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. 2025 Jan 23:15:1513524.
doi: 10.3389/fpsyt.2024.1513524. eCollection 2024.

Symptom network analysis of insomnia-depression-anxiety-stigma in tuberculosis patients

Affiliations

Symptom network analysis of insomnia-depression-anxiety-stigma in tuberculosis patients

Xiangmin Liu et al. Front Psychiatry. .

Abstract

Background: Insomnia, depression, anxiety, and stigma are prevalent and often coexist in patients with Tuberculosis (TB), potentially exacerbating one another. However, the complex intrinsic associations among these four disorders remain unclear, particularly concerning the role of stigma in relation to the other disorders.

Methods: A cross-sectional study was conducted at West China Hospital and the Fourth People's Hospital of Guangxi from November 2023 to June 2024. The levels of insomnia, depression, anxiety, and stigma among TB patients were assessed using the Pittsburgh Sleep Quality Index (PSQI), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and the TB-Related Stigma Scale (TRSS). Network analysis was used to identify the central and bridge symptoms and explore the role of stigma within the insomnia-depression-anxiety-stigma network.

Results: PHQ1 (anhedonia), GAD1 (nervousness), GAD5 (restlessness), and PHQ3 (sleep problems) are central to the network. Bridge symptoms, including PHQ3 (sleep problems), PSQI5 (sleep disturbances), and GAD5 (restlessness) link the depression, insomnia, and anxiety communities. TRSS1 (family's negative perception) of the stigma community exhibited the highest betweenness and second highest bridge betweenness in the network, highlighting the mediating role of family support across insomnia and psychological symptoms. Additionally, the global strength invariance test indicates that gender, age and education level do not significantly impact the network structure.

Conclusion: Depression (anhedonia and sleep problems) and anxiety (nervousness and restlessness) are the primary concerns requiring intervention in TB patients. In addition, sleep problems act as a bridge in the overall network. Stigma, particularly negative perceptions from family, may play a crucial mediating role in sustaining the entire symptom network. Consequently, these symptoms could represent potential targets for intervention.

Keywords: anxiety; depression; insomnia; stigma; symptom network analysis; tuberculosis.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Central symptoms of insomnia-depression-anxiety-stigma in TB patients. (A) The symptom network structure of insomnia-depression-anxiety-stigma. Red circles indicate central symptoms, green lines indicate positive associations, and red lines indicate negative associations. (B) Centrality measures of symptom networks, including Strength Centrality, Closeness Centrality, Betweenness Centrality, and Expected Influence (EI).
Figure 2
Figure 2
Bridge symptoms of insomnia-depression-anxiety-stigma in TB patients. (A) The symptom network structure of insomnia-depression-anxiety-stigma. Red circles indicate bridge symptoms, green lines indicate positive associations, and red lines indicate negative associations. (B) Bridge measures of symptom networks, including Bridge Strength Centrality, Bridge Closeness Centrality, Bridge Betweenness Centrality, and Bridge Expected Influence (BEI).
Figure 3
Figure 3
Accuracy and stability tests of the symptom network. (A) 95% confidence intervals for network edge weights derived from bootstrapping 1000 times. (B) Average correlation curve with the original sample derived from case-dropping subset bootstrap 1000 times. The green curve shows the correlation coefficient between the Expected Influence (EI) ranking after deleting a certain percentage of the sample and the ranking of the original sample. The red curve shows the correlation coefficient between the Bridge Expected Influence (BEI) ranking after deleting a certain percentage of samples and the ranking of the original samples.

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