Background: The 2019 coronavirus disease (COVID-19) pandemic has impacted the mental health and well-being of medical personnel, including nursing students. Network analysis provides a deeper characterization of symptom-symptom interactions in mental disorders. The aim of this study was to elucidate characteristics of anxiety and depressive symptom networks of Chinese nursing students during the COVID-19 pandemic. Method: A total of 932 nursing students were included. Anxiety and depressive symptom were measured using the seven-item Generalized Anxiety Disorder Scale (GAD-7) and two-item Patient Health Questionnaire (PHQ-2), respectively. Central symptoms and bridge symptoms were identified via centrality indices and bridge centrality indices, respectively. Network stability was examined using the case-dropping procedure. Results: Irritability, Uncontrollable worry, Trouble relaxing, and Depressed mood had the highest centrality values. Three bridge symptoms (Depressed mood, Nervousness, and Anhedonia) were also identified. Neither gender nor region of residence was associated with network global strength, distribution of edge weights or individual edge weights. Limitations: Data were collected in a cross-sectional study design, therefore, causal relations and dynamic changes between anxiety and depressive symptoms over time could not be inferred. Generalizability of findings may be limited to Chinese nursing students during a particular phase of the current pandemic. Conclusions: Irritability, Uncontrollable worry, Trouble relaxing, and Depressed mood constituted central symptoms maintaining the anxiety-depression network structure of Chinese nursing students during the pandemic. Timely, systemic multi-level interventions targeting central symptoms and bridge symptoms may be effective in alleviating co-occurring experiences of anxiety and depression in this population.
Background: Nursing students who suffer from co-occurring anxiety experience added difficulties when communicating and interacting with others in a healthy, positive, and meaningful way. Previous studies have found strong positive correlations between Internet addiction (IA) and anxiety, suggesting that nursing students who report severe IA are susceptible to debilitating anxiety as well. To date, however, network analysis (NA) studies exploring the nature of association between individual symptoms of IA and anxiety have not been published.Objective: This study examined associations between symptoms of IA and anxiety among nursing students using network analysis.Methods: IA and anxiety symptoms were assessed using the Internet Addiction Test (IAT) and the Generalized Anxiety Disorder Screener (GAD-7), respectively. The structure of IA and anxiety symptoms was characterized using “Strength” as a centrality index in the symptom network. Network stability was tested using a case-dropping bootstrap procedure and a Network Comparison Test (NCT) was conducted to examine whether network characteristics differed on the basis of gender and by region of residence.Results: A total of 1,070 nursing students participated in the study. Network analysis showed that IAT nodes, “Academic decline due to Internet use,” “Depressed/moody/nervous only while being off-line,” “School grades suffer due to Internet use,” and “Others complain about your time spent online” were the most influential symptoms in the IA-anxiety network model. Gender and urban/rural residence did not significantly influence the overall network structure.Conclusion: Several influential individual symptoms including Academic declines due to Internet use, Depressed/moody/nervous only while being off-line, School grades suffering due to Internet use and Others complain about one's time spent online emerged as potential targets for clinical interventions to reduce co-occurring IA and anxiety. Additionally, the overall network structure provides a data-based hypothesis for explaining potential mechanisms that account for comorbid IA and anxiety.
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