Model-driven engineering for digital twins: a graph model-based patient simulation application.

Introduction: Digital twins of patients are virtual models that can create a digital patient replica to test clinical interventions in silico without exposing real patients to risk. With the increasing availability of electronic health records and sensor-derived patient data, digital twins offer significant potential for applications in the healthcare sector. Methods: This article presents a scalable full-stack architecture for a patient simulation application driven by graph-based models. This patient simulation application enables medical practitioners and trainees to simulate the trajectory of critically ill patients with sepsis. Directed acyclic graphs are utilized to model the complex underlying causal pathways that focus on the physiological interactions and medication effects relevant to the first 6 h of critical illness. To realize the sepsis patient simulation at scale, we propose an application architecture with three core components, a cross-platform frontend application that clinicians and trainees use to run the simulation, a simulation engine hosted in the cloud on a serverless function that performs all of the computations, and a graph database that hosts the graph model utilized by the simulation engine to determine the progression of each simulation. Results: A short case study is presented to demonstrate the viability of the proposed simulation architecture. Discussion: The proposed patient simulation application could help train future generations of healthcare professionals and could be used to facilitate clinicians' bedside decision-making.

Digital intraoral and radiologic records in forensic identification: Match with disruptive technology.

While clinical dentistry has seamlessly integrated the digital revolution, there is a gap in the technological capabilities of forensic dentistry.The study aimed to compare the superimposition accuracy of two different three-dimensional record formats, namely the intraoral scanner and cone beam computer tomography, in the context of forensic identification.The sample consisted of randomly selected adults (n=10) of both sexes aged between 20 and 50 years. Following the acquisition of data using the Medit i700 wireless scanner and the iCAT Tomograph with InVivo software, the records were analysed and compared through superimposition using Medit Scan Clinic software to assess the technical precision of anatomical identification details.The results obtained through the superimposition of dental and bone records following intra- and inter-observer analysis enabled an accurate comparison and identification of an individual. This method can differentiate between positive and negative matches, achieving exclusion results and offering a potential solution to overcoming the absence of a standardisation procedure in human identification.

3D virtual patient-Magnetically retained printed stackable system for implant guided placement: Case report.

OBJECTIVE: The aim of this report is to present the complete workflow of 3D virtual patient for planning and performing implant surgery with magnetically retained 3D-printed stackable guides. CLINICAL CONSIDERATIONS: A 3D-printed stackable system was proposed based on bone, dental, and facial references. Initially, a 66-year-old male patient was digitalized through photographs, cone beam computed tomography, and intraoral scans (Virtuo Vivo, Straumann). All files were merged to create a 3D virtual patient in the planning software (coDiagnostiX, Straumann). Sequential stackable guides were designed, printed, and cured. Magnets were inserted into connectors, and the interim protheses received color characterization. Four mounted guides were produced for the specific purposes of pin fixation, bone reduction, implant placement, and immediate provisionalization. After surgery and healing period, patient digital data were updated. Final implant positions were compared to planned values and inconsistencies were clinically acceptable. The mean angular deviation was 5.4° (3.2-7.3) and mean 3D discrepancies were of 0.90 mm (0.46-1.12) at the entry point and 1.68 mm (1.00-2.20) at implant apex. Case follow-up revealed stability, patient's comfort, and no intercurrences. CONCLUSION: Magnetically retained stackable guides provide treatment accuracy and reduce surgical and prosthetic complications. The projected virtual patient enhances decision-making and communication between the multidisciplinary team and the patient, while decreases time and costs. CLINICAL SIGNIFICANCE: Bidimensional diagnosis and freehand implant placement have limitations and outcomes often rely on professionals' expertise. Performing facially driven virtual planning improves treatment predictability. This approach promotes function, esthetic harmony, and patient satisfaction. Implant guided surgery and 3D printed prostheses constitute a reproducible digital workflow that can be implemented into clinical practice to optimize dental care.

Perception of enhanced learning in medicine through integrating of virtual patients: an exploratory study on knowledge acquisition and transfer.

