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Purpose Teamwork in surgery depends on a shared mental model of success, i.e., a common understanding of objectives in the operating room. A shared model leads to increased engagement among team members and is associated with fewer complications and overall better outcomes for patients. However, clinical training typically focuses on role-specific skills, leaving individuals to acquire a shared model indirectly through on-the-job experience. Methods We investigate whether virtual reality (VR) cross-training, i.e, exposure to other roles, can enhance a shared mental model for non-surgeons more directly. Our study focuses on X-ray guided pelvic trauma surgery, a procedure where successful communication depends on the shared model between the surgeon and a C-arm technologist. We present a VR environment supporting both roles and evaluate a cross-training curriculum in which non-surgeons swap roles with the surgeon. Results Exposure to the surgical task resulted in higher engagement with the C-arm technologist role in VR, as measured by the mental demand and effort expended by participants. It also has a significant effect on non-surgeon’s mental model of the overall task; novice participants’ estimation of the mental demand and effort required for the surgeon’s task increases after training, while their perception of overall performance decreases, indicating a gap in understanding based solely on observation. This phenomenon was also present for a professional C-arm technologist. Conclusion Until now, VR applications for clinical training have focused on virtualizing existing curricula. We demonstrate how novel approaches which are not possible outside of a virtual environment, such as role swapping, may enhance the shared mental model of surgical teams by contextualizing each individual’s role within the overall task in a time- and cost-efficient manner. As workflows grow increasingly sophisticated, we see VR curricula as being able to directly foster a shared model for success, ultimately benefiting patient outcomes through more effective teamwork in surgery.more » « less
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Jiang, Baichuan; Wang, Liam; Xu, Keshuai; Hossbach, Martin; Demir, Alican; Rajan, Purnima; Taylor, Russell H; Moghekar, Abhay; Foroughi, Pezhman; Kazanzides, Peter; et al (, IEEE Transactions on Medical Robotics and Bionics)
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Pryor, Will; Wang, Liam J.; Chatterjee, Arko; Vagvolgyi, Balazs P.; Deguet, Anton; Leonard, Simon; Whitcomb, Louis L.; Kazanzides, Peter (, IEEE)
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