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A Network Analysis of ADHD and ASD Symptoms in Chinese Children: Insights on Age and Gender Differences.

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Title: A Network Analysis of ADHD and ASD Symptoms in Chinese Children: Insights on Age and Gender Differences.
Authors: Luo, Jie (AUTHOR), Shao, Wen (AUTHOR), Wu, Yuanzhen (AUTHOR), Huang, Huanhuan (AUTHOR), Xu, Gaoyang (AUTHOR), Qi, Yanjie (AUTHOR), Overton, Paul (AUTHOR), Zheng, Yi (AUTHOR), He, Fan (AUTHOR)
Source: International Journal of Methods in Psychiatric Research. Dec2025, Vol. 34 Issue 4, p1-12. 12p.
Subjects: Attention-deficit hyperactivity disorder, Autism, Mental health surveys, Communication network analysis, Chinese people, Gender differences (Sociology), Age differences
Abstract: Objective: This study aimed to explore the transdiagnostic interactions between ADHD and ASD symptoms in Chinese children, identifying core and bridging symptoms, and examining differences in symptom networks across gender and age subgroups. Method: Using data from a nationwide mental health survey of 71,217 Chinese children (mean age = 11.49, SD = 2.82), a symptom network analysis was conducted. ADHD and ASD symptoms were assessed via the Child Behavior Checklist (CBCL), with ASD items selected from an empirically derived CBCL autism scale. Network estimation was performed using the Glasso algorithm, and community detection was achieved through exploratory graph analysis (EGA). Network comparison tests (NCT) were used to evaluate differences in network structure and connectivity between gender (male vs. female) and age (younger vs. older) subgroups. Results: Inattentive symptoms (I8 "Cannot concentrate," I78 "Inattentive/easily distracted") emerged as central bridging nodes linking ADHD and ASD symptoms. Three stable communities were identified: (1) an inattentive/internalizing cluster reflecting overlapping ADHD‐inattentive and ASD features, (2) a hyperactive/impulsive and immature behavior cluster, and (3) a social withdrawal/low energy cluster representing core ASD features. Females exhibited significantly higher network connectivity than males (global strength: S = 1.05, p = 0.03), with tighter symptom interplay. Older children showed greater ADHD‐ASD symptom overlap, though global strength differences were non‐significant (S = 0.70, p = 0.13). Conclusion: Two inattentive symptoms (I8 and I78) emerged as among the most strongly connected items in the combined ADHD–ASD symptom profile, suggesting that attentional difficulties could play an important role in the psychopathological mechanisms underlying both conditions. Nevertheless, this cross‐sectional finding does not establish causality; longitudinal and intervention studies remain necessary. Screening approaches tailored to gender differences and local cultural context could improve identification of these symptoms in Chinese children and adolescents. The present findings may also guide future refinements in school mental‐health support and related policy development. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Methods in Psychiatric Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: A Network Analysis of ADHD and ASD Symptoms in Chinese Children: Insights on Age and Gender Differences.
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  Data: <searchLink fieldCode="AR" term="%22Luo%2C+Jie%22">Luo, Jie</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shao%2C+Wen%22">Shao, Wen</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wu%2C+Yuanzhen%22">Wu, Yuanzhen</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Huang%2C+Huanhuan%22">Huang, Huanhuan</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xu%2C+Gaoyang%22">Xu, Gaoyang</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Qi%2C+Yanjie%22">Qi, Yanjie</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Overton%2C+Paul%22">Overton, Paul</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zheng%2C+Yi%22">Zheng, Yi</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22He%2C+Fan%22">He, Fan</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Methods+in+Psychiatric+Research%22">International Journal of Methods in Psychiatric Research</searchLink>. Dec2025, Vol. 34 Issue 4, p1-12. 12p.
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  Data: <searchLink fieldCode="DE" term="%22Attention-deficit+hyperactivity+disorder%22">Attention-deficit hyperactivity disorder</searchLink><br /><searchLink fieldCode="DE" term="%22Autism%22">Autism</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+health+surveys%22">Mental health surveys</searchLink><br /><searchLink fieldCode="DE" term="%22Communication+network+analysis%22">Communication network analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Chinese+people%22">Chinese people</searchLink><br /><searchLink fieldCode="DE" term="%22Gender+differences+%28Sociology%29%22">Gender differences (Sociology)</searchLink><br /><searchLink fieldCode="DE" term="%22Age+differences%22">Age differences</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Objective: This study aimed to explore the transdiagnostic interactions between ADHD and ASD symptoms in Chinese children, identifying core and bridging symptoms, and examining differences in symptom networks across gender and age subgroups. Method: Using data from a nationwide mental health survey of 71,217 Chinese children (mean age = 11.49, SD = 2.82), a symptom network analysis was conducted. ADHD and ASD symptoms were assessed via the Child Behavior Checklist (CBCL), with ASD items selected from an empirically derived CBCL autism scale. Network estimation was performed using the Glasso algorithm, and community detection was achieved through exploratory graph analysis (EGA). Network comparison tests (NCT) were used to evaluate differences in network structure and connectivity between gender (male vs. female) and age (younger vs. older) subgroups. Results: Inattentive symptoms (I8 "Cannot concentrate," I78 "Inattentive/easily distracted") emerged as central bridging nodes linking ADHD and ASD symptoms. Three stable communities were identified: (1) an inattentive/internalizing cluster reflecting overlapping ADHD‐inattentive and ASD features, (2) a hyperactive/impulsive and immature behavior cluster, and (3) a social withdrawal/low energy cluster representing core ASD features. Females exhibited significantly higher network connectivity than males (global strength: S = 1.05, p = 0.03), with tighter symptom interplay. Older children showed greater ADHD‐ASD symptom overlap, though global strength differences were non‐significant (S = 0.70, p = 0.13). Conclusion: Two inattentive symptoms (I8 and I78) emerged as among the most strongly connected items in the combined ADHD–ASD symptom profile, suggesting that attentional difficulties could play an important role in the psychopathological mechanisms underlying both conditions. Nevertheless, this cross‐sectional finding does not establish causality; longitudinal and intervention studies remain necessary. Screening approaches tailored to gender differences and local cultural context could improve identification of these symptoms in Chinese children and adolescents. The present findings may also guide future refinements in school mental‐health support and related policy development. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Methods in Psychiatric Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1002/mpr.70042
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        Text: English
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        PageCount: 12
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    Subjects:
      – SubjectFull: Attention-deficit hyperactivity disorder
        Type: general
      – SubjectFull: Autism
        Type: general
      – SubjectFull: Mental health surveys
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      – SubjectFull: Communication network analysis
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      – SubjectFull: Chinese people
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      – SubjectFull: Gender differences (Sociology)
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      – SubjectFull: Age differences
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              Text: Dec2025
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              Y: 2025
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