<p>The current paper aimed to estimate the network structure of general psychopathology (internalizing and externalizing symptoms/disorders) among 239 gifted children in Jordan. This cross-sectional study with a convenience sampling method was conducted between September 2023 and October 2024 among gifted children aged 7–12. The Child Behavior Checklist (CBCL) was employed to assess six symptom clusters: conduct problems, attention-deficit/hyperactivity disorder (ADHD), and oppositional defiant problems as externalizing symptoms, and affective problems, anxiety issues, and somatic complaints as internalizing symptoms. We used the network analysis perspective by graphical least absolute shrinkage and selection operator (gLASSO) and the Extended Bayesian Information Criterion (EBIC). These methods were used to determine network structure and important nodes in the estimated network. “Sleeps less” (centrality strength = 2.04, edge weight = 0.33) was the central symptom in the affective cluster. In contrast, “worries” (centrality strength = 1.89, edge weight = 0.28) and “headaches” (centrality strength = 2.35, edge weight = 0.41) were pivotal in the anxiety and somatic clusters, respectively. The findings suggested that these symptoms had critical roles in the context of the general psychopathology among gifted children. Accordingly, the mentioned symptoms should be assessed and targeted among gifted children. Future studies could evaluate the results of targeting these symptoms on gifted children’s well-being and daily functions.</p>

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Network Analysis of Internalizing and Externalizing Symptoms in Arab Gifted Children: A Cross-Sectional Study

  • Ayoub Hamdan Al-Rousan,
  • Mohammad Nayef Ayasrah,
  • Mohamad Ahmad Saleem Khasawneh

摘要

The current paper aimed to estimate the network structure of general psychopathology (internalizing and externalizing symptoms/disorders) among 239 gifted children in Jordan. This cross-sectional study with a convenience sampling method was conducted between September 2023 and October 2024 among gifted children aged 7–12. The Child Behavior Checklist (CBCL) was employed to assess six symptom clusters: conduct problems, attention-deficit/hyperactivity disorder (ADHD), and oppositional defiant problems as externalizing symptoms, and affective problems, anxiety issues, and somatic complaints as internalizing symptoms. We used the network analysis perspective by graphical least absolute shrinkage and selection operator (gLASSO) and the Extended Bayesian Information Criterion (EBIC). These methods were used to determine network structure and important nodes in the estimated network. “Sleeps less” (centrality strength = 2.04, edge weight = 0.33) was the central symptom in the affective cluster. In contrast, “worries” (centrality strength = 1.89, edge weight = 0.28) and “headaches” (centrality strength = 2.35, edge weight = 0.41) were pivotal in the anxiety and somatic clusters, respectively. The findings suggested that these symptoms had critical roles in the context of the general psychopathology among gifted children. Accordingly, the mentioned symptoms should be assessed and targeted among gifted children. Future studies could evaluate the results of targeting these symptoms on gifted children’s well-being and daily functions.