Emotional Distress Symptom Networks in Patients with Gynecological Malignancies: A Cross-Sectional Study

Background: Emotional distress (ED) is common among patients with gynecological malignancies and is associated with reduced quality of life and suboptimal health outcomes. Total-score approaches may overlook the complex interrelationships among individual emotional symptoms. Objective: This study provides a theory-informed contextual application and empirical boundary test of symptom network analysis, organized by the Stress Process Model (SPM), to examine not only how ED symptoms cluster and connect with psychosocial correlates and quality-of-life domains, but also whether psychosocial stratification is reflected in altered symptom topology or primarily in differences in distress burden. Methods: A cross-sectional study was conducted among 415 patients with gynecological malignancies recruited from a tertiary hospital in China. ED was assessed using the Brief Profile of Mood States-Short Form (BPOMS-SF30). An exploratory three-track screening strategy was used to derive a focused 16-node set of frequent negative mood symptoms. Gaussian graphical models with EBICglasso regularization were estimated for the symptom network and for extended networks including demographic/clinical variables, SPM-related psychosocial variables, and quality-of-life indicators. Results: The ED network showed dense positive connectivity, with strong within-domain clustering and several cross-domain associations. Exhaustion, restlessness, and irritability were relatively more relationally prominent in the primary network, although centrality stability was low to moderate across models. Fatigue-related symptoms were closely connected with anxiety, depressive symptoms, and impaired quality of life. Among psychosocial variables, self-perceived burden showed the strongest conditional association with fatigue. Adjusting for demographic and clinical variables did not materially alter the core symptom network, and no significant subgroup differences in global strength or overall structure were observed across psychosocial strata. Conclusions: In this sample, psychosocial risk stratification appeared to relate more to the overall severity and burden of distress than to major reorganization of symptom topology. The study therefore contributes primarily as a theory-informed contextual application of network methods and as an empirical boundary test showing that several psychosocial strata did not exhibit major topological differences. Because the retained nodes were selected for prevalence, association strength, and selection stability, the observed prominence of fatigue- and activation-related symptoms should be interpreted as conditional on this focused symptom subset. Overall, the findings are correlational, exploratory, and hypothesis-generating.