Training Medical Communication Skills with Virtual Patients: Literature Review and Directions for Future Research

Effective communication is a crucial skill for healthcare providers since it leads to better patient health, satisfaction and avoids malpractice claims. In standard medical education, students’ communication skills are trained with role-playing and Standardized Patients (SPs), i.e., actors. However, SPs are difficult to standardize, and are very resource consuming. Virtual Patients (VPs) are interactive computer-based systems that represent a valuable alternative to SPs. VPs are capable of portraying patients in realistic clinical scenarios and engage learners in realistic conversations. Approaching medical communication skill training with VPs has been an active research area in the last ten years. As a result, the number of works in this field has grown significantly. The objective of this work is to survey the recent literature, assessing the state of the art of this technology with a specific focus on the instructional and technical design of VP simulations. After having classified and analysed the VPs selected for our research, we identified several areas that require further investigation, and we drafted practical recommendations for VP developers on design aspects that, based on our findings, are pivotal to create novel and effective VP simulations or improve existing ones

Holo-BLSD – A holographic tool for self-training and self-evaluation of emergency response skills

In case of cardiac arrest, prompt intervention of bystanders can be vital in saving lives. Basic Life Support and Defibrillation (BLSD) is a procedure designed to deliver a proficient emergency first response. Developing skills in BLSD in a large part of the population is a primary educational goal of resuscitation medicine. In this context, novel computer science technologies like Augmented Reality (AR) and Virtual Reality (VR) can alleviate some of the drawbacks of traditional instructor-led courses, especially concerning time and cost constraints. This paper presents Holo-BLSD, an AR system that allows users to learn and train the different operations involved in BLSD and receive an automatic assessment. The system uses a standard manikin which is quotes{augmented} by an interactive virtual environment that reproduces realistic emergency scenarios. The proposed approach has been validated through a user study. Subjective results confirmed the usability of the devised tool and its capability to stimulate learners' attention. Objective results indicated no statistical significance in the differences between the examiners' evaluation of users who underwent traditional and AR training; they also showed a close agreement between expert and automatic assessments, suggesting that Holo-BLSD can be regarded as an effective self-learning method and a reliable self-evaluation tool

A multi-organ-on-chip to recapitulate the infiltration and the cytotoxic activity of circulating NK cells in 3D matrix-based tumor model

The success of immunotherapeutic approaches strictly depends on the immune cells interaction with cancer cells. While conventional in vitro cell cultures under-represent the complexity and dynamic crosstalk of the tumor microenvironment, animal models do not allow deciphering the anti-tumor activity of the human immune system. Therefore, the development of reliable and predictive preclinical models has become crucial for the screening of immune-therapeutic approaches. We here present an organ-on-chip organ on chips (OOC)-based approach for recapitulating the immune cell Natural Killer (NK) migration under physiological fluid flow, infiltration within a 3D tumor matrix, and activation against neuroblastoma cancer cells in a humanized, fluid-dynamic environment. Circulating NK cells actively initiate a spontaneous "extravasation " process toward the physically separated tumor niche, retaining their ability to interact with matrix-embedded tumor cells, and to display a cytotoxic effect (tumor cell apoptosis). Since NK cells infiltration and phenotype is correlated with prognosis and response to immunotherapy, their phenotype is also investigated: most importantly, a clear decrease in CD16-positive NK cells within the migrated and infiltrated population is observed. The proposed immune-tumor OOC-based model represents a promising approach for faithfully recapitulating the human pathology and efficiently employing the immunotherapies testing, eventually in a personalized perspective. An immune-organ on chip to recapitulate the tumor-mediated infiltration of circulating immune cells within 3D tumor model

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

Efficacy of a new technique - INtubate-RECruit-SURfactant-Extubate - "IN-REC-SUR-E" - in preterm neonates with respiratory distress syndrome: Study protocol for a randomized controlled trial

