Psychological consistency network characteristics and influencing factors in patients after percutaneous coronary intervention treatment.

Background: A psychological sense of coherence (SOC) in percutaneous coronary intervention (PCI) patients is important for disease prognosis, and there is considerable variation between their symptoms. In contrast, network analysis provides a new approach to gaining insight into the complex nature of symptoms and symptom clusters and identifying core symptoms.

Aim: To explore the psychological coherence of symptoms experienced by PCI patients, we aim to analyze differences in their associated factors and employ network analysis to characterize the symptom networks.

Methods: A total of 472 patients who underwent PCI were selected for a cross-sectional study. The objective was to investigate the association between general patient demographics, medical coping styles, perceived stress status, and symptoms of psychological coherence. Data analysis was conducted using a linear regression model and a network model to visualize psychological coherence and calculate a centrality index.

Results: Post-PCI patients exhibited low levels of psychological coherence, which correlated with factors such as education, income, age, place of residence, adherence to medical examinations, perceived stress, and medical coping style. Network analysis revealed that symptoms within the sense of psychological coherence were strongly interconnected, particularly with SOC2 and SOC8, demonstrating the strongest correlations. Among these, SOC10 emerged as the symptom with the highest intensity, centrality, and proximity, identifying it as the most central symptom.

Conclusion: The network model has strong explanatory power in describing the psychological consistency symptoms of patients after PCI, identifying the central SOC symptoms, among which SOC10 is the key to overall SOC enhancement, and there is a strong positive correlation between SOC2 and SOC8, emphasizing the need to consider the synergistic effect of symptoms in intervention measures.