@article{halberstadt_cooke_hagan_liu_2021, title={PerCEIVED: Perceptions of Children's Emotions in Videos, Evolving and Dynamic Task}, ISSN={["1931-1516"]}, DOI={10.1037/emo0001019}, abstractNote={Researchers have been studying emotion recognition skill for over 100 years (Feleky, 1914), yet technological advances continue to allow for the creation of better measures. Interest in consistent inaccuracies (sometimes described as bias) has also emerged recently. To support research in both emotion recognition skill and bias, we first describe all extant measures of emotion recognition with child actors that we have found, evaluating strengths and constraints of these measures. We then introduce a new measure of emotion understanding (Perceptions of Children's Emotions in Videos, Evolving and Dynamic task) that includes assessment of six emotions portrayed dynamically over rounds by 72 child actors, balancing child race and gender within each emotion, and certified by Facial Action Coding System coders. We provide participant accuracy and bias rates by round and within emotion, based on results from four studies (N = 477 adult participants), and report evidence for reliability over time, criterion and discriminant validity, and multidimensionality of emotion recognition from these studies. We conclude with potential uses of the measure in terms of assessing the accuracy and inaccuracies of participants, including opportunities for the study of developmental processes, individual differences, and confusions between various emotions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).}, journal={EMOTION}, author={Halberstadt, Amy G. and Cooke, Alison N. and Hagan, Courtney A. and Liu, Xi}, year={2021}, month={Sep} }