Background: Although beneficial in clinical practice, the INtubate-SURfactant-Extubate (IN-SUR-E) method is not successful in all preterm neonates with respiratory distress syndrome, with a reported failure rate ranging from 19 to 69 %. One of the possible mechanisms responsible for the unsuccessful IN-SUR-E method, requiring subsequent re-intubation and mechanical ventilation, is the inability of the preterm lung to achieve and maintain an "optimal" functional residual capacity. The importance of lung recruitment before surfactant administration has been demonstrated in animal studies showing that recruitment leads to a more homogeneous surfactant distribution within the lungs. Therefore, the aim of this study is to compare the application of a recruitment maneuver using the high-frequency oscillatory ventilation (HFOV) modality just before the surfactant administration followed by rapid extubation (INtubate-RECruit-SURfactant-Extubate: IN-REC-SUR-E) with IN-SUR-E alone in spontaneously breathing preterm infants requiring nasal continuous positive airway pressure (nCPAP) as initial respiratory support and reaching pre-defined CPAP failure criteria. Methods/design: In this study, 206 spontaneously breathing infants born at 24+0-27+6 weeks' gestation and failing nCPAP during the first 24 h of life, will be randomized to receive an HFOV recruitment maneuver (IN-REC-SUR-E) or no recruitment maneuver (IN-SUR-E) just prior to surfactant administration followed by prompt extubation. The primary outcome is the need for mechanical ventilation within the first 3 days of life. Infants in both groups will be considered to have reached the primary outcome when they are not extubated within 30 min after surfactant administration or when they meet the nCPAP failure criteria after extubation. Discussion: From all available data no definitive evidence exists about a positive effect of recruitment before surfactant instillation, but a rationale exists for testing the following hypothesis: a lung recruitment maneuver performed with a step-by-step Continuous Distending Pressure increase during High-Frequency Oscillatory Ventilation (and not with a sustained inflation) could have a positive effects in terms of improved surfactant distribution and consequent its major efficacy in preterm newborns with respiratory distress syndrome. This represents our challenge. Trial registration: ClinicalTrials.gov identifier: NCT02482766. Registered on 1 June 2015

MetaRehab: Enhancing Parkinson's Disease Rehabilitation through Gamified Virtual Reality, a Usability Study

Motor impairment and cognitive decline are the most relevant symptoms of Parkinson's disease (PD), a neurodegenerative syndrome that is usually treated with pharmacological and rehabilitation therapy. However, traditional physical and cognitive rehabilitation approaches require frequent visits to specialized centers and often lack engagement, leading to demotivation and non-compliance. The increasing prevalence of neurodegenerative syndromes highlights the need for innovative, more sustainable and entertaining rehabilitation strategies. This study explores the potential of immersive Virtual Reality (VR) in physical and cognitive at-home rehabilitation. By incorporating gamification elements, our approach aims to increase patient motivation and engagement, which are crucial for successful rehabilitation outcomes. The use of Natural User Interfaces in the application increases user engagement and the user experience by enabling intuitive interactions and thus promoting a sense of agency. In addition, the VR environment utilizes different communication channels to deliver instructions and feedback on activities, ensuring that the system is accessible to individuals with different needs and preferences. In this paper, we describe the experimental evaluation of the usability and perceived effort of MetaRehab, the proposed VR-based rehabilitation process, prior to its application in a therapeutic context. These preliminary results provide a solid foundation for future enhancements aimed at adding new features and further increasing system inclusivity and engagement

