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

Hongyu Zou, Junyao Gao, Wanchun Wu, Lijuan Huo and Wei Zhang

Social Science & Medicine, 2024, vol. 360, issue C

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.

Keywords: Depression; Anxiety; Cross-lagged network analysis; Symptomatology; Prediction (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.socscimed.2024.117339

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