INTRODUCTION: Virtual Patients (VPs) have been shown to improve various aspects of medical learning, however, research has scarcely delved into the specific factors that facilitate the knowledge gain and transfer of knowledge from the classroom to real-world applications. This exploratory study aims to understand the impact of integrating VPs into classroom learning on students' perceptions of knowledge acquisition and transfer. METHODS: The study was integrated into an elective course on "Personalized Medicine in Cancer Treatment and Care," employing a qualitative and quantitative approach. Twenty-two second-year medical undergraduates engaged in a VP session, which included role modeling, practice with various authentic cases, group discussion on feedback, and a plenary session. Student perceptions of their learning were measured through surveys and focus group interviews and analyzed using descriptive statistics and thematic analysis. RESULTS: Quantitative data shows that students highly valued the role modeling introduction, scoring it 4.42 out of 5, and acknowledged the practice with VPs in enhancing their subject matter understanding, with an average score of 4.0 out of 5. However, students' reflections on peer dialogue on feedback received mixed reviews, averaging a score of 3.24 out of 5. Qualitative analysis (of focus-group interviews) unearthed the following four themes: 'Which steps to take in clinical reasoning', 'Challenging their reasoning to enhance deeper understanding', 'Transfer of knowledge ', and ' Enhance Reasoning through Reflections'. Quantitative and qualitative data are cohered. CONCLUSION: The study demonstrates evidence for the improvement of learning by incorporating VPs with learning activities. This integration enhances students' perceptions of knowledge acquisition and transfer, thereby potentially elevating students' preparedness for real-world clinical settings. Key facets like expert role modeling and various authentic case exposures were valued for fostering a deeper understanding and active engagement, though with some mixed responses towards peer feedback discussions. While the preliminary findings are encouraging, the necessity for further research to refine feedback mechanisms and explore a broader spectrum of medical disciplines with larger sample sizes is underscored. This exploration lays a groundwork for future endeavors aimed at optimizing VP-based learning experiences in medical education.

Effectiveness of a virtual patient simulation training on improving provider engagement in suicide safer care.

BACKGROUND: Health care providers have a critical opportunity to mitigate the public health problem of suicide. Virtual patient simulations (VPS) allow providers to learn and practice evidence-based suicide prevention practices in a realistic and risk-free environment. The purpose of this study was to test whether receiving VPS training increases the likelihood that providers will engage in effective suicide safer care practices. METHODS: Behavioral health and non-behavioral health providers (N = 19) at a Federally Qualified Health Center who work with patients at risk for suicide received the VPS training on risk assessment, safety planning, and motivation to engage in treatment. Providers' electronic health records were compared 6 months pre- and post-VPS training on their engagement in suicide safer care practices of screening, assessment, safety planning, and adding suicide ideation to the problem list. RESULTS: Most behavioral health providers were already engaging in evidence-based suicide prevention care prior to the VPS training. Findings demonstrated the VPS training may impact the likelihood that non-behavioral health providers engage in suicide safer care practices. CONCLUSION: VPS training in evidence-based suicide prevention practices can optimize and elevate all health care providers' skills in suicide care regardless of role and responsibility, demonstrating the potential to directly impact patient outcomes.

Acceptance of virtual patients as a continuous professional development approach among practicing nurses in primary health care settings in a low-income country: a quasi-experimental posttest setup design.

