Suppr超能文献

冲动与抑郁和焦虑症状的关系:一种跨诊断网络分析及复制。

The association of impulsivity with depression and anxiety symptoms: A transdiagnostic network analysis and replication.

机构信息

Department of Military Medical Psychology, Air Force Medical University, Xi'an, China.

Department of Nursing, Air Force Medical University, Xi'an, China.

出版信息

J Affect Disord. 2024 Aug 15;359:100-108. doi: 10.1016/j.jad.2024.05.076. Epub 2024 May 19.

Abstract

BACKGROUND

Impulsivity increases the risk for depression and anxiety. However, the granular pathways among them remain unknown. A network approach that moves from disorder-level analysis to symptom-level analysis can provide further understanding of psychopathological mechanisms. In this study, we examined the network structure of impulsivity and separate and comorbid symptoms of depression and anxiety.

METHODS

Regularized partial-correlation networks were estimated using cross-sectional data from 1047 Chinese participants aged 18-26 years (main dataset, mean age = 21.45 ± 2.01 years) and 325 Chinese participants aged 18-36 years (an independent replication dataset, mean age = 21.49 ± 3.73 years), including impulsivity-depression, impulsivity-anxiety, and impulsivity-depression-anxiety networks. The datasets were collected from 1 June 2023 to 4 August 2023 and from 27 April 2022 to 16 May 2022, respectively. Impulsivity, depression, and anxiety were assessed using Barratt Impulsiveness Scale Version 11, Patient Health Questionnaire-9, and Generalized Anxiety Disorder-7, respectively. Bridge centrality was analyzed, and a network comparison test (NCT) was conducted to investigate the differences between the main dataset and replication dataset.

RESULTS

The motor impulsivity dimension was revealed to be closely connected with individual symptoms of depression and anxiety regardless of whether they were in separate disorder forms or comorbid forms. In all the networks, motor impulsivity was the most important bridge node. The NCT showed comparable network connectivity and network structure between the main and replication datasets.

LIMITATIONS

The use of cross-sectional data limited the inferences about the direction of causality between variables.

CONCLUSIONS

These findings elucidate the psychopathological mechanisms underlying how impulsivity functions within depression, anxiety, and comorbidity and support that motor impulsivity is an important risk factor across different mental disorders and is responsible for comorbidity. The implications of these findings are discussed.

摘要

背景

冲动会增加抑郁和焦虑的风险。然而,它们之间的具体途径尚不清楚。从障碍层面分析到症状层面分析的网络方法可以进一步了解精神病理机制。在这项研究中,我们检验了冲动以及抑郁和焦虑的单独和共病症状的网络结构。

方法

使用来自 1047 名年龄在 18-26 岁的中国参与者(主要数据集,平均年龄=21.45±2.01 岁)和 325 名年龄在 18-36 岁的中国参与者(独立复制数据集,平均年龄=21.49±3.73 岁)的横断面数据,估计了正则化部分相关网络,包括冲动-抑郁、冲动-焦虑和冲动-抑郁-焦虑网络。这些数据集分别于 2023 年 6 月 1 日至 8 月 4 日和 2022 年 4 月 27 日至 5 月 16 日收集。使用巴雷特冲动量表第 11 版、患者健康问卷-9 和广泛性焦虑症-7 分别评估冲动、抑郁和焦虑。分析了桥接中心度,并进行了网络比较测试(NCT),以研究主要数据集和复制数据集之间的差异。

结果

无论是否存在单独的障碍形式或共病形式,运动冲动维度都被发现与抑郁和焦虑的个体症状密切相关。在所有网络中,运动冲动都是最重要的桥接节点。NCT 表明主要和复制数据集之间的网络连接和网络结构具有可比性。

局限性

使用横断面数据限制了对变量之间因果关系方向的推断。

结论

这些发现阐明了冲动在抑郁、焦虑和共病中的作用的精神病理机制,并支持运动冲动是不同精神障碍的重要风险因素,负责共病。讨论了这些发现的意义。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验