Symptom network connectivity and interaction among people with HIV in China: secondary analysis based on a cross-sectional survey

Abstract

Abstract Background The symptom burden in people with HIV (PWH) is considerable. Nonetheless, the identification of a central symptom, or bridge symptom, among the myriad symptoms experienced by PWH remains unclear. This study seeks to establish networks of symptom experiences within different clusters and investigate the relationships and interconnectedness between these symptoms in PWH. Methods A multicenter, cross-sectional descriptive design was carried out in China over two periods: November 2021 to January 2022 and April 2022 to May 2022. A total of 711 PWH completed online questionnaires, providing information on demographics and the 27-item Self-Report Symptom Scale. The symptom network was analyzed using Network/Graph theory, allowing for the exploration of connections between physical, cognitive, and psychological symptoms. This analysis was based on data from a subset of 493 individuals out of the total 711 PWH. Results A total of 493 PWH who exhibited symptoms out of a total of 711 PWH were analyzed. The average number of symptoms reported was 5.367. The most prevalent symptom was sleep disturbance (37.98%). In the node centrality analysis, a cognitive symptom, ‘becoming confusing’, emerged as the most central symptom with significant values for node centrality (strength = 1.437, betweenness = 140.000, closeness = 0.003). Fever was identified as the bridge symptom with the highest bridge strength (0.547), bridge closeness (0.053), lower bridge betweenness (23.000), and bridge expectedinfluence (0.285). Overall, our network displayed good accuracy and stability. Conclusion Early identification and assessment of the central or bridge symptoms should be emphasized in clinical practice. According to the findings from network analysis, healthcare providers should proactively explore intervention strategies or bundle care to alleviate the burden of symptoms and enable anticipatory care.

Keywords

• HIV/AIDS
• Symptom experience
• Network analysis