BACKGROUND: Virtual patients are an educational technological approach used in healthcare education. Its distinctive features have rendered virtual patient technology appealing for the training of medical and healthcare students, particularly in the enhancement of clinical reasoning. Virtual patients are less often applied for continuous professional development for practicing healthcare providers, and there is a scarcity of studies exploring this possibility. This study aimed to assess the acceptability of nurses for using virtual patients as a continuous professional development approach. METHOD: The study used a quasi-experimental posttest setup design. The study was conducted in ten primary healthcare settings in Rwanda. Among 76 nurses who consented to participate in the study, 56 completed the intervention and responded to the study questionnaire. Following a one-week program of continuous professional development on four non-communicable diseases, the study used a self-administered questionnaire based on the Technology Acceptance Model 3 to collect data. Descriptive analysis served as the primary method for analyzing participants' responses. The study also used a correlation test to assess the relationship of variables. RESULTS: Across all items in the questionnaire, the median response tended towards either agree or strongly agree, with only a minority number of participants expressing strong disagreement, disagreement, or neutrality. The results indicated a significant positive correlation between perceived usefulness and behavior intention (p < 0.001). CONCLUSION: The findings indicate an acceptability and behavioral intention of adopting virtual patients as an alternative continuous professional development approach among nurses working at health centers in Rwanda or other locations with similar contexts.

Digital Health Education for the Future: The SaNuRN (Santé Numérique Rouen-Nice) Consortium's Journey.

SaNuRN is a five-year project by the University of Rouen Normandy (URN) and the Côte d'Azur University (CAU) consortium to optimize digital health education for medical and paramedical students, professionals, and administrators. The project includes a skills framework, training modules, and teaching resources. In 2027, SaNuRN is expected to train a significant portion of the 400,000 health and paramedical professions students at the French national level. Our purpose is to give a synopsis of the SaNuRN initiative, emphasizing its novel educational methods and how they will enhance the delivery of digital health education. Our goals include showcasing SaNuRN as a comprehensive program consisting of a proficiency framework, instructional modules, and educational materials and explaining how SaNuRN is implemented in the participating academic institutions. SaNuRN is a project aimed at educating and training health-related and paramedics students in digital health. The project results from a cooperative effort between URN and CAU, covering four French departments. The project is based on the French National Referential on Digital Health (FNRDH), which defines the skills and competencies to be acquired and validated by every student in the health, paramedical, and social professions curricula. The SaNuRN team is currently adapting the existing URN and CAU syllabi to FNRDH and developing short-duration video capsules of 20 to 30 minutes to teach all the relevant material. The project aims to ensure that the largest student population earns the necessary skills, and it has developed a two-tier system involving facilitators who will enable the efficient expansion of the project's educational outreach and support the students in learning the needed material efficiently. With a focus on real-world scenarios and innovative teaching activities integrating telemedicine devices and virtual professionals, SaNuRN is committed to enabling continuous learning for healthcare professionals in clinical practice. The SaNuRN team introduced new ways of evaluating healthcare professionals by shifting from a knowledge-based to a competencies-based evaluation, aligning with the Miller teaching pyramid and using the Objective Structured Clinical Examination and Script Concordance Test in digital health education. Drawing on the expertise of URN, CAU, and their public health and digital research laboratories and partners, the SaNuRN project represents a platform for continuous innovation, including telemedicine training and living labs with virtual and interactive professional activities. The SaNuRN project provides a comprehensive, personalized 30-hour training package for health and paramedical students, addressing all 70 FNRDH competencies. The program is enhanced using AI and NLP to create virtual patients and professionals for digital healthcare simulation. SaNuRN teaching materials are open-access. The project collaborates with academic institutions worldwide to develop educational material in digital health in English and multilingual formats. SaNuRN offers a practical and persuasive training approach to meet the current digital health education requirements.

The impact of scaffolded and non-scaffolded suicidal virtual human interaction training on clinician emotional self-awareness, empathic communication, and clinical efficacy.

