Objective: Firefighters are prone to mental disorders such as anxiety and depression because they are frequently exposed to trauma, including injury and death. Network analysis is an approach used to depict a holistic view of mental disorders, which is a symptom-oriented method, and argues that the mental structure is likely to arise from the interaction among observable symptoms. Hence, the present study aims to reveal the characteristics of depressive and anxiety symptoms for Chinese firefighters via a network approach.
Method: We recruited 715 male firefighters (Mage = 26.29, SDage = 5.93) and asked them to complete the Self-rating Anxiety Scale and Self-rating Depression Scale to measure their levels of anxiety and depression.
Results: Faintness had the highest symptom strength in the anxiety network, while irritability had the highest symptom strength in the depression network. The strongest edge (i.e., the connection among symptoms) in the anxiety network was apprehension-restlessness, and in the depression network was confusion-psychomotor retardation. In the bridge network, which contained both anxiety and depression, the strongest edge was confusion-psychomotor retardation, and the highest centrality symptoms (Z score above 1) were panic, easy fatiguability, palpitations, crying spells, and tachycardia. Bayesian network analysis revealed that fear was the most influential trigger symptom in the anxiety-depression network structure of firefighters.
Conclusions: Clinicians could focus on treating the related bridge and trigger symptoms, such as panic, easy fatiguability, palpitations, crying spells, tachycardia, and fear, to alleviate the comorbidity of anxiety and depression in firefighters. (PsycInfo Database Record (c) 2024 APA, all rights reserved).