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Knowledge Gain and the Impact of Stress in a Fully Immersive Virtual Reality–Based Medical Emergencies Training With Automated Feedback: Randomized Controlled Trial

Knowledge Gain and the Impact of Stress in a Fully Immersive Virtual Reality–Based Medical Emergencies Training With Automated Feedback: Randomized Controlled Trial

Both physiological stress markers can be recorded by wearable sensors (eg, wristbands), causing minimal or no disruption to the simulation [24,25]. To evaluate objectively the learning outcomes of self-moderated VR-based emergency training with automated feedback and simultaneously to gain insight into the impact of different stress dimensions on the learning process, we aimed to answer the following questions.

Marco Lindner, Tobias Leutritz, Joy Backhaus, Sarah König, Tobias Mühling

J Med Internet Res 2025;27:e67412

Mono-Professional Simulation-Based Obstetric Training in a Low-Resource Setting: Stepped-Wedge Cluster Randomized Trial

Mono-Professional Simulation-Based Obstetric Training in a Low-Resource Setting: Stepped-Wedge Cluster Randomized Trial

Additional challenges, such as resource constraints, difficulties in sustaining training programs, staff shortages, and high turnover rates, further hinder the implementation and long-term impact of simulation-based training in sub-Saharan Africa. To overcome these challenges, high-quality research is essential to determine the most effective methodologies for emergency obstetric simulation-based training in sub-Saharan Africa.

Anne A C van Tetering, Ella L de Vries, Peter Ntuyo, E R van den Heuvel, Annemarie F Fransen, M Beatrijs van der Hout-van der Jagt, Imelda Namagembe, Josaphat Byamugisha, S Guid Oei

JMIR Med Educ 2025;11:e54911

Immersive Virtual Reality and AI (Generative Pretrained Transformer) to Enhance Student Preparedness for Objective Structured Clinical Examinations: Mixed Methods Study

Immersive Virtual Reality and AI (Generative Pretrained Transformer) to Enhance Student Preparedness for Objective Structured Clinical Examinations: Mixed Methods Study

This investigation used an improved VR simulation featuring the use of AI, which allowed the virtual patient to provide dynamic responses to student questions. This investigation also included qualitative components—semistructured interviews and focus groups were used to obtain student perspectives regarding their experiences with their first-year coursework and the VR simulation.

Shaniff Esmail, Brendan Concannon

JMIR Serious Games 2025;13:e69428

Impact of a 3-Month Recall Using High-Fidelity Simulation or Screen-Based Simulation on Learning Retention During Neonatal Resuscitation Training for Residents in Anesthesia and Intensive Care: Randomized Controlled Trial

Impact of a 3-Month Recall Using High-Fidelity Simulation or Screen-Based Simulation on Learning Retention During Neonatal Resuscitation Training for Residents in Anesthesia and Intensive Care: Randomized Controlled Trial

The objective of our study is to analyze the retention of knowledge and skills at 6 months after an initial training in neonatal resuscitation for anesthesia and intensive care residents, with or without a 3-month recall training session using either screen-based simulation or high-fidelity (HF) simulation. This randomized controlled simulation study was conducted from February 2021 to November 2021 at the University Hospital of Reims, France.

Anne-Claire Louvel, Cécile Dopff, Gauthier Loron, Daphne Michelet

JMIR Serious Games 2025;13:e57057

Demonstrating Tactical Combat Casualty Care in Simulated Environments to Enable Passive, Autonomous Documentation: Protocol for a Prospective Simulation-Based Study

Demonstrating Tactical Combat Casualty Care in Simulated Environments to Enable Passive, Autonomous Documentation: Protocol for a Prospective Simulation-Based Study

From the beginning of the scenario brief to after action reporting, each participant will be engaged in the study for a maximum of 2.5 hours, where 50 minutes is the maximum amount of time a participant can participate in a simulation run. Autonomous documentation flow diagram from simulation data collection to algorithm development. TATRC: Telemedicine & Advanced Technology Research Center.

Jeanette R Little, Triana Rivera-Nichols, Holly H Pavliscsak, Omar Badawi, James C Gaudaen, Chevas R Yeoman, Todd S Hall, Ethan T Quist, Ericka L Stoor-Burning

JMIR Res Protoc 2025;14:e67673

Evaluation of a Simulation Program for Providing Telenursing Training to Nursing Students: Cohort Study

Evaluation of a Simulation Program for Providing Telenursing Training to Nursing Students: Cohort Study

This study evaluates the skills and knowledge of third-year nursing students regarding remote nursing care before and after participation in a simulation-based training program on telenursing as part of their undergraduate nursing degree. To the best of our knowledge, very few studies to date have evaluated programs that use simulation to train nursing students in the provision of nursing care from a distance (telenursing). This study tests 3 hypotheses.

Ola Ali-Saleh, Layalleh Massalha, Ofra Halperin

JMIR Med Educ 2025;11:e67804

Exploring the Role of Immersive Virtual Reality Simulation in Health Professions Education: Thematic Analysis

Exploring the Role of Immersive Virtual Reality Simulation in Health Professions Education: Thematic Analysis

As technology rapidly advances in immersive virtual reality (VR) simulation, there is a growing interest among educators to develop VR simulation curricula for health professions education. However, there is a paucity of literature to guide these efforts, and there are no accepted best practices for the development or implementation of this technology.

Jordan Talan, Molly Forster, Leian Joseph, Deepak Pradhan

JMIR Med Educ 2025;11:e62803