The interplay between stigma and sleep quality in breast cancer: A cross-sectional network analysis.

PURPOSE: Stigma, a subjective internal shame, arises from the association of cancer with death. Sleep quality can be considered a product of stigma. However, the extent of overlap or difference between the two remains unclear. METHODS: In total, 512 survivors with breast cancer were recruited from the "Be Resilient to Breast Cancer" project between May and August 2023. This study estimated the stigma, sleep quality, and their relationship by conducting a cross-sectional network analysis. The social impact scale and Pittsburgh Sleep Quality Index scale were employed in this study. RESULTS: The core symptom for stigma from the network analysis was alienation by people (Strength = 1.213, Betweenness = 13, Closeness = 0.00211). The core symptom for sleep quality were the sleep quality (Str = 1.114, Bet = 17, Clo = 0.01586). Regarding the combination network, results showed that self-isolation and daytime dysfunction were the bridge nodes and that daytime dysfunction was positively associated with feeling less capable than before (according to self) (r = 0.15). CONCLUSION: Our study demonstrates the core symptoms in different symptomatic networks, which can be targeted for treatment personalization and aid in the improvement of sleep quality and stigma in breast cancer patients.

Association between stigma and sleep quality in patients with breast cancer: A latent profile and mediation analysis.

PURPOSE: This study aims to identify the heterogeneity in the stigma experienced by patients with breast cancer and examine the mediation effect of resilience on the relation between stigma and sleep quality. METHOD: A total of 396 patients with breast cancer were enrolled from Be Resilient to Breast Cancer (BRBC) program between January and April 2023. Participants completed the Social Impact Scale, the 10-item Connor-Davidson Resilience Scale, and the Pittsburgh Sleep Quality Index Scale. Latent profile analysis (LPA) and mediation analysis were conducted to analyze the data. RESULTS: LPA categorized stigma into three subgroups, namely low-stigma (21.9%), moderate-stigma (64.9%), and high-stigma (13.2%). Mediation analysis revealed a fully mediated effect in the comparison between low-stigma and moderate-stigma groups (standard error [SE] = 0.13, 95%CI = 0.06,0.56), whereas a partially mediated effect was observed in the comparison between low-stigma and high-stigma groups (SE = 0.18, 95%CI = 0.39,1.10). CONCLUSIONS: Stigma is a significant factor to sleep quality in breast cancer and resilience could act as a robust buffer against stigma resulting in improved sleep quality. Resilience-based interventions might be helpful in this population.