è considerata un metodo di formazione in grado di migliorare le competenze cliniche e il comportamento degli operatori sanitari e, di conseguenza, la qualità dell'assistenza per il paziente. Inoltre, l'utilizzo di nuove tecnologie come la Realtà Aumentata, offre ai discenti l'opportunità di esercitarsi in un ambiente immersivo. L'opportunità di sperimentare questo innovativo metodo didattico è efficace non solo nel ridurre il rischio di errori e approcci sbagliati ma anche nel provare ansia e stress simili a quelli avvertiti nella pratica reale. La sfida sta nel trovare il giusto equilibrio. I discenti devono infatti provare lo stesso stress che avvertirebbero lavorando ad un vero caso clinico ma, allo stesso tempo, devono essere controllati ed evitati possibili disturbi da stress post-traumatico, verificabili soprattutto nel campo della gestione delle emergenze (pronto soccorso). Inoltre, è fondamentale anche ottenere alte prestazioni e un apprendimento adeguato, evitando sovraccarichi cognitivi che influenzerebbero negativamente l’apprendimento. Tuttavia, ad oggi mancano ancora studi approfonditi sull'impatto che le simulazioni mediche hanno su stress, frustrazione, carico cognitivo e apprendimento dei discenti. Per questo motivo, l'obiettivo principale di questo studio è valutare l'efficacia del training tramite simulazione, analizzando prestazioni, ansia, stress e carico cognitivo durante simulazioni cliniche tradizionali (con manichino) ed avanzate (in realtà mista). A questo scopo, è stato sviluppato un approccio metodologico strutturato e completo per valutare le prestazioni, le condizioni emotive e cognitive degli studenti. Questo comprende l'acquisizione e l'analisi di parametri psicologici (valutazione soggettiva), segnali biometrici (valutazione oggettiva) e prestazioni. Questa indagine consente di evidenziare i punti deboli delle simulazioni e offre l'opportunità di definire utili linee guida per la riprogettazione e l'ottimizzazione delle stesse. La metodologia è stata applicata su tre casi studio: il primo si riferisce a simulazioni ad alta fedeltà per la gestione del paziente in pronto soccorso, il secondo si riferisce a simulazioni a bassa fedeltà per la pratica della rachicentesi. Per il terzo caso studio, è stato progettato e sviluppato un prototipo di simulatore in realtà mista per la rachicentesi, con l'obiettivo di migliorare il senso di realismo e immersione della simulazione a bassa fedeltà. 148 studenti sono stati coinvolti nei primi due casi studio osservazionali, mentre soltanto 36 studenti hanno preso parte allo studio pilota sulla simulazione in realtà mista. In tutti i casi di studio sono state effettuate analisi descrittive delle prestazioni, degli stati cognitivi ed emotivi. Per le simulazioni ad alta e bassa fedeltà, le analisi di regressione statistica hanno evidenziato quali variabili influenzano le prestazioni, lo stress e il carico cognitivo degli studenti. Per lo studio pilota sulla realtà mista, l'analisi della user experience ha sottolineato i limiti tecnici della nuova tecnologia.Simulation in medical education is considered a training method capable of improving clinical competence and practitioners’ behaviour, and, consequently quality of care and patient’s outcome. Moreover, the use of new technologies, such as augmented reality, offers to the learners the opportunity to engage themselves in an immersive environment. The opportunity to experiment with this innovative instructional method is effective not only in reducing the risk of errors and wrong approaches but also in experiencing anxiety and stress as in real practice. The challenge is to find the right stress balance: learners have to feel as if they were practicing in the real stressful clinical case, and, at the same time, post-traumatic stress disorders, verifiable especially in the emergency field, must be controlled and avoided. Moreover, it is fundamental also to obtain high performance and learning, thus avoiding cognitive overloads. However, extensive researches about the impact of medical simulations on students’ stress, frustration, cognitive load, and learning are still lacking. For this reason, the main objective of this study is to assess simulation training effectiveness by analysing performance, anxiety, stress, and cognitive load during traditional (with manikin) and advanced (with augmented reality) clinical simulations. A structured and comprehensive methodological approach to assess performance, emotional and cognitive conditions of students has been developed. It includes the acquisition and analysis of psychological parameters (subjective assessment), biometric signals (objective assessment), and task performance. This investigation allows to point out simulations’ weaknesses and offers the opportunity to define useful optimisation guidelines. The methodology has been applied to three case studies: the first one refers to high-fidelity simulations, for the patient management in the emergency room, the second one refers to low-fidelity simulation for rachicentesis. For the third case study, a prototype of a mixed reality simulator for the rachicentesis practice has been designed and developed aiming at improving the sense of realism and immersion of the low-fidelity simulation. While 148 students have been enrolled in the first two case studies, only 36 students have taken part in the pilot study about mixed reality simulation. Descriptive analysis about performance, cognitive and emotional states have been done in all the case studies. For the high-fidelity and low-fidelity simulations, the statistical regression analysis has pointed out which variables affect students’ performance, stress, and cognitive load. For the pilot study about mixed reality, the user experience analysis highlighted the technical limitations of the new technology

