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利用网络分析识别青少年抑郁症的核心症状。

Using Network Analysis to Identify Central Symptoms of Adolescent Depression.

机构信息

a Department of Psychology , University of Texas at Austin.

b Department of Experimental-Clinical and Health Psychology , Ghent University.

出版信息

J Clin Child Adolesc Psychol. 2019 Jul-Aug;48(4):656-668. doi: 10.1080/15374416.2018.1437735. Epub 2018 Mar 13.

Abstract

Experiencing depression symptoms, even at mild to moderate levels, is associated with maladaptive outcomes for adolescents. We used network analysis to evaluate which symptoms (and associations between symptoms) are most central to adolescent depression. Participants were part of a large, diverse community sample ( = 1,409) of adolescents between 13 and 19 years of age. Network analysis was used to identify the most central symptoms (nodes) and associations between symptoms (edges) assessed by the Children's Depression Inventory. We also evaluated these centrality indicators for network robustness using stability and accuracy tests, associated symptom centrality with mean levels of symptoms, and examined potential differences between the structure and connectivity of depression networks in boys and girls. The most central symptoms in the network were self-hatred, loneliness, sadness, and pessimism. The strongest associations between symptoms were sadness-crying, anhedonia-school dislike, sadness-loneliness, school work difficulty-school performance decrement, self-hatred-negative body image, sleep disturbance-fatigue, and self-deprecation-self-blame. The network was robust to stability and accuracy tests. Notably, symptom centrality and mean levels of symptoms were not associated. Boys and girls' networks did not differ in levels of connectivity, though the link between body image and self-hatred was stronger in girls than boys. Self-hatred, loneliness, sadness, and pessimism were the most central symptoms in adolescent depression networks, suggesting that these symptoms (and associations between symptoms) should be prioritized in theoretical models of adolescent depression and could also serve as important treatment targets for adolescent depression interventions.

摘要

经历抑郁症状,即使是轻度到中度的抑郁症状,也与青少年的适应不良结果有关。我们使用网络分析来评估哪些症状(以及症状之间的关联)对青少年抑郁最为重要。参与者是一个由年龄在 13 至 19 岁之间的青少年组成的大型、多样化社区样本(n=1409)的一部分。网络分析用于识别由儿童抑郁量表评估的最中心症状(节点)和症状之间的关联(边缘)。我们还使用稳定性和准确性测试评估了这些网络中心性指标,评估了症状中心性与症状平均水平之间的关系,并检查了男孩和女孩抑郁网络结构和连接性的潜在差异。网络中最中心的症状是自我仇恨、孤独、悲伤和悲观。症状之间最强的关联是悲伤-哭泣、快感缺乏-不喜欢学校、悲伤-孤独、学业困难-学业成绩下降、自我仇恨-负面身体形象、睡眠障碍-疲劳、自贬-自责。该网络对稳定性和准确性测试具有鲁棒性。值得注意的是,症状中心性和症状平均水平之间没有关联。男孩和女孩的网络在连接水平上没有差异,尽管身体形象和自我仇恨之间的联系在女孩中比男孩更强。自我仇恨、孤独、悲伤和悲观是青少年抑郁网络中最中心的症状,这表明这些症状(以及症状之间的关联)应该在青少年抑郁的理论模型中优先考虑,也可以作为青少年抑郁干预的重要治疗目标。

相似文献

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Using Network Analysis to Identify Central Symptoms of Adolescent Depression.利用网络分析识别青少年抑郁症的核心症状。
J Clin Child Adolesc Psychol. 2019 Jul-Aug;48(4):656-668. doi: 10.1080/15374416.2018.1437735. Epub 2018 Mar 13.

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