Evidence map›Paper›PMID 39652253›Full record

ArticleJournal of autism and developmental disorders2026

The Impact of Emotion Network Density on Psychological Distress in Chinese Parents of Children with Autism: A Daily Diary Study.

Hui Wang, Jia Julia Yan, Shailey Curtis, Peiyuan Zhao, Xinru Ma, Zhuo Rachel Han, Xiaoyi Hu

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Article in Journal of autism and developmental disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Hui WangDepartment of Psychology, Faculty of Arts and Sciences, Beijing Normal University at Zhuhai, Zhuhai, China.ORCID http://orcid.org/0000-0002-0011-8899
Jia Julia YanDepartment of Child and Family Studies, The University of Tennessee, Knoxville, USA.
Shailey CurtisDepartment of Child and Family Studies, The University of Tennessee, Knoxville, USA.
Peiyuan ZhaoDepartment of Psychology, Faculty of Arts and Sciences, Beijing Normal University at Zhuhai, Zhuhai, China.
Xinru MaDepartment of Psychology, Faculty of Arts and Sciences, Beijing Normal University at Zhuhai, Zhuhai, China.
Zhuo Rachel HanBeijing Key Laboratory of Applied Experimental Psychology, Faculty of Psychology, National Demonstration Center for Experimental Psychology Education, National Virtual Simulation Center for Experimental Psychology Education, Beijing Normal University, Beijing, China.
Xiaoyi HuFaculty of Education, School of Special Education, Education Research Center for Children with ASD, Beijing Normal University, Beijing, China. huxiaoyi@bnu.edu.cn.ORCID http://orcid.org/0000-0002-6936-4799

Funding

Guangdong Province Philosophy and Social Science Planning Project GD24YXL04National Natural Science Foundation of China 32300891
6 · The paper itself

Abstract

Parents of children with autism often experience a wide range of emotions in their daily lives. However, previous research has primarily focused on average levels of emotional challenges, neglecting the significance of daily emotion dynamics that may underlie parental psychological functioning. This study adopted a dynamic network approach to examine the strength of temporal connections within and between various emotions-referred to as emotion network density-and further explore its impacts on parental psychological distress. Participants included 76 Chinese parents (M = 36.36 years, SD = 3.95 years; 58 mothers) of children with autism. Parents reported their psychological distress at baseline and then completed measures of daily emotions over a 14-day period. The densities of overall, positive, and negative emotion networks were estimated using the Multilevel Vector Auto-Regression model. The results indicated that higher densities of the overall and negative emotion networks were associated with increased stress, anxiety, and depressive symptoms in parents. Further analysis of network components showed that the in-strength of fear and guilt (i.e., their likelihood of being affected by other emotions) and the out-strength of anger and guilt (i.e., their capacity to influence other emotions) were positively related to parental psychological distress. However, neither the overall density of the positive emotion network nor its specific components showed a significant relationship with parental psychological distress. These findings highlight the importance of considering the daily dynamics of emotions, particularly negative emotions, from a network perspective to better understand the development of psychological distress in parents of children with autism.

Indexed as

Autistic DisorderEmotionsParentsPsychological DistressStress, PsychologicalAdultAnxietyChildChinaDepressionEast Asian PeopleFemaleHumansMaleMiddle AgedAutism spectrum disorderEmotion dynamicsNetwork densityParental psychological distress

Identifiers

PMID39652253

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.