ArticleBMC psychiatry2025
A simulation-based network analysis of intervention targets for comorbid symptoms of depression and anxiety in Chinese healthcare workers in the post-dynamic zero-COVID policy era.
Article in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- Mapping the Symptom Networks of Depression, Anxiety, and Their Comorbidity Among Chinese Individuals Under Community Correction.Psychiatry investigation · 2026Article
- Career Status and Mental Health Among Female Dentists in China: A Nationwide Cross-Sectional Survey.International dental journal · 2026Article
- Identification of adaptation subgroups among Chinese nursing students: an integrated latent profile and network intervention simulation analysis.BMC nursing · 2026Article
- Symptom networks of internalizing and externalizing problems in children with leukemia: a network analysis and computer-simulated intervention study.BMC psychology · 2026Article
- Simulating symptom-specific interventions linking depression and anxiety among civil aviation college students: a network analysis differentiated by perceived parental relationships.BMC psychology · 2026Article
- Quality of life in older adults with urinary incontinence and its impact on the stigma-care needs network: latent profile and network analysis.BMC geriatrics · 2026Article
- The relationship between role clarity and compulsory citizenship behavior among junior nurses: evidence from network analysis and simulation-based network modeling.Frontiers in public health · 2026Article
- Early warning mechanism for college student adaptation: a network analysis and computational intervention simulation study based on mind wandering and problematic short video use.Frontiers in psychology · 2026Article
- Exploring which symptom should be targeted first in the comorbidity of anxiety and depression among adolescents with nomophobia: insight from a simulation network analysis.Frontiers in psychiatry · 2026Article
- Identifying profile-specific candidate targets for miner safety: a latent class and network analysis of psychological resources.Frontiers in psychology · 2026Article
- The interrelation between major depressive symptoms and ambivalence over emotional expression among college students: a network perspective on gender differences.Frontiers in psychiatry · 2025Article
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6 authors.
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Abstract
backgroundAfter the official end of the dynamic zero-COVID policy in China, healthcare workers continued to heavy workloads and psychological stress. In this new phase, concerns related to work and family, rather than infection, may have become new sources of psychological issues such as depression and anxiety among healthcare workers, leading to new patterns of comorbidity. However, few studies have addressed these issues. To fill this gap, this study used network analysis to examine new features and mechanisms of comorbidity between depression and anxiety symptoms, and simulated symptom-specific interventions to identify effective targets for intervention.
methodsA total of 708 Chinese healthcare workers (71.2% females; Age: M = 37.55, SD = 9.37) were recruited and completed the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7). This study first calculated the incidence rates of anxiety, depression, and their comorbidity, and then constructed the comorbid Ising network. Central and bridge symptoms were identified with expected influence (EI) and bridge EI, respectively. The NodeIdentifyR algorithm (NIRA) was then used to simulate interventions within the network, examining the effects of alleviating or aggravating specific symptoms on the network's severity.
results48.2% of Chinese healthcare workers reported experiencing depression (19.8%), anxiety (11.7%), or both (16.2%). In the anxiety-depression network, "guilt" and "appetite changes" were identified as the central symptoms, and "guilt" and "excessive worry" were identified as the bridge symptoms. Simulated interventions suggested that alleviating "Anhedonia" can the most reduce the overall severity of the network, while aggravating "guilt" can the most increase the overall severity. These two symptoms were considered the key target for treatment and prevention, respectively.
conclusionsChinese healthcare workers still face high risk of depression, anxiety, and comorbidity in the post-dynamic zero-COVID policy era. Our findings highlight the key roles of guilt, appetite changes, and excessive worry in the network of depression and anxiety symptoms. Future research should apply the results of the simulated interventions, develop intervention strategies targeting anhedonia, and focus on preventing guilt to improve the healthcare workers' mental health.
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