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ORIGINAL RESEARCH article
Front. Psychiatry
Sec. Public Mental Health
Volume 16 - 2025 | doi: 10.3389/fpsyt.2025.1502252
Complex associations between anxiety, depression, and resilience in a college student sample: A network analysis
Provisionally accepted- 1 Air Force Medical University, Xi'an, China
- 2 Department of Spleen and Gastroenterology, Leshan Traditional Chinese Medicine Hospital, Leshan, China
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.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.
Keywords: anxiety, depression, network analysis,resilience Abbreviations GAD-7: Generalized Anxiety Disorder-7, PHQ-9: Patient Health Questionnaire-9, CD-RISC-10: 10-item Connor-Davidson Resilience Scale, BEI: bridge expected influence, GGM: Gaussian graphical model, EBIC: extended Bayesian information criterion, LASSO: least absolute shrinkage and selection operator, CI: confidence interval
Received: 26 Sep 2024; Accepted: 04 Apr 2025.
Copyright: © 2025 Feng, Wang, Wang, Wang and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Tingwei Feng, Air Force Medical University, Xi'an, China
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