Simulation in healthcare : journal of the Society for Simulation in Healthcare
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Randomized Controlled Trial
Simulation training improves medical students' learning experiences when performing real vaginal deliveries.
To determine the relationship between simulation training for vaginal delivery maneuvers and subsequent participation in live deliveries during the clinical rotation and to assess medical students' performance and confidence in vaginal delivery maneuvers with and without simulation training. ⋯ Students who receive simulation training participate more actively in the clinical environment during the course of the clerkship. Student simulation training is beneficial to learn obstetric skills in a minimal risk environment, demonstrate competency with maneuvers, and translate this competence into increased clinical participation and confidence.
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Comparative Study
The effect of high-fidelity simulation on educational outcomes in an advanced cardiovascular life support course.
The use of high-fidelity simulation has been studied in many healthcare education areas. However, the use of this instructional technology in the American Heart Association (AHA) Advanced Cardiovascular Life Support (ACLS) course has not been extensively reported, despite this program being one of the most widely taught standardized medical courses in the United States. ⋯ Expert raters judged students in a high-fidelity simulation-based AHA ACLS course as more competent than students in a low-fidelity course. On item level analysis, items focused on manual tasks or actions in the first 1 to 2 minutes of the cardiac arrest event were more likely to be nonsignificant. As the scenario grew longer and more complex, expert rater scores of the high-fidelity trained team leaders' confidence, knowledge, and treatment decisions were higher than the low-fidelity team leaders' score at a statistically significant level.
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Photorealistic simulations may provide efficient transfer of certain skills to the real system, but by being opaque may fail to encourage deeper learning of the structure and function of the system. Schematic simulations that are more abstract, with less visual fidelity but make system structure and function transparent, may enhance deeper learning and optimize retention and transfer of learning. We compared learning effectiveness of these 2 modes of externalizing the output of a common simulation engine (the Virtual Anesthesia Machine, VAM) that models machine function and dynamics and responds in real time to user interventions such as changes in gas flow or ventilation. ⋯ Schematic simulations that transparently allow learners to visualize, and explore, underlying system dynamics and relations among components may provide a more effective mental model for certain systems. This may lead to a deeper understanding of how the system works, and therefore, we believe, how to detect and respond to potentially adverse situations.
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Prompt and successful cardiopulmonary resuscitation during a sudden cardiac arrest can be hindered by multiple variables, ie, ineffective communication, stress, lack of training, and an unfamiliar environment, such as a new hospital facility. The main objective of the study was to use high-fidelity simulations to orient Code Blue Teams (CBTs) to critical events in a new hospital facility. A secondary objective was to elucidate factors that may have contributed to responses by debriefing teams. ⋯ Clinical simulation can be effectively used to orient CBTs and identify critical safety issues in a newly constructed healthcare facility.