Emotion knowledge contributes to emotion regulation and coping among adults, but few studies have investigated its role in children’s coping development, especially in a cross-cultural context. We examine relations between children’s emotion knowledge and coping in European American and Chinese immigrant families. One hundred and three 7- to 10-year-old children and their mothers from European American and Chinese cultural background participated in this study. Children's emotion knowledge was assessed using emotion-situation knowledge production task. This task examines their understanding of situational antecedents o discrete emotions. Children’s use of coping strategies was reported by mothers using the Children’s Coping Strategies Checklist. Results showed that Chinese immigrant children had greater emotion knowledge of fear and pride but were reported using less variety of coping strategies than European American children. The relationship between children’s knowledge of self-conscious emotions and their use of distraction coping strategies was moderated by culture, whereby knowledge of self-conscious emotions was negatively associated with the parent-reported distraction strategies only for European American children but not for Chinese immigrant children. The importance of culture in both theory and practice related to emotion knowledge and coping is discussed. Findings in this study suggest that family intervention and children’s emotion training programs may need to consider children’s cultural background. 相似文献
This paper presents a dynamic tree-based item response (IRTree) model as a novel extension of the autoregressive generalized linear mixed effect model (dynamic GLMM). We illustrate the unique utility of the dynamic IRTree model in its capability of modeling differentiated processes indicated by intensive polytomous time-series eye-tracking data. The dynamic IRTree was inspired by but is distinct from the dynamic GLMM which was previously presented by Cho, Brown-Schmidt, and Lee (Psychometrika 83(3):751–771, 2018). Unlike the dynamic IRTree, the dynamic GLMM is suitable for modeling intensive binary time-series eye-tracking data to identify visual attention to a single interest area over all other possible fixation locations. The dynamic IRTree model is a general modeling framework which can be used to model change processes (trend and autocorrelation) and which allows for decomposing data into various sources of heterogeneity. The dynamic IRTree model was illustrated using an experimental study that employed the visual-world eye-tracking technique. The results of a simulation study showed that parameter recovery of the model was satisfactory and that ignoring trend and autoregressive effects resulted in biased estimates of experimental condition effects in the same conditions found in the empirical study.
