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大学生样本中焦虑、抑郁和心理韧性之间的复杂关联:一项网络分析

Complex associations between anxiety, depression, and resilience in a college student sample: a network analysis.

作者信息

Wang Hui, Wang Min, Wang Xiuchao, Feng Tingwei, Liu Xufeng, Xiao Wei

机构信息

Department of Military Medical Psychology, Air Force Military Medical University, Shanxi, China.

Sleep Psychosomatic Department, Leshan Traditional Chinese Medicine Hospital, Leshan, China.

出版信息

Front Psychiatry. 2025 May 14;16:1502252. doi: 10.3389/fpsyt.2025.1502252. eCollection 2025.

Abstract

BACKGROUND

Anxiety and depression have significant impacts on individuals' mental health and social functioning, particularly among college students. Psychological resilience is considered a crucial resource for coping with adversity and stress and may play a key role in alleviating anxiety and depression symptoms. The aim of this study is to explore the finer-grained potential relationships between psychological resilience, anxiety, and depression among college students.

METHODS

This study employed network analysis to examine the psychological resilience, anxiety, and depression status of a randomly sampled cohort of 855 college students (51.8% female; M = 18.70, SD = 1.13). Statistical analyses and network visualization were conducted using R version 4.2.2 and the qgraph package. Bridge centrality indices of variables within the network were computed, with particular emphasis on the significance of bridge symptoms within the network structure.

RESULTS

Significant covariation was observed between anxiety and depression symptoms. Psychological resilience exhibited a negative correlation with both anxiety and depression, with a negative bridge expected influence value for R10 "Can handle unpleasant feelings", indicating a potential protective role of psychological resilience in mitigating these mental health issues. R10 "Can handle unpleasant feelings" occupies the most central position within the psychological resilience network, with the smallest BEI value (-0.01), indicating its protective role in the overall network. To some extent, it can regulate anxiety and depression symptoms.

CONCLUSION

This study highlights the complex interrelationships between psychological resilience, anxiety, and depression among college students through network analysis. Bridge expected influence analysis identified "R10" as a protective factor and "A7" as a key risk factor. The findings suggest that interventions targeting bridge symptoms and enhancing resilience may help alleviate anxiety and depression. Prioritizing these two symptoms in future research could yield greater intervention benefits.

摘要

背景

焦虑和抑郁对个体的心理健康和社会功能有重大影响,在大学生中尤为如此。心理韧性被认为是应对逆境和压力的关键资源,可能在减轻焦虑和抑郁症状方面发挥关键作用。本研究的目的是探讨大学生心理韧性、焦虑和抑郁之间更细粒度的潜在关系。

方法

本研究采用网络分析方法,对855名随机抽样的大学生(51.8%为女性;平均年龄M = 18.70,标准差SD = 1.13)的心理韧性、焦虑和抑郁状况进行了研究。使用R版本4.2.2和qgraph软件包进行统计分析和网络可视化。计算了网络中变量的桥梁中心性指数,特别强调了网络结构中桥梁症状的重要性。

结果

观察到焦虑和抑郁症状之间存在显著的共变关系。心理韧性与焦虑和抑郁均呈负相关,“R10:能够处理不愉快的情绪”的负向桥梁预期影响值表明心理韧性在减轻这些心理健康问题方面具有潜在的保护作用。“R10:能够处理不愉快的情绪”在心理韧性网络中占据最中心的位置,桥梁预期影响值(BEI)最小(-0.01),表明其在整个网络中的保护作用。在一定程度上,它可以调节焦虑和抑郁症状。

结论

本研究通过网络分析突出了大学生心理韧性、焦虑和抑郁之间的复杂相互关系。桥梁预期影响分析确定“R10”为保护因素,“A7”为关键风险因素。研究结果表明,针对桥梁症状并增强心理韧性的干预措施可能有助于减轻焦虑和抑郁。在未来的研究中优先考虑这两种症状可能会产生更大的干预效益。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23d8/12117827/a385a4af0aca/fpsyt-16-1502252-g001.jpg

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