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      The validation of a Mandarin version of the Empathy Components Questionnaire (ECQ-Chinese) in Chinese samples

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          Abstract

          Empathy involves both empathic ability and empathic motivation. An important topic has been how to measure empathic ability and motivation simultaneously in both clinical and non-clinical samples and across different cultures. The Empathy Components Questionnaire (ECQ) is a self-report questionnaire that measures empathic ability and motivation in a questionnaire. The current study aimed to validate the Mandarin Chinese version of the ECQ (ECQ-Chinese) in three Chinese samples. In study 1, a total of 538 Chinese participants (Sample 1) completed the ECQ-Chinese via an online survey, and existing measures of empathy and related constructs which were used for criterion validity. In study 2, a total of 104 participants (Sample 2) were recruited again from sample 1 and completed the ECQ-Chinese three weeks later to investigate test-retest reliability. In study 3, a further 324 participants (Sample 3) completed the ECQ-Chinese for confirmatory factor analysis. The results showed that the ECQ-Chinese has a good internal consistency reliability, split-half reliability, and criterion validity (Study 1), and a good test-retest reliability (Study 2). Further, Study 3 found that a 22-item ECQ-Chinese consisting of five subscales had a good construct validity, convergence validity and discriminate validity, demonstrating it to be a suitable tool for the measurement of empathic ability and motivation in Chinese samples and to carry out cross-cultural studies of empathy and its components.

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          Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives

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            Measuring individual differences in empathy: Evidence for a multidimensional approach.

            Mark Davis (1983)
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              The functional architecture of human empathy.

              Empathy accounts for the naturally occurring subjective experience of similarity between the feelings expressed by self and others without loosing sight of whose feelings belong to whom. Empathy involves not only the affective experience of the other person's actual or inferred emotional state but also some minimal recognition and understanding of another's emotional state. In light of multiple levels of analysis ranging from developmental psychology, social psychology, cognitive neuroscience, and clinical neuropsychology, this article proposes a model of empathy that involves parallel and distributed processing in a number of dissociable computational mechanisms. Shared neural representations, self-awareness, mental flexibility, and emotion regulation constitute the basic macrocomponents of empathy, which are underpinned by specific neural systems. This functional model may be used to make specific predictions about the various empathy deficits that can be encountered in different forms of social and neurological disorders.
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                Author and article information

                Contributors
                Role: Writing – original draft
                Role: Writing – review & editing
                Role: Data curationRole: Supervision
                Role: Data curation
                Role: Data curation
                Role: Data curation
                Role: Data curation
                Role: Conceptualization
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                26 January 2023
                2023
                : 18
                : 1
                : e0275903
                Affiliations
                [1 ] Department of Psychology, Zhejiang Normal University, Jinhua, China
                [2 ] Institute of Child Development, Jinhua Polytechnic, Jinhua, China
                [3 ] Centre for Applied Autism Research, Department of Psychology, University of Bath, Bath, United Kingdom
                [4 ] Publicity Department, Zhejiang Normal University, Jinhua, China
                [5 ] College of Mathematics and Computer Science, Zhejiang Normal University, Jinhua, China
                Lorestan University, ISLAMIC REPUBLIC OF IRAN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0001-5062-2615
                Article
                PONE-D-22-16459
                10.1371/journal.pone.0275903
                9879452
                36701341
                1a6f7948-89f4-4c7c-b01d-5d9b085c2820
                © 2023 Ge et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 8 June 2022
                : 25 September 2022
                Page count
                Figures: 2, Tables: 4, Pages: 17
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 31871124
                Award Recipient :
                This work was supported by the National Natural Science Foundation of China (No. 31871124).
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                Data relevant to this study are available from OSF at osf.io/5cd7q.

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