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Micro-expressions are brief facial expressions that last for 500 milliseconds or less and show the true emotional state of an individual when he or she is displaying a false emotional state. There are currently 2 different methods to train individuals to recognize micro-expressions-picture-based and video-based. Numerous organizations use micro-expression training as part of a deception detection program, but little research has been conducted on training outcomes, and no research has investigated the difference between the methods. In this quantitative study based on Darwin's theory of the universality of emotional expression, a control group experimental design was used to determine if there is a difference in training outcomes, as measured by post-training accuracy rates of overall and emotion-specific micro-expression identification, between the 2 current micro-expression training methods and no training. A total of 196 participants recruited from Amazon's Mechanical Turk community were randomly assigned to a picture-based training, video-based training, or no training control group. The online training and post-training test were delivered via a computer-based training platform. MANOVA, ANOVA and t-tests were run to determine the differences between the groups. Results indicated that participants in both picture-based and video-based training groups showed a significant increase in their ability to recognize micro-expressions compared to those in the no training group, but did not differ from each other. The study provides an increased understanding of micro-expression training outcomes that may contribute to the training of numerous law enforcement, security, and human resources professionals.
Kane, Matthew Patrick, "A Comparison of Micro-Expression Training Methods" (2018). Walden Dissertations and Doctoral Studies. 5885.