BACKGROUND: Clinicians working with patients at risk of suicide often experience high stress, which can result in negative emotional responses (NERs). Such negative emotional responses may lead to less empathic communication (EC) and unintentional rejection of the patient, potentially damaging the therapeutic alliance and adversely impacting suicidal outcomes. Therefore, clinicians need training to effectively manage negative emotions toward suicidal patients to improve suicidal outcomes. METHODS: This study investigated the impact of virtual human interaction (VHI) training on clinicians' self-awareness of their negative emotional responses, assessed by the Therapist Response Questionnaire Suicide Form, clinicians' verbal empathic communication assessed by the Empathic Communication and Coding System, and clinical efficacy (CE). Clinical efficacy was assessed by the likelihood of subsequent appointments, perceived helpfulness, and overall interaction satisfaction as rated by individuals with lived experience of suicide attempts. Two conditions of virtual human interactions were used: one with instructions on verbal empathic communication and reminders to report negative emotional responses during the interaction (scaffolded); and the other with no such instructions or reminders (non-scaffolded). Both conditions provided pre-interaction instructions and post-interaction feedback aimed at improving clinicians' empathic communication and management of negative emotions. Sixty-two clinicians participated in three virtual human interaction sessions under one of the two conditions. Linear mixed models were utilized to evaluate the impact on clinicians' negative emotional responses, verbal empathic communication, and clinical efficacy; and to determine changes in these outcomes over time, as moderated by the training conditions. RESULTS: Clinician participants' negative emotional responses decreased after two training sessions with virtual human interactions in both conditions. Participants in the scaffolded condition exhibited enhanced empathic communication after one training session, while two sessions were required for participants in the non-scaffolded condition. Surprisingly, after two training sessions, clinical efficacy was improved in the non-scaffolded group, while no similar improvements were observed in the scaffolded group. CONCLUSION: Lower clinical efficacy after virtual human interaction training in clinicians with higher verbal empathic communication suggests that nonverbal expressions of empathy are critical when interacting with suicidal patients. Future work should explore virtual human interaction training in both nonverbal and verbal empathic communication.

Enhancing clinical reasoning for management of non-communicable diseases: virtual patient cases as a learning strategy for nurses in primary healthcare centers: a pre-post study design.

BACKGROUND: In Rwanda, nurses manage all primary care at health centres, and therefore are their clinical reasoning skills important. In this study, a web-based software that allows the creation of virtual patient cases (VP cases) has been used for studying the possibility of using VP cases for the continuous professional development of nurses in primary health care in Rwanda. Previous studies in pre-service education have linked VP cases with the enhancement of clinical reasoning, a critical competence for nurses. This study investigated the feasibility of continuous professional development through VP cases to further train in-service nurses in clinical reasoning. METHOD: The study used a pre-post test design. Initially, seventy-six participants completed a questionnaire as part of the pre-test phase, subsequently invited to engage with all four VP cases, and finally responded to the post-test questionnaire evaluating clinical reasoning skills. Fifty-six participants successfully completed the entire study process and were considered in the analysis. The primary outcomes of this study were evaluated using a paired t-test for the statistical analysis. RESULTS: The results show that the mean score of clinical reasoning increased significantly from the pre-test to the post-test for all four illness areas (p < 0.001). The study findings showed no statistically significant difference in participants' scores based on demographic factors, including whether they worked in urban or rural areas.  CONCLUSION AND RECOMMENDATION: Utilizing VP cases appears to significantly enhance the continuous professional development of nurses, fostering a deliberate learning process that enables them to reflect on how they manage cases and, in turn, refine their clinical reasoning skills. This study strongly recommends incorporating VP cases in the continuous professional development of nurses at the primary health level (health centers). This is especially pertinent in a context where nurses are required to perform diagnostic processes similar to those employed by physicians.

The effect of case-based mobile virtual patient application on students' academic achievement in clinical reasoning skills.

This mixed-method study aims to determine the effect of the use of mobile virtual patient application with narrated case-based virtual patients as an assistive technology on students' clinical reasoning skills. It makes a notable contribution by exploring the impact of mobile virtual patient applications on healthcare students' clinical skills and their preparation for real-world patient care. In addition, the accuracy of the analysis results regarding the effect on student achievement was analyzed with a second dataset tool, and thus, aiming to increase reliability by verifying the same research question with a different quantitative analysis technique. In the qualitative part of the study, students' views on the implementation were collected through an open-ended questionnaire and the data were subjected to content analysis. An achievement test was also developed to determine the development of students' clinical reasoning skills, which revealed that each of the learning environments had different outcomes regarding students' achievement and that supporting the traditional environment with the mobile virtual patient application yielded better results for increasing students' achievement. Students' opinions about the mobile virtual patient application and the process also support the increase in academic achievement aimed at measuring clinical reasoning skills. The content analysis showed that the students, who generally reported multiple positive factors related to the application, thought that the stories and cases presented created a perception of reality, and they especially highlighted the contribution of the application to learning the story organization. Based on all these results, it can be said that the application supports clinical reasoning, provides practical experience, improves academic achievement, and contributes positively to motivation.

