Al-Rousan Ayoub Hamdan, Ayasrah Mohammad Nayef, Khasawneh Mohamad Ahmad Saleem
Educational psychology, The Hashemite University, Queen Rania Faculty for Childhood, Early Childhood Department, Zarqa, Jordan.
Special Education, Al Balqa Applied University, Department of Educational Science, Irbid University College, Irbid, Jordan.
Psychiatr Q. 2025 Mar;96(1):117-132. doi: 10.1007/s11126-025-10112-2. Epub 2025 Jan 14.
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.
本论文旨在评估约旦239名天才儿童的一般精神病理学（内化和外化症状/障碍）的网络结构。本横断面研究采用便利抽样方法，于2023年9月至2024年10月期间对7至12岁的天才儿童进行。使用儿童行为检查表（CBCL）评估六个症状群：作为外化症状的品行问题、注意力缺陷/多动障碍（ADHD）和对立违抗问题，以及作为内化症状的情感问题、焦虑问题和躯体主诉。我们通过图形最小绝对收缩和选择算子（gLASSO）和扩展贝叶斯信息准则（EBIC）从网络分析的角度进行研究。这些方法用于确定网络结构和估计网络中的重要节点。“睡眠少”（中心性强度 = 2.04，边权重 = 0.33）是情感群中的核心症状。相比之下，“担忧”（中心性强度 = 1.89，边权重 = 0.28）和“头痛”（中心性强度 = 2.35，边权重 = 0.41）分别在焦虑群和躯体群中起关键作用。研究结果表明，这些症状在天才儿童的一般精神病理学背景中具有关键作用。因此，应在天才儿童中对上述症状进行评估和针对性处理。未来的研究可以评估针对这些症状对天才儿童的幸福感和日常功能的影响结果。
