Non-adherence to medical regimens among patients with diabetes is a well-recognized concern in health care. Modified information, motivation, behavioural skills (IMB) model by adding an emotion component to it was tested to explore predictors of treatment adherence among 1,125 Iranian patients with diabetes type I (T1D) and type II (T2D) and due to other medical conditions. The modified IMB model explained 35% of the treatment adherence with large effect-sizes f² = 0.56 to 0.69. Self-compassion and interpersonal communication between staff and patients (ICSP) were significant predictors of treatment adherence among patients with T1D, T2D and diabetes due to other medical conditions, while both outperformed the other significant predictors of treatment adherence, i.e., illness perception and social support in all groups. Distress intolerance was a significant predictor of treatment adherence only in patients with T2D. In addition, patients, based on their type of diabetes, exhibited different patterns of illness perception in predicting treatment adherence. Among T2D patients and those with diabetes due to other medical conditions, gender (male; only in T2D) and being single were significant predictors of treatment adherence, while age and diabetes duration were not. Finally, the model demonstrated that above and beyond demographic features, self-compassion, interpersonal communication between patients and health care staff, distress intolerance, perceived social support and illness perception were significant predictors of treatment adherence among patients with diabetes.

中文翻译：

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糖尿病患者（I 型和 II 型）治疗依从性的心理预测因子：改进的信息-动机-行为技能模型

糖尿病患者不遵守医疗方案是医疗保健领域公认的一个问题。通过向其中添加情绪成分来改进信息、动机、行为技能 (IMB) 模型，对 1,125 名伊朗 I 型 (T1D) 和 II 型 (T2D) 糖尿病患者以及其他疾病患者的治疗依从性进行了测试，以探索治疗依从性的预测因素。修改后的 IMB 模型解释了 35% 的治疗依从性，效应值f ²  = 0.56 至 0.69。员工与患者之间的自我同情和人际沟通(ICSP) 是 T1D、T2D 和糖尿病患者因其他医疗条件而导致的治疗依从性的重要预测因子，而两者均优于治疗依从性的其他重要预测因子，即所有组的疾病认知和社会支持。痛苦不耐受是仅在 T2D 患者中治疗依从性的重要预测因子。此外，根据糖尿病类型，患者在预测治疗依从性时表现出不同的疾病感知模式。在 T2D 患者和因其他疾病而患有糖尿病的患者中，性别（男性；仅在 T2D 中）和单身是治疗依从性的重要预测因素，而年龄和糖尿病病程则不是。最后，该模型表明，除了人口特征、自我同情之外，