Integrirani dijagnostički postupak za posttraumatski stresni poremećaj Integrative diagnostic algorithm for posttraumatic stress disorder

摘要

The diagnosis of post-traumatic stress disorder (PTSD) is a complex process, which is reflected in clinical and forensic work and research. Because of the complexity of diagnosing PTSD, there is a need for additional and more comprehensive diagnostic models. The intention of this work was to use data mining methods for integration of data related to psychiatric patients with PTSD (personal history, data from psychiatric and psychological questionnaires and evaluation), to select significant variables and rules, and form an algorithm that would contribute to improvement and objectivization of diagnostic procedure. After performing the data analysis, we have extracted significant variables and rules that characterize patients with PTSD, conducted regression analysis and then formed diagnostic algorithm for PTSD. This is the first study of this type in psychiatry, using data mining methods, which is focusing on the integration of a broad set of data and formation of models for diagnosing PTSD. Of importance for clinical practice is that the variables that are found significant may help in the diagnostic process in patients with PTSD. In addition, we have developed a system that allows the collection of a large number of variables and their structuring in a way that is suitable for further processing using data mining methods, which can serve as a basis for the development of similar models for other psychiatric disorders.