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哪个先来?抑郁和焦虑症状共病:交叉滞后网络分析。

Which comes first? Comorbidity of depression and anxiety symptoms: A cross-lagged network analysis.

机构信息

Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, 510631, Guangzhou, China; Center for studies of Psychological Application, School of Psychology, South China Normal University, 510631, Guangzhou, China.

Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, 510631, Guangzhou, China; Institute for Brain Research and Rehabilitation, South China Normal University, 510631, Guangzhou, China.

出版信息

Soc Sci Med. 2024 Nov;360:117339. doi: 10.1016/j.socscimed.2024.117339. Epub 2024 Sep 11.

Abstract

Depression and anxiety significantly impact college students, leading to various negative outcomes. While numerous studies have investigated the relationship between these two conditions, their temporal sequence remains unresolved. Many previous studies have concentrated on broad latent variables, often neglecting the nuanced symptomatology perspective, which may offer deeper insight into the clinical characteristics of these disorders. In this study, we collected questionnaire data from a college in South China using a cluster random sampling method. Data collection occurred over two time points, with the first round completed in November 2022 and May 2023, with a six-month interval. A total of 689 participants successfully completed the questionnaires during both rounds. Employing cross-lagged network analysis from a symptom-focused perspective, this research examines the interactions and predictive relationships between symptoms of depression and anxiety. The findings identified key symptoms-specifically "Irritability", "Guilty" and "Sad mood"- as critical bridging nodes of connection within the depression and anxiety symptom network. Our analysis revealed both bidirectional predictive relationships between certain symptoms nodes of depression and anxiety, as well as unidirectional ones. By highlighting these core nodes and their directional relationships, this study offers valuable insights that can inform targeted intervention and treatment strategies for enhancing mental health among college students.

摘要

抑郁和焦虑会对大学生产生重大影响,导致各种负面结果。虽然许多研究已经调查了这两种情况之间的关系,但它们的时间顺序仍未得到解决。许多以前的研究都集中在广泛的潜在变量上,往往忽略了细微的症状学观点,这可能为这些障碍的临床特征提供更深入的了解。在这项研究中,我们使用聚类随机抽样方法从华南的一所大学收集了问卷数据。数据收集在两个时间点进行,第一轮于 2022 年 11 月和 2023 年 5 月完成,间隔六个月。共有 689 名参与者在两轮都成功完成了问卷。本研究从症状角度采用交叉滞后网络分析,考察了抑郁和焦虑症状之间的相互作用和预测关系。研究结果确定了关键症状——“易怒”、“内疚”和“悲伤情绪”——作为抑郁和焦虑症状网络中关键的连接节点。我们的分析揭示了某些抑郁和焦虑症状节点之间的双向预测关系,以及单向预测关系。通过突出这些核心节点及其方向关系,本研究提供了有价值的见解,可以为增强大学生心理健康提供有针对性的干预和治疗策略。

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