A comprehensive method to design and assess mixed reality simulations

AbstractThe scientific literature highlights how Mixed Reality (MR) simulations allow obtaining several benefits in healthcare education. Simulation-based training, boosted by MR, offers an exciting and immersive learning experience that helps health professionals to acquire knowledge and skills, without exposing patients to unnecessary risks. High engagement, informational overload, and unfamiliarity with virtual elements could expose students to cognitive overload and acute stress. The implementation of effective simulation design strategies able to preserve the psychological safety of learners and the investigation of the impacts and effects of simulations are two open challenges to be faced. In this context, the present study proposes a method to design a medical simulation and evaluate its effectiveness, with the final aim to achieve the learning outcomes and do not compromise the students' psychological safety. The method has been applied in the design and development of an MR application to simulate the rachicentesis procedure for diagnostic purposes in adults. The MR application has been tested by involving twenty students of the 6th year of Medicine and Surgery of Università Politecnica delle Marche. Multiple measurement techniques such as self-report, physiological indices, and observer ratings of performance, cognitive and emotional states of learners have been implemented to improve the rigour of the study. Also, a user-experience analysis has been accomplished to discriminate between two different devices: Vox Gear Plus® and Microsoft Hololens®. To compare the results with a reference, students performed the simulation also without using the MR application. The use of MR resulted in increased stress measured by physiological parameters without a high increase in perceived workload. It satisfies the objective to enhance the realism of the simulation without generating cognitive overload, which favours productive learning. The user experience (UX) has found greater benefits in involvement, immersion, and realism; however, it has emphasized the technological limitations of devices such as obstruction, loss of depth (Vox Gear Plus), and narrow FOV (Microsoft Hololens)

Virtual training for assembly tasks: a framework for the analysis of the cognitive impact on operators

The importance of training for operators in industrial contexts is widely highlighted in literature. Virtual Reality (VR) technology is considered an efficient solution for training, since it provides immersive, realistic, and interactive simulations environments where the operator can learn-by-doing, far from the risks of the real field. Its efficacy has been demonstrated by several studies, but a proper assessment of the operator’s cognitive response in terms of stress and cognitive load, during the use of such technology, is still lacking. This paper proposes a comprehensive methodology for the analysis of user’s cognitive states, suitable for each kind of training in the industrial sector and beyond. Preliminary feasibility analysis refers to virtual training for assembly of agricultural vehicles. The proposed protocol analysis allowed understanding the operators’ loads to optimize the VR training application, considering the mental demand during the training, and thus avoiding stress, mental overload, improving the user performance

MIXED REALITY IN MEDICAL SIMULATION: A COMPREHENSIVE DESIGN METHODOLOGY

AbstractIn the medical education field, the use of highly sophisticated simulators and extended reality (XR) simulations allow training complex procedures and acquiring new knowledge and attitudes. XR is considered useful for the enhancement of healthcare education; however, several issues need further research.The main aim of this study is to define a comprehensive method to design and optimize every kind of simulator and simulation, integrating all the relevant elements concerning the scenario design and prototype development.A complete framework for the design of any kind of advanced clinical simulation is proposed and it has been applied to realize a mixed reality (MR) prototype for the simulation of the rachicentesis. The purpose of the MR application is to immerse the trainee in a more realistic environment and to put him/her under pressure during the simulation, as in real practice.The application was tested with two different devices: the headset Vox Gear Plus for smartphone and the Microsoft Hololens. Eighteen students of the 6th year of Medicine and Surgery Course were enrolled in the study. Results show the comparison of user experience related to the two different devices and simulation performance using the Hololens

how to improve worker s well being and company performance a method to identify effective corrective actions

Abstract In manufacturing context, social dimension is often neglected. With Industry 4.0, companies focus more on technologies and data. However, human continues to play a key role in cyber-physical systems and company growth. This work proposes a method to help the company to evaluate workers' experience and identify the optimal solution to improve workers' well-being and company performance. It starts from personalized social analysis within a production plant to identify ergonomics problems and intelligently suggest effective corrective actions. The latter are selected achieving the best trade-off between social, economic and productive aspects. Three case studies are proposed to validate the method

