Transgenerational Transmission of Addiction Problems

This paper aims to evaluate the possible transgenerational transmission of a mechanism of addiction triggered by a specific type of attachment and the prevalence of psychological trauma in the descendants. 22 adults (alcoholics, drug addicts, and heroin addicts) aged 23 to 56 followed in an addictology treatment centre are participated. Measurements: We evaluated the prevalence of family ascendants on our population using two semi structured interviews and a genogram. Potential psychological trauma was measured with the Child Trauma Questionnaire (CTQ) and the quality of attachment with the Attachment Style Questionnaire (ASQ). Findings: 95% of patients have direct ascendants who suffer from addiction. 86% of patients suffered emotional negligence during childhood. Physical abuse is frequent (41%) as well as emotional abuse (50%), which proves a form of mistreatment and explains the presence of an insecure attachment. Conclusion: Addicts have often been neglected and have lived in emotional deprivation during childhood, which is the reason for an insecure attachment. The ascendants, who often suffer from addiction themselves, have, because of their pathology, contributed to a possible transgenerational transmission of the mechanism of addiction via the quality of the affective links with their children.

DESIGN METHODOLOGY OF NETWORKED SOFTWARE EVOLUTION GROWTH BASED ON SOFTWARE PATTERNS

Recently, some new characteristics of complex networks attract the attentions of scientist, in different fields, and lead to many kinds of emerging research directions. So far, most of the researcl work has been limited in discovery of complex network characteristics by structure analysis in large-scale software systems. This paper presents the theoretical basis, design method, algorithms and experiment results of the research. It firstly emphasizes the significance of design method of evolution growth for network topology of Object Oriented （OO） software systems, and argues that the selection and modulation of network models with various topology characteristics will bring un-ignorable effect on the process, