Development of Nutrition Knowledge-based Learning Model by Information Technology for Blood Sugar Control among Diabetic Patients
Keywords:Nutrition knowledge-based learning model, Information technology, Blood sugar control, Diabetic patient
Background : The development of educational tools for behavior change in diabetes patients is widespread. However, the educational model using the mobile application for DM control is limited.Objective : To develop and evaluate the nutrition knowledge-based learning model (classify food) for blood sugar control among diabetic patients in Rajavithi Hospital.Methods : The research and development was carried out in two phases. First: The situation analysis to develop a nutrition knowledge-based learning model using information technology was performed by multidisciplinary brainstorming. Second: A quasi-experimental study was performed to evaluate outcomes including FBS, HbA1c, knowledge to classify food types, and satisfaction. Eighty diabetic patients were equally assigned into two groups. The experiment was given classify foods application via smart devices. The application is a colorful figure with music. Touching with fingertips to move each figure along the point of each food type. Three food types were classified as unlimited intake, limited intake and forbidden foods. A trial took 90 seconds per cycle, and correct answer scores were recorded. The comparison group received pre-and post- knowledge paper assessment, nurses and nutritionists gave counseling for both groups. To follow-up, the team called both groups for lifestyle modification. FBS and HbA1c were measured at baseline and three months. Independent t-test and Paired t-test were used to compare outcomes between groups and before-after the trial. This study was reviewed and approved by the research ethics committee, Rajavithi hospital.Results : Classify food application model via Android was initiated. The characteristics of both groups were similar. The experiment group had significantly better knowledge about food classification than before the study and better than the comparison group (p=0.035). After the trial, average FBS and HbA1c in the experiment group were significantly lower than those before the trial, and significantly lower than those of the comparison group (p=0.041 and p=0.048). The experiment group had higher satisfaction scores than those of a comparison group (p<0.001). Attractive style, better knowledge, modern model, and ease to use were the main reasons for classifying food at the most satisfactory level.Conclusions : The classify food game model is an effective learning tool that significantly improved FBS and HbA1c in diabetic patients. Further investigation should apply this model for the long term to manage proper dietary behavior and control blood sugar levels. Exercise and emotional management should add to the application.
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