A Transdisciplinary Approach for the Design Optimization of Medical Simulations

Simulation in healthcare is rapidly replacing more traditional educational methods, becoming a fundamental step in the medical training path. Medical simulations have a remarkable impact not only on learners’ competencies and skills but also on their attitudes, behaviors, and emotions such as anxiety, stress, mental effort, and frustration. All these aspects are transferred to the real practice and reflected on patients’ safety and outcomes. The design of medical simulations passes through a careful analysis of learning objectives, technology to be used, instructor’s and learners’ roles, performance assessment, and so on. However, an overall methodology for the simulation assessment and consequent optimization is still lacking. The present work proposes a transdisciplinary framework for the analysis of simulation effectiveness in terms of learners’ performance, ergonomics conditions, and emotional states. It involves collaboration among different professional figures such as engineers, clinicians, specialized trainers, and human factors specialists. The aim is to define specific guidelines for the simulation optimization, to obtain enhanced learners’ performance, improved ergonomics, and consequently positively affect the patient treatment, leading to cost savings for the healthcare system. The proposed framework has been tested on a low-fidelity simulation for the training of rachicentesis and has allowed the definition of general rules for its enhancement

A Preliminary Experimental Study on the Workers’ Workload Assessment to Design Industrial Products and Processes

The human-centered design (HCD) approach places humans at the center of design in order to improve both products and processes, and to give users an effective, efficient and satisfying interactive experience. In industrial design and engineering, HCD is very useful in helping to achieve the novel Industry 5.0 concept, based on improving workers’ wellbeing by providing prosperity beyond jobs and growth, while respecting the production limits of the planet as recently promoted by the European Commission. In this context, the paper proposes an ergonomic assessment method based on the analysis of the workers’ workload to support the design of industrial products and processes. This allows the simultaneous analysis of the physical and cognitive workload of operators while performing their tasks during their shift. The method uses a minimum set of non-invasive wearable devices to monitor human activity and physiological parameters, in addition to questionnaires for subjective self-assessment. The method has been preliminarily tested on a real industrial case in order to demonstrate how it can help companies to support the design of optimized products and processes promoting the workers’ wellbeing

Human-centred data-driven redesign of simulation-based training: a qualitative study applied on two use cases of the healthcare and industrial domains

Among the main features of Industry 4.0, digitization and the evolution of the human-machine interaction occupy a central role. These concepts are transferring even in the health domain, moving toward Healthcare 4.0. The new concept of Industry 5.0 further promotes the human-centric perspective focusing on the consideration of human factors. In this context, training for workers, both in the industry and in the healthcare sectors, needs to be strongly human-centred to be efficient and effective. This paper refers to simulation-based training and aims to provide a transdisciplinary framework for the simulation assessment from the learners’ perspective. The final scope is to outline a set of data-driven guidelines for the simulation optimization and redesign, throughout a human-centred approach, aiming to improve the workers’ performance and the overall learning process, considering the physical, cognitive, and emotional conditions. The proposed method is suitable for each kind of training (both traditional and with the use of virtual reality/augmented reality systems) and relevant for every sector. Two different use cases are presented, respectively referring to the healthcare and industry fields, proposing a unique assessment protocol. The healthcare use case considered the low-fidelity simulation of lumbar puncture, while the industrial use case referred to the replacement of the engine oil filter on tractors. Although the great differences between the content of the use cases, the results obtained about performance as well as cognitive and emotional states are close enough to define a common set of guidelines to redesign and optimize the simulation-based training

Healthy Ageing: A Decision-Support Algorithm for the Patient-Specific Assignment of ICT Devices and Services

In response to rapid population ageing, digital technology represents the greatest resource in supporting the implementation of active and healthy ageing principles at clinical and service levels. However, digital information platforms that deliver coordinated health and social care services for older people to cover their needs comprehensively and adequately are still not widespread. The present work is part of a project that focuses on creating a new personalised healthcare and social assistance model to enhance older people’s quality of life. This model aims to prevent acute events to favour the elderly staying healthy in their own home while reducing hospitalisations. In this context, the prompt identification of criticalities and vulnerabilities through ICT devices and services is crucial. According to the human-centred care vision, this paper proposes a decision-support algorithm for the automatic and patient-specific assignment of tailored sets of devices and local services based on adults’ health and social needs. This decision-support tool, which uses a tree-like model, contains conditional control statements. Using sequences of binary divisions drives the assignation of products and services to each user. Based on many predictive factors of frailty, the algorithm aims to be efficient and time-effective. This goal is achieved by adequately combining specific features, thresholds, and constraints related to the ICT devices and patients’ characteristics. The validation was carried out on 50 participants. To test the algorithm, its output was compared to clinicians’ decisions during the multidimensional evaluation. The algorithm reported a high sensitivity (96% for fall monitoring and 93% for cardiac tracking) and a lower specificity (60% for fall monitoring and 27% for cardiac monitoring). Results highlight the preventive and protective behaviour of the algorithm