Subgrouping patients with type 2 diabetes using behavioural and clinical factors: a cross-sectional study in a hospital-based setting in Thailand

Abstract

OBJECTIVES: This study aimed to identify distinct patient subgroups based on glycaemic control (glycosylated haemoglobin (HbA1c)), self-efficacy and self-management in patients with type 2 diabetes mellitus (T2DM), and to examine differences in outcomes and identify key predictors associated with cluster characteristics. DESIGN: Cross-sectional study. SETTING: Chronic disease clinic at Thasala Hospital, Thailand. PARTICIPANTS: Participants with T2DM were recruited using a consecutive sampling approach during their scheduled clinic visits on predefined days and times. A total of 440 participants were included in the final analysis. OUTCOMES MEASURES: The three variables used for K-means cluster analysis were HbA1c, self-efficacy scores and self-management scores. HbA1c values were obtained from medical records, while self-efficacy and self-management were assessed using the Thai versions of the Diabetes Management Self-Efficacy Scale and the Diabetes Self-Management Scale. Demographic and clinical characteristics were included as predictor variables in multiple linear regression analyses. RESULTS: Four clusters were identified. Cluster 1 (moderate profile, n=124) had fair glycaemic control (HbA1c=7.9%) and moderate self-efficacy (mean=70) and self-management (mean=47). Cluster 2 (underperforming, n=136) exhibited poor glycaemic control (HbA1c=8.7%), regardless of high self-efficacy (mean=79) and low self-management (mean=40). Cluster 3 (high performers, n=135) demonstrated fair glycaemic control (HbA1c=7.5%) with the highest levels of self-efficacy (mean=84) and self-management (mean=51). Cluster 4 (high risk, n=45) had very poor glycaemic control (HbA1c=9.4%) and the lowest scores for both self-efficacy (mean=56) and self-management (mean=34). Regression analysis confirmed the heterogeneity across clusters, with varying predictors and explained variance (adjusted R² ranging from 0.014 to 0.182 across significant models). CONCLUSIONS: The findings highlight the distinct behavioural and clinical profiles among patients with T2DM. Cluster 4 patients with the poorest glycaemic and behavioural outcomes may benefit from intensive behavioural support and closer clinical monitoring, whereas Cluster 2 patients, showing high self-efficacy but poor self-management, indicate the need for structured, skills-based interventions. Clusters 1 and 3 showed balanced profiles, suggesting less urgent need for intervention and potential to maintain current management.