Application of the path analysis model to evaluate the role of distress, mental health literacy and burnout in predicting self-care behaviors among patients with type 2 diabetes

应用路径分析模型评估心理困扰、心理健康素养和倦怠在预测2型糖尿病患者自我护理行为中的作用

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Abstract

INTRODUCTION: Mental complications of diabetes are one of the main obstacles to the implementation of self -care behaviors that have been less studied. Therefore, this study was conducted to survey the effective factors in predicting burnout and self-care behaviors among patients with type 2 diabetes. METHODS: In this Path analysis, 1280 patients with type 2 diabetes were selected from Mashhad (Iran) in 2023 to 2024. Four scales, the mental health literacy (MHL) scale, diabetes burnout scale, diabetes distress scale, and self-care behavior scale were used for data gathering. AMOS software checked the direct and indirect paths between the variables. RESULTS: In the path analysis, variables of MHL and diabetes distress predicted 25% variance of diabetes burnout (R(2) = 0.25), and diabetes distress (total effect = 0.491) had the greatest impact on predicting diabetes burnout. Variables of MHL, diabetes distress, and diabetes burnout predicted 12% variance of Self-care behaviors (R(2) = 0.12) and MHL (total effect = -0.256), age of onset of diabetes (total effect = 0.199), and diabetes burnout (total effect = - 0.167) had the greatest impact on prediction of self-care behaviors. CONCLUSION: MHL could reduce diabetes distress and burnout and eventually promote self-care behaviors among patients with type 2 diabetes. Therefore, screening and identifying psychological problems (such as distress and burnout) and designing interventions to increase MHL can ultimately increase the health of patients with diabetes.

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