مجله دیابت و متابولیسم ایران
سال هجدهم شماره 2 (پیاپی 84، آذر و دی 1397)

The lack of self-care is the most important in diabetic. Because it is important factor that lead to dead of diabetic patients. The aim of this study was to Comparison of the Effect of Group Based and Mobile Based Education on Self-Care Behaviors in Type II Diabetic Patients This randomized clinical trial was conducted on 90 patients' diabetic type 2 who referred to diabetic clinic of Ahvaz University of Medical Sciences. Initially, patients were divided into three groups of homogeneous mobile-based education, group training and control group based on individual characteristics. . In group training, eight sessions of training were conducted, mobile education was installed on the patient's phone and the control group through had given routine education. The data collection tool was self-care questionnaire, demographic, and demographic questionnaire for type II diabetic patients. Data were analyzed using SPSS 22 software and one-way and one-way ANOVA tests at a significant level was (0.05). Group training and mobile-based education had a significant effect on routine education (P = 0.001). Self-care education, except in the field of foot care that the effect of mobile-based education was more than group training. In comparison, self-care score in the three groups was statistically significant. Although there was no statistically significant difference between the two educational groups, the effectiveness of education in the mobile group was more effective. However, the findings found the effectiveness of group-based and mobile-based education. However, the use of mobile-based training programs is recommended because of easy access, lack of time and space restrictions.

Patients with diabetes need to be educated efficiently and effectively in order to increase their quality of life. According to modern technological developments, multimedia message-based education is considered as one of the effective educational strategies. The purpose of this study was to investigate the effect of multimedia-based education in the Telegram application and in-person method on fasting blood glucose and glycosylated hemoglobin levels in patients with insulin-dependent diabetes. In this clinical trial study, a sample of 66 patients with insulin-dependent diabetes who referred to the emergency department and the clinic of Sina hospital in Tabriz, were randomly assigned in double blocks into two groups: in-person education and multimedia-based education. Data gathering tools included a demographic form, glycosylated hemoglobin and fasting blood glucose were measured before and three months after the educational intervention. Data were analyzed with independent and paired samples t-tests. The results indicated that there were no significant differences in the mean values of glycosylated hemoglobin and fasting blood glucose between two groups before and after education(P >0.05). In within-group comparison, there was a statistically significant difference in the multimedia message group on the reduction of mean values of glycosylated hemoglobin (p= 0.02) but these values differences were not significant in in-person group (p= 0.33). Multimedia-based education in the Telegram application compared to in-person education improves self-care and reduces the mean values of glycosylated hemoglobin in diabetic patients. This educational context can be used to facilitate the self-care education process to patients.

Early detection of diabetes is critical to avoid complications and damage caused by this disease. The purpose of this paper is designing an intelligent system for Diabetes prediction (healthy or patient) by using regression method based on Multilayer Perceptron Neural Network. In this descriptive-analytic study, an intelligent system is designed to classification diabetes patients. The system is simulated by MATLAB software 2015 (8.5.0.197613). In this study, used PID dataset in UCI Machine Learning Repository. The dataset is contained 768 records from Indian women and 8 diagnostic factors for Diabetes. The data were then divided randomly in 20 groups for training and testing, after preprocessing. 90% of the data is used for training phase and 10% for the test phase. The results obtained based on sensitivity, specificity, accuracy and precision were 0.4815, 0.9804, 0.8077 and 0.9286, respectively. The obtained results, showed superiority of designed intelligent system to classify individuals (healthy and patient) in comparison with other methods implemented on this dataset. Using MLP- Regression has increased the accuracy of the proposed system.

Diabetes mellitus is one of the most common chronic diseases and the patient's quality of life plays an important role in controlling the disease. The purpose of this study was to investigate the mediating role of quality of life in the relationship between depression, stress and anxiety, with severity of diabetes. 108 patients with type 2 diabetes (57 women, 51 males) participated in this study. The participants completed the 21st-DASS Questionnaire, a quality of life questionnaire (SF-36), and a demographic questionnaire. The results of the study showed that the severity of the disease was negatively correlated with quality of life and positively correlated with anxiety, depression and stress (P <0.01). The results of path analysis also indicated the mediating role of quality of life in the relationship between depression and anxiety and the severity of type 2 diabetes. Based on the results, it is necessary to consider psychological interventions in order to reduce depression and anxiety and improve the quality of life of patients in the field of diabetes management.

Diabetes is one of the most dangerous and common diseases of the modern world. Since medical research usually has limited data available and medical data is very ambiguous, it seems appropriate to use the fuzzy model to find out the relationship between input and output in medical data. None of the previous articles of fuzzy regression have been used to predict complications of diabetes, including nephropathy. Therefore, in this study, a fuzzy regression model was used to predict nephropathy in a diabetic patient. In the present study, GFR results of previous patient experiments were used to predict a deeper horizons of GFR and ultimately to predict renal disease. Chronic kidney disease has been stratified based on the amount of GFR, that fuzzy data has been constructed based on these levels. The GFR prediction was performed in the following steps. Step 1: Define fuzzy sets based on the GFR level, which is considered for each level of a fuzzy set. Step 2: Fuzzify patient data Based on fuzzy sets. Step 3: GFR prediction with fuzzy regression model. Step 4: Defuzzifying the predictions. Step 5: Evaluating the model efficiency. The RMSE error is used to compare the performance of the model. The results of GFR prediction showed that comparison RMSE was 10.09 with using simple linear regression model and 4.24 in fuzzy model. fuzzy regression model can predict nephropathy in diabetic patients.

Type 1 diabetes is one of the most common metabolic abnormalities in childhood, with one in every 400 to 600 children affected by the disease. The aim of study was to evaluate the effectiveness of cognitive-behavioral therapy on emotional regulation of children with type 1 diabetes. The research design was a quasi-experimental design with pre-test, post-test and follow-up and control group. The sample of 25 children aged 8 to 13 years with type 1 diabetes was diagnosed by endocrinologist. They were randomly assigned control (n = 15) and experimental (n = 10) groups. Subjects completed an cognitive emotion regulation questionnaire (Garnefski et al., 2007) in a pre-test, post-test, and one month and a half follow-up. Data were analyzed using repeated measure analysis of variances. The results of this study showed that there was a significant difference between the mean scores of emotional regulation in pre-test, post-test and follow-up (P <0.01). Also, there was a significant difference between emotional regulation in the experimental and control groups (P <0.05). Cognitive-behavioral therapy can be considered as an effective intervention to regulate the excitement of children with diabetes.