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绘制抑郁症患者网络成瘾与残留抑郁症状之间的网络连通性

Mapping network connectivity between internet addiction and residual depressive symptoms in patients with depression.

作者信息

Cai Hong, Bai Wei, Yue Yan, Zhang Ling, Mi Wen-Fang, Li Yu-Chen, Liu Huan-Zhong, Du Xiangdong, Zeng Zhen-Tao, Lu Chang-Mou, Zhang Lan, Feng Ke-Xin, Ding Yan-Hong, Yang Juan-Juan, Jackson Todd, Cheung Teris, An Feng-Rong, Xiang Yu-Tao

机构信息

Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao, Macao SAR, China.

Centre for Cognitive and Brain Sciences, University of Macau, Macao, Macao SAR, China.

出版信息

Front Psychiatry. 2022 Oct 24;13:997593. doi: 10.3389/fpsyt.2022.997593. eCollection 2022.

Abstract

BACKGROUND AND AIMS

Depression often triggers addictive behaviors such as Internet addiction. In this network analysis study, we assessed the association between Internet addiction and residual depressive symptoms in patients suffering from clinically stable recurrent depressive disorder (depression hereafter).

MATERIALS AND METHODS

In total, 1,267 depressed patients were included. Internet addiction and residual depressive symptoms were measured using the Internet Addiction Test (IAT) and the two-item Patient Health Questionnaire (PHQ-2), respectively. Central symptoms and bridge symptoms were identified via centrality indices. Network stability was examined using the case-dropping procedure.

RESULTS

The prevalence of IA within this sample was 27.2% (95% CI: 24.7-29.6%) based on the IAT cutoff of 50. IAT15 ("Preoccupation with the Internet"), IAT13 ("Snap or act annoyed if bothered without being online") and IAT2 ("Neglect chores to spend more time online") were the most central nodes in the network model. Additionally, bridge symptoms included the node PHQ1 ("Anhedonia"), followed by PHQ2 ("Sad mood") and IAT3 ("Prefer the excitement online to the time with others"). There was no gender difference in the network structure.

CONCLUSION

Both key central and bridge symptoms found in the network analysis could be potentially targeted in prevention and treatment for depressed patients with comorbid Internet addiction and residual depressive symptoms.

摘要

背景与目的

抑郁症常引发成瘾行为,如网络成瘾。在这项网络分析研究中,我们评估了临床稳定的复发性抑郁症患者(以下简称抑郁症患者)的网络成瘾与残留抑郁症状之间的关联。

材料与方法

总共纳入了1267名抑郁症患者。分别使用网络成瘾测试(IAT)和两项患者健康问卷(PHQ - 2)来测量网络成瘾和残留抑郁症状。通过中心性指标确定核心症状和桥梁症状。使用剔除病例法检查网络稳定性。

结果

根据IAT临界值50,该样本中网络成瘾的患病率为27.2%(95%CI:24.7 - 29.6%)。IAT15(“沉迷于网络”)、IAT13(“如果不在线时被打扰会突然发怒或表现烦躁”)和IAT2(“为花更多时间上网而忽视家务”)是网络模型中最核心的节点。此外,桥梁症状包括节点PHQ1(“快感缺失”),其次是PHQ2(“情绪低落”)和IAT3(“比起与他人相处,更喜欢网上的刺激”)。网络结构不存在性别差异。

结论

网络分析中发现的关键核心症状和桥梁症状都可能成为预防和治疗合并网络成瘾及残留抑郁症状的抑郁症患者的潜在靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7bd/9638086/34cc1f3c093a/fpsyt-13-997593-g001.jpg

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