A type-2 fuzzy ontology and its application to personal diabetic-diet recommendation
IEEE Transactions on Fuzzy Systems
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The healthcare industry strives to improve the technical work of healthcare providers in hospitals. In contrast, the more common home treatment tasks like managing prescription medications and complying with the complex demands of life-threatening diseases such as Type II Diabetes receive little attention. Treatment and prevention decisions are in the hands of patients and often mismanaged. Available commercial information sheets, designed to support prescription self management, are incompatible with patient perceptual and cognitive capacities. We show that material that is sensitive to the perceptual and cognitive capacities of potential users is more usable and is preferred. A review of existing training for diabetics identified compliance barriers. Many patients do not understand the dynamics that controlled their disease and so make poor decisions. Available training provides rules and procedures, but little about the dynamic demands of maintaining stability within parameters. We explored using control theory and incorporating a mental model of diabetes into rule-based training. This promises to improve the effectiveness of self management. These two naturalistic investigations confirm the importance of field studies and of using patient informants to understand the demands and opportunities that accompany medical self management.