PSYCHOSOMATIC SYMPTOMS IN TYPE 2 DIABETES PATIENTS: A NETWORK ANALYSIS

Abstract

Background

Type 2 diabetes patients display complex psychosomatic symptoms, but the key variables and their interactions remain poorly understood.

Aims & Objectives

We aimed to explore the networks and predictivities among psychosomatic symptoms, demographics, and clinical characteristics of type 2 diabetes.

Method

412 type 2 diabetes patients and 422 healthy controls were recruited. The demographics, the Diagnostic Criteria for Psychosomatic Research-Revised Semi-Structured Interview (DCPR-R SSI), and the Psychosomatic Symptom Scale (PSSS) were used. Clinical characteristics, including glycated hemoglobin (HbA1c) and high-density lipoprotein (HDL), were tested. Flow network analyses were applied to psychosomatic symptoms. Then, a predictability network of psychosomatic symptoms, demographics, and clinical characteristics was constructed.

Results

Compared to healthy controls, the type 2 diabetes networks showed significantly stronger edge connections (global strength type 2 diabetes/healthy controls = 3.56/2.23, p <0.001), especially between PSSS somatic factor and persistent somatization (edge weight difference = 0.29, p <0.001), allostatic overload, and demoralization (edge weight difference = 0.32, p <0.001). The comprehensive network showed high predictability in work (62.5%), sex (43.8%), age (37.8%), diabetes duration (13%), HDL (11.4%), and HbA1c (7.6%), in addition to psychosomatic manifestations.

Discussion and Conclusion

This study not only provides a novel framework for understanding the psychosomatic symptoms specific to type 2 diabetes but also offers robust evidence for targeted interventions for these complex symptoms.