Objectives To assess advanced communication skills among second-year medical students exposed either to a computer simulation (MPathic-VR) featuring virtual humans, or to a multimedia computer-based learning module, and to understand each group’s experiences and learning preferences. Methods A single-blinded, mixed methods, randomized, multisite trial compared MPathic-VR (N=210) to computer-based learning (N=211). Primary outcomes: communication scores during repeat interactions with MPathic-VR’s intercultural and interprofessional communication scenarios and scores on a subsequent advanced communication skills objective structured clinical examination (OSCE). Multivariate analysis of variance was used to compare outcomes. Secondary outcomes: student attitude surveys and qualitative assessments of their experiences with MPathic-VR or computer-based learning. Results MPathic-VR-trained students improved their intercultural and interprofessional communication performance between their first and second interactions with each scenario. They also achieved significantly higher composite scores on the OSCE than computer-based learning-trained students. Attitudes and experiences were more positive among students trained with MPathic-VR, who valued its providing immediate feedback, teaching nonverbal communication skills, and preparing them for emotion-charged patient encounters. Conclusions MPathic-VR was effective in training advanced communication skills and in enabling knowledge transfer into a more realistic clinical situation. Practice Implications MPathic-VR’s virtual human simulation offers an effective and engaging means of advanced communication training.

This paper examines the feasibility of using artificial neural networks (ANNs) and genetic algorithms (GAs) to develop discrete time dynamic models for fault free and faulted switchedreluctance-motor (SRM) drive systems. The results of using the ANN-GA-based (neurogenetic) model to predict the performance characteristics of prototype SRM drive motor under normal and abnormal operating conditions are presented and verified by comparison to test data.

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