High temperature interfacial interactions in Ni-X/HfB2 systems

This study presents data on the wettability and the interfacial characteristics of systems based on HfB2 ceramics hot-pressed with different sintering aids (B4C, HfSi2) in contact with liquid Ni-X alloys (X= Ti, B) to promote/control wettability. The experimental data, obtained by sessile drop tests at 1500 ?C under carefully controlled conditions, are reported and discussed as a function of time, compositions and ceramic micro-structure. The specimens are analysed by optical microscopy, SEM, EDS, X-ray diffraction and by means of specific mechanical adhesion tests. The main results, at present, are: 1. Liquid Ni first wets and then penetrates polycrystalline HfB2 substrate via grain boundaries. 2. During high-temperature interaction, two phenomena take place that are responsible for wettability kinetics and mass transfer in the Ni/HfB2 couples, i.e. I substrate dissolution, resulting in the displacement of the liquid/substrate interface, II drop spreading, resulting in fast movement of the triple line along the substrate surface. 3. The "competition" between these two phenomena affects the final shape of the drop/substrate interface, i.e., the drop has a lens-like shape if the substrate dissolution is a dominant factor while it forms a thin layer on the substrate if kinetics of spreading is fast but substrate dissolution is negligible. 4. Metallurgical factors, but not interfacial reactions, are responsible for the final structure of drop/substrate interface that is formed during cooling, but not at the test temperature, mainly because, during cooling, recrystallization of HfB2 through the liquid state takes place. 5. Other precipitates (e.g. HfC, Ni intermetallics) are evidenced which can be formed by two processes: ? in situ directly in the drop by chemical reaction between Hf, dissolved in liquid Ni from HfB2, and Ni itself and/or C, dissolved from B4C or from carbon present as a main impurity ? due to chemical reaction between Hf, dissolved in liquid Ni from HfB2, and residual B4C grains, opened at and released from the substrate during dissolution of surrounding HfB2 grains. The unusual shape of drop/substrate interface with well-distinguished two-regions, the specific spreading kinetics curves and the influence of interfacial structure on wetting and adhesion (also mechanical), as well as the need of further research aiming at optimising the ceramic/ceramic joining procedures, will be discussed

Asteroid Escape: A serious game to foster teamwork abilities

Teamwork skills have become a fundamental asset in the labor market. Modern organizations are increasingly implementing team building activities, aimed to improve or assess their employees’ skills. Research suggests that serious games could be promising tools capable to support the creation of engaging and effective team building experiences. However, the design and development of serious games targeting these activities is still sparse and requires further investigation. This work introducesAsteroid Escape, an immersive serious game for team building, whose design was based on theoretical models on teamwork effectiveness. Although conducted on a restricted user sample, preliminary experiments suggest that tools like the devised one could positively contribute to ongoing research and implementation efforts targeting the exploitation of technology-enhanced learning methods for the development of teamwork skills and, more in general, of so-called soft skills

Assessing the Usability of Different Virtual Reality Systems for Firefighter Training

The use of Virtual Reality (VR) based learning environments for training firefighters is becoming more and more common. The key advantages of these approaches is that they allow the development of experiential learning environments, where trainees can be involved into and interact with complex emergency scenarios, including those that cannot rely for the training on real world systems and environments due to costs or security concerns. Despite that, current VR training systems are still affected by a number of weaknesses, mainly related to usability and to the (limited) sense of presence conveyed by the virtual environment (VE), which can negatively affect the expected learning outcomes. To this end, in order to gain further insight into this problem, this work aims at assessing the usability of a firefighter training application deployed in three VR systems and exploiting serious games in the educational approach. The VR systems under analysis provide different levels of immersion and offer different approaches to manage interaction and locomotion inside the VE. Experimental results, obtained through a user study, show differences among the three systems. In particular, the devices and metaphors used to manage locomotion in VR seem to be the most critical parameters with respect to usability and learners' achievements

Feature Matching-based Approaches to Improve the Robustness of Android Visual GUI Testing

In automated Visual GUI Testing (VGT) for Android devices, the available tools often suffer from low robustness to mobile fragmentation, leading to incorrect results when running the same tests on different devices. To soften these issues, we evaluate two feature matching-based approaches for widget detection in VGT scripts, which use, respectively, the complete full-screen snapshot of the application (Fullscreen) and the cropped images of its widgets Cropped) as visual locators to match on emulated devices. Our analysis includes validating the portability of different feature-based visual locators over various apps and devices and evaluating their robustness in terms of cross-device portability and correctly executed interactions. We assessed our results through a comparison with two state-of-the-art tools, EyeAutomate and Sikuli. Despite a limited increase in the computational burden, our Fullscreen approach outperformed state-of-the-art tools in terms of correctly identified locators across a wide range of devices and led to a 30% increase in passing tests. Our work shows that VGT tools' dependability can be improved by bridging the testing and computer vision communities. This connection enables the design of algorithms targeted to domain-specific needs and thus inherently more usable and robust