Structural Model for Explaining Quality of Life Based on Early Maladaptive Schemas and the Role of Treatment Adherence and Coping Strategies in Patients with Type 2 Diabetes

The objective of the present research was to explain the structural model for quality of life based on early maladaptive schemas and the role of treatment adherence and coping strategies in patients with type 2 diabetes.

Methods and Materials: 

This study, in terms of research methodology, falls into the category of descriptive-correlational research using structural equation modeling. The research population consisted of all patients with type 2 diabetes in Tehran who visited medical centers during the year 2021. The sample of the current study included 350 patients with type 2 diabetes in Tehran in 2021, selected through convenience sampling based on inclusion and exclusion criteria of the study. Data were collected using the short form of the World Health Organization Quality of Life Questionnaire, Young's Early Maladaptive Schemas Short Form Questionnaire, Treatment Adherence Questionnaire, and Young's Avoidance Coping Strategies Questionnaire. Data were analyzed using Structural Equation Modeling (SEM) and Pearson correlation statistical methods, employing SPSS 22 and AMOS 22 software.

The results showed that the fit indices PCFI=0.655, PNFI=0.661, CMIN/DF=2.90, RMSEA=0.089, IFI=0.917, CFI=0.914, and GFI=0.903 indicate a good fit of the proposed model with the data. The highest coefficient (-0.47) was attributed to the path from autonomy and impaired performance to quality of life. The coefficient of determination for the quality variable of marital relationship in the proposed structural model is 0.889, indicating that the external variables can predict 89 percent of the variance in quality of life, which is considered strong.

Therefore, it can be concluded that the structural model for explaining quality of life based on early maladaptive schemas and the role of treatment adherence and coping strategies in patients with type 2 diabetes fits appropriately.