ArticleFrontiers in aging neuroscience2026
Joint network analysis of non-motor symptoms and quality of life in patients with Parkinson's disease.
Article in Frontiers in aging neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Non-motor symptoms (NMS) are highly prevalent in Parkinson's disease (PD) and are major determinants of declining quality of life (QoL), yet traditional statistical approaches are insufficient to capture the complex interactions between NMS and QoL. Network analysis offers a promising alternative for exploring these interactions. Objective: To construct a joint network of non-motor symptoms (NMS) and quality of life (QoL) in patients with Parkinson's disease (PD), identify core and bridge nodes, and inform precision nursing interventions. Methods: A convenience sample of 342 PD patients was recruited between January and June 2026 from the PD specialty outpatient clinic and neurology inpatient wards of a tertiary specialized hospital in Tianjin, and investigated using the Non-Motor Symptoms Scale (NMSS) and the Parkinson's Disease Questionnaire-39 (PDQ-39). A joint network model was constructed via network analysis, and network structures were compared between early- and mid-to-late-stage patients. Results: NMSS6 gastrointestinal symptoms (Str = 1.027), PDQ5 social support (Str = 0.995), and PDQ6 cognition (Str = 0.992) were the core nodes of the joint network based on strength centrality. PDQ6 cognition (Bridge Str = 0.326) and NMSS3 mood/cognition (Bridge Str = 0.260) were the key bridge symptoms linking NMS and QoL. Mobility and social support showed the highest expected influence (EI = 0.960 and 0.939, respectively). The overall network structure differed significantly between early-stage and mid-to-late-stage patients ( Conclusion: Complex associations exist between NMS and QoL in PD patients and are reorganized across disease stages; gastrointestinal symptoms, cognition, and social support represent candidate targets for future longitudinal and interventional research.
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