Assessing Diabetes Self-Management with the Diabetes Self-Management Questionnaire (DSMQ) Can Help Analyse Behavioural Problems Related to Reduced Glycaemic Control

Abstract

Aim: To appraise the Diabetes Self-Management Questionnaire (DSMQ)'s measurement of diabetes self-management as a statistical predictor of glycaemic control relative to the widely used SDSCA.

Methods: 248 patients with type 1 diabetes and 182 patients with type 2 diabetes were cross-sectionally assessed using the two self-report measures of diabetes self-management DSMQ and SDSCA; the scales were used as competing predictors of HbA1c. We developed a structural equation model of self-management as measured by the DSMQ and analysed the amount of variation explained in HbA1c; an analogue model was developed for the SDSCA.

Results: The structural equation models of self-management and glycaemic control showed very good fit to the data. The DSMQ's measurement of self-management showed associations with HbA1c of -0.53 for type 1 and -0.46 for type 2 diabetes (both P < 0.001), explaining 21% and 28% of variation in glycaemic control, respectively. The SDSCA's measurement showed associations with HbA1c of -0.14 (P = 0.030) for type 1 and -0.31 (P = 0.003) for type 2 diabetes, explaining 2% and 10% of glycaemic variation. Predictive power for glycaemic control was significantly higher for the DSMQ (P < 0.001).

Conclusions: This study supports the DSMQ as the preferred tool when analysing self-reported behavioural problems related to reduced glycaemic control. The scale may be useful for clinical assessments of patients with suboptimal diabetes outcomes or research on factors affecting associations between self-management behaviours and glycaemic control.

Fig 1. Stuctural equation model of diabetes self-management as measured by the DSMQ and glycaemic control for patients with type 1 and type 2 diabetes.

Data are standardised regression weights (β) for paths or squared multiple correlations (R²) for variables. Boxes indicate manifest measurement variables; ovals indicate latent variables operationalised by manifest indicators; error terms are not displayed for ease of presentation. SRMR, Standardised Root Mean Square Residual; TLI, Tucker Lewis Index; CFI, Comparative Fit Index; RMSEA, Root Mean Square Error of Approximation. Indication of two-sided significance: * P < 0.05; † P < 0.01; ‡ P < 0.001.

Fig 2. Stuctural equation model of diabetes self-management as measured by the SDSCA and glycaemic control for patients with type 1 and type 2 diabetes.

Data are standardised regression weights (β) for paths or squared multiple correlations (R²) for variables. Boxes indicate manifest measurement variables; ovals indicate latent variables operationalised by manifest indicators; error terms are not displayed for ease of presentation. SRMR, Standardised Root Mean Square Residual; TLI, Tucker Lewis Index; CFI, Comparative Fit Index; RMSEA, Root Mean Square Error of Approximation. Indication of two-sided significance: * P < 0.05; † P < 0.01; ‡ P < 0.001.