The chance and challenge of creating virtual patients in prosthodontics.

In the field of prosthodontics, the use of virtual patients for biomimetic restoration holds great promise for various applications. Virtual patients consist of digitized data that encompasses details on the morphology, structure, and spatial relationships within the maxillofacial and intraoral regions. Nonetheless, there are several challenges associated with acquiring digital data, achieving accurate alignment, and recording and transferring dynamic jaw movements. This paper aims to concentrate on the process of constructing virtual patients, highlight the key and challenging aspects of virtual patient construction, and advocate for the extensive adoption and utilization of virtual patient technology.

Establishment of a 3D esthetic analysis workflow on 3D virtual patient and preliminary evaluation.

BACKGROUND: In esthetic dentistry, a thorough esthetic analysis holds significant role in both diagnosing diseases and designing treatment plans. This study established a 3D esthetic analysis workflow based on 3D facial and dental models, and aimed to provide an imperative foundation for the artificial intelligent 3D analysis in future esthetic dentistry. METHODS: The established 3D esthetic analysis workflow includes the following steps: 1) key point detection, 2) coordinate system redetermination and 3) esthetic parameter calculation. The accuracy and reproducibility of this established workflow were evaluated by a self-controlled experiment (n = 15) in which 2D esthetic analysis and direct measurement were taken as control. Measurement differences between 3D and 2D analysis were evaluated with paired t-tests. RESULTS: 3D esthetic analysis demonstrated high consistency and reliability (0.973 < ICC < 1.000). Compared with 2D measurements, the results from 3D esthetic measurements were closer to direct measurements regarding tooth-related esthetic parameters (P<0.05). CONCLUSIONS: The 3D esthetic analysis workflow established for 3D virtual patients demonstrated a high level of consistency and reliability, better than 2D measurements in the precision of tooth-related parameter analysis. These findings indicate a highly promising outlook for achieving an objective, precise, and efficient esthetic analysis in the future, which is expected to result in a more streamlined and user-friendly digital design process. This study was registered with the Ethics Committee of Peking University School of Stomatology in September 2021 with the registration number PKUSSIRB-202168136.

Increasing Realism and Variety of Virtual Patient Dialogues for Prenatal Counseling Education Through a Novel Application of ChatGPT: Exploratory Observational Study.

BACKGROUND: Using virtual patients, facilitated by natural language processing, provides a valuable educational experience for learners. Generating a large, varied sample of realistic and appropriate responses for virtual patients is challenging. Artificial intelligence (AI) programs can be a viable source for these responses, but their utility for this purpose has not been explored. OBJECTIVE: In this study, we explored the effectiveness of generative AI (ChatGPT) in developing realistic virtual standardized patient dialogues to teach prenatal counseling skills. METHODS: ChatGPT was prompted to generate a list of common areas of concern and questions that families expecting preterm delivery at 24 weeks gestation might ask during prenatal counseling. ChatGPT was then prompted to generate 2 role-plays with dialogues between a parent expecting a potential preterm delivery at 24 weeks and their counseling physician using each of the example questions. The prompt was repeated for 2 unique role-plays: one parent was characterized as anxious and the other as having low trust in the medical system. Role-play scripts were exported verbatim and independently reviewed by 2 neonatologists with experience in prenatal counseling, using a scale of 1-5 on realism, appropriateness, and utility for virtual standardized patient responses. RESULTS: ChatGPT generated 7 areas of concern, with 35 example questions used to generate role-plays. The 35 role-play transcripts generated 176 unique parent responses (median 5, IQR 4-6, per role-play) with 268 unique sentences. Expert review identified 117 (65%) of the 176 responses as indicating an emotion, either directly or indirectly. Approximately half (98/176, 56%) of the responses had 2 or more sentences, and half (88/176, 50%) included at least 1 question. More than half (104/176, 58%) of the responses from role-played parent characters described a feeling, such as being scared, worried, or concerned. The role-plays of parents with low trust in the medical system generated many unique sentences (n=50). Most of the sentences in the responses were found to be reasonably realistic (214/268, 80%), appropriate for variable prenatal counseling conversation paths (233/268, 87%), and usable without more than a minimal modification in a virtual patient program (169/268, 63%). CONCLUSIONS: Generative AI programs, such as ChatGPT, may provide a viable source of training materials to expand virtual patient programs, with careful attention to the concerns and questions of patients and families. Given the potential for unrealistic or inappropriate statements and questions, an expert should review AI chat outputs before deploying them in an educational program.

