The Effect of Emotional Intelligence Training via Method Psychodrama on Marital Satisfaction of Patients with MS

MS is a progressive and chronic disease of the central nervous system with symptoms that can be debilitating. Appropriate interventions including Emotional Intelligence Training improve the quality of life MS patients. The aim of this study is to determine the effect of emotional intelligence training through Psycho-Drama methods on marital satisfaction of patients with MS. This study is a one-group, before-after, quasi-experimental study. A total of 22 patients were enrolled in this study. The samples were selected through non-random sampling based on the goal of study among visitors of MS Society, Kurdistan province, Iran. Data collection tool was questionnaires with two sections: 1) demographic information and 2) ENRICH-B marital satisfaction questionnaire including 47 items. Intervention was conducting 20 sessions of 2-hour training. Questionnaires were filled by patients before and after intervention. Methods for data analysis were descriptive statistics (tables of relative frequency distribution, the mean, and standard deviation) and inferential statistics of paired t test. Paired t test showed a significant difference in total scores of marital satisfaction before and after training sessions (P < 0.05). Finally, we concluded that, designing and applying emotional intelligence training programs via psychodrama method is effective on marital satisfaction in patients with multiple sclerosis. Keywords: Multiple sclerosis, emotional intelligence training, psychodrama, marital satisfactio

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications