Zdrojem výzkumu byla diskusní fóra na čtyřech českých a jednom slovenském portálu věnovaná zdraví a poruchám příjmu potravy. Obsahovou analýzou 378 příspěvků od 259 dívek byly získány nejčastěji zmiňované faktory podílející se na rozvoji poruch příjmu potravy (PPP) u dospívajících dívek. Kvalitativní obsahovou analýzou textů v internetových diskusích jsme hledali subjektivní významy, které faktorům vzniku onemocnění připisují samy dívky. Byly formulovány následující výzkumné otázky: Které faktory vnímaly dívky jako důležité v období vzniku nemoci? Jaké hypotézy měly / mají dívky o příčině onemocnění? Zjištění diskutujeme v kontextu jiných publikovaných, podobně zaměřených výzkumů. and Four Czech and one Slovak portal dedicated to health matters were used as a research source here. The content analysis of 378 stories collected from 259 girls was the source of the most frequently mentioned factors contributing to the development of eating disorders of adolescent girls. Using the qualitative content analysis of the texts from the discussions we have searched for subjective meaning, which the girls have assigned as the main factors of this disorder’s occurrence. The research questions were formulated: Which factors were perceived by girls as important at the time of the disorder’s onset? What hypotheses were used by the girls to explain the disorder’s cause?
E-government becomes an important element of the emerging e-societies. There is a great diversity of strategies, policies and results related to its introduction. Educational and cultural conditions and possibilities are vital because they generate - or not - interests in ICTs and their various applications. So capacity building for e-government is a coplex porcess, not limited to introduciton of technological and organizational actions. Moreover e-government is costly and will require soon not only social but also econimic evaluation. These issues are explored in an illustrative case study of e-services in Poland. and Lech W. Zacher, Tomasz Białobłocki
The Internet has become an important source of information for physicians seeking immediate data for the management of patients and for those developing decision-making methodologies and guidelines for clinical practice. In this study, components and subsystems of a medical decision support system are presented. An artificial neural network model, which is one of the subsystems of the differential diagnosis component, has been proposed as a reasoning tool to support medical diagnosis. The input data of artificial neural network models used in different medical diagnosis can be obtained via the Internet. The present study is concerned with the application of artificial neural network model to diabetes prediction. Demographic and medical data of diabetics and non-diabetics obtained via the Internet were used as the artificial neural network inputs. The accuracy of the neural network's results has shown that the diabetes prediction is feasible by the neural network described in this study.