Exploring medical students' perceptions of individual and group-based clinical reasoning with virtual patients: a qualitative study.

BACKGROUND: Virtual Patients are computer-based simulations used to teach and evaluate patient interviews, medical diagnoses, and treatment of medical conditions. It helps develop clinical reasoning skills, especially in undergraduate medical education. This study aimed to and investigate the medical students' perceptions of individual and group-based clinical reasoning and decision-making processes by using Virtual Patients. METHODS: The study group comprised 24 third-year medical students. Body Interact® software was utilized as a VP tool. The students' readiness and the courses' learning goals were considered when choosing the scenarios. Semi-structured interview forms were employed for data collection. MAXQDA 2020 qualitative analysis software was used to analyze the data. The students' written answers were analyzed using content analysis. RESULTS: The participants perceived individual applications as beneficial when making clinical decisions with Virtual Patients, but they suggested that group-based applications used with the same cases immediately following individual applications were a more appropriate decision-making method. The results indicated that students learn to make decisions through trial and error, based on software scoring priorities, or using clinical reasoning protocols. CONCLUSION: In group-based reasoning, the discussion-conciliation technique is utilized. The students stated that the individual decision-making was advantageous because it provided students with the freedom to make choices and the opportunity for self-evaluation. On the other hand, they stated that the group based decision-making process activated their prior knowledge, assisted in understanding misconceptions, and promoted information retention. Medical educators need to determine the most appropriate method when using Virtual Patients, which can be structured as individual and/or group applications depending on the competency sought.

Pulmonary response prediction through personalized basis functions in a virtual patient model.

BACKGROUND AND OBJECTIVE: Recruitment maneuvers with subsequent positive-end-expiratory-pressure (PEEP) have proven effective in recruiting lung volume and preventing alveoli collapse. However, determining a safe, effective, and patient-specific PEEP is not standardized, and this more optimal PEEP level evolves with patient condition, requiring personalised monitoring and care approaches to maintain optimal ventilation settings. METHODS: This research examines 3 physiologically relevant basis function sets (exponential, parabolic, cumulative) to enable better prediction of elastance evolution for a virtual patient or digital twin model of MV lung mechanics, including novel elements to model and predict distension elastance. Prediction accuracy and robustness are validated against recruitment maneuver data from 18 volume-controlled ventilation (VCV) patients at 7 different baseline PEEP levels (0 to 12 cmH2O) and 14 pressure-controlled ventilation (PCV) patients at 4 different baseline PEEP levels (6 to 12 cmH2O), yielding 623 and 294 prediction cases, respectively. Predictions were made up to 12 cmH2O of added PEEP ahead, covering 6 × 2 cmH2O PEEP steps. RESULTS: The 3 basis function sets yield median absolute peak inspiratory pressure (PIP) prediction error of 1.63 cmH2O for VCV patients, and median peak inspiratory volume (PIV) prediction error of 0.028 L for PCV patients. The exponential basis function set yields a better trade-off of overall performance across VCV and PCV prediction than parabolic and cumulative basis function sets from other studies. Comparing predicted and clinically measured distension prediction in VCV demonstrated consistent, robust high accuracy with R2 = 0.90-0.95. CONCLUSIONS: The results demonstrate recruitment mechanics are best captured by an exponential basis function across different mechanical ventilation modes, matching physiological expectations, and accurately capture, for the first time, distension mechanics to within 5-10 % accuracy. Enabling the risk of lung injury to be predicted before changing ventilator settings. The overall outcomes significantly extend and more fully validate this digital twin or virtual mechanical ventilation patient model.

Education of Patients With Atrial Fibrillation and Evaluation of the Efficacy of a Mobile Virtual Patient Environment: Protocol for a Multicenter Pseudorandomized Controlled Trial.

BACKGROUND: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and is a leading cause of mortality and morbidity. Patient knowledge about AF and its management is paramount but often limited. Patients need to be appropriately informed about treatment options, medicinal adherence, and potential consequences of nonadherence, while also understanding treatment goals and expectations from it. Mobile health apps have experienced an explosion both in their availability and acceptance as "soft interventions" for patient engagement and education; however, the prolific nature of such solutions revealed a gap in the evidence base regarding their efficacy and impact. Virtual patients (VPs), interactive computer simulations, have been used as learning activities in modern health care education. VPs demonstrably improved cognitive and behavioral skills; hence, they have been effectively implemented across undergraduate and postgraduate curricula. However, their application in patient education has been rather limited so far. OBJECTIVE: This work aims to implement and evaluate the efficacy of a mobile-deployed VP regimen for the education and engagement of patients with AF on crucial topics regarding their condition. A mobile VP app is being developed with the goal of each VP being a simple scenario with a set goal and very specific messages and will be subsequently attempted and evaluated. METHODS: A mobile VP player app is being developed so as to be used for the design of 3 educational scenarios for AF management. A pseudorandomized controlled trial for the efficacy of VPs is planned to be executed at 3 sites in Greece, Ukraine, and Kazakhstan for patients with AF. The Welch t test will be used to demonstrate the performance of patients' evaluation of the VP experience. RESULTS: Our study is at the development stage. A preliminary study regarding the system's development and feasibility was initiated in December 2022. The results of our study are expected to be available in 2024 or when the needed sample size is achieved. CONCLUSIONS: This study aims to evaluate and demonstrate the first significant evidence for the value of VP resources in outreach and training endeavors for empowering and patients with AF and fostering healthy habits among them. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/45946.

Recommendations for successful virtual patient-assisted esthetic implant rehabilitation: A guide for optimal function and clinical efficiency.

OBJECTIVE: Complete arch implant rehabilitation necessitates meticulous treatment planning and high-level collaboration between surgical and prosthetic dental teams. Emerging virtual technologies hold considerable promise in streamlining this process. The aim of this article is to extend recommendations to clinicians venturing into the virtual patient-assisted esthetic implant rehabilitation workflow. OVERVIEW: This article summarizes recommendations for virtual patient-assisted esthetic implant rehabilitation in the following five aspects: three-dimensional data handling and superimposition, occlusion and virtual articulator integration in creating virtual patients, streamlined face- and prosthetic-driven surgical planning, reuse of presurgical data ("Copy & Paste"), and final impression for passive fitting of final restoration. To illustrate these principles, a case with complete-mouth implant rehabilitation completed within six visits using this virtual patient workflow is presented. CONCLUSION: The virtual patient workflow serves as an invaluable tool to perform treatment planning, enhance efficiency, and ensure predictable outcomes in esthetic complete arch implant rehabilitation. CLINICAL SIGNIFICANCE: Virtual workflows are increasingly prevalent in esthetic implant rehabilitation. Nevertheless, these workflows necessitate a distinct set of knowledge and tools divergent from conventional dentistry practices. This article offers guidelines and recommendations for dental clinicians who are new to this field.

Challenges for Medical Students in Applying Ethical Principles to Allocate Life-Saving Medical Devices During the COVID-19 Pandemic: Content Analysis.

BACKGROUND: The emergence of the COVID-19 pandemic has posed a significant ethical dilemma in the allocation of scarce, life-saving medical equipment to critically ill patients. It remains uncertain whether medical students are equipped to navigate this complex ethical process. OBJECTIVE: This study aimed to assess the ability and confidence of medical students to apply principles of medical ethics in allocating critical medical devices through the scenario of virtual patients. METHODS: The study recruited third- and fourth-year medical students during clinical rotation. We facilitated interactions between medical students and virtual patients experiencing respiratory failure due to COVID-19 infection. We assessed the students' ability to ethically allocate life-saving resources. Subsequently, we analyzed their written reports using thematic analysis to identify the ethical principles guiding their decision-making. RESULTS: We enrolled a cohort of 67 out of 71 medical students with a mean age of 34 (SD 4.7) years, 60% (n=40) of whom were female students. The principle of justice was cited by 73% (n=49) of students while analyzing this scenario. A majority of them expressed hesitancy in determining which patient should receive life-saving resources, with 46% (n=31) citing the principle of nonmaleficence, 31% (n=21) advocating for a first-come-first-served approach, and 25% (n=17) emphasizing respect for patient autonomy as key influencers in their decisions. Notably, medical students exhibited a lack of confidence in making ethical decisions concerning the distribution of medical resources. A minority, comprising 12% (n=8), proposed the exploration of legal alternatives, while 4% (n=3) suggested medical guidelines and collective decision-making as potential substitutes for individual ethical choices to alleviate the stress associated with personal decision-making. CONCLUSIONS: This study highlights the importance of improving ethical reasoning under time constraints using virtual platforms. More than 70% of medical students identified justice as the predominant principle in allocating limited medical resources to critically ill patients. However, they exhibited a lack of confidence in making ethical determinations and leaned toward principles such as nonmaleficence, patient autonomy, adherence to legal and medical standards, and collective decision-making to mitigate the pressure associated with such decisions.

Using Virtual Patients to Assess and Improve Clinicians' Emotional Self-awareness: a Randomized Controlled Study.

OBJECTIVE: Working with suicidal patients can elicit negative emotional responses that can impede clinicians' empathy and affect clinical outcomes. Virtual human interactions represent a promising tool to train clinicians. The present study investigated the impact of virtual human interaction training to enhance clinicians' emotional self-awareness and empathy when working with suicidal patients. METHODS: Clinicians were randomly assigned into two groups. Both groups interviewed a virtual patient presenting with a suicidal crisis; clinicians in the intervention condition (n = 31) received immediate feedback about negative emotional responses and empathic communication, whereas those in the control condition (n = 33) did not receive any feedback. All clinicians interviewed a second virtual patient 1 week later. Clinicians' emotional response to the two virtual patients and their empathic communication with each of them were assessed immediately after each interaction. Linear mixed models were used to assess change in clinicians' emotional response and verbal empathy between the two interactions across conditions. RESULTS: Clinicians' emotional responses toward the suicidal virtual patients were unchanged in both conditions. Clinicians in the intervention condition presenting low empathy level with the first virtual patient showed higher empathy level with the second virtual patient than with the first (B = 1.15, SE = 0.25, p < 0.001, 95% CI [0.42, 1.89]). CONCLUSIONS: This work demonstrates the feasibility of using virtual human interactions to improve empathic communication skills in clinicians with poor empathy skills. Further refinement of this methodology is needed to create effective training modules for a broader array of clinicians.

A digital technique of bone reduction for a maxillary full-arch implant-supported fixed dental prosthesis.

When fabricating a maxillary full-arch implant-supported fixed dental prosthesis, it is often challenging to systematically reduce alveolar bone to create prosthetic space and hide the prosthesis-tissue junction. This article presents a digital technique that allows for precise bone reduction while simultaneously placing implants and interim prostheses. By using this technique, clinicians can perform surgical procedures in a systematic manner without compromising the functional or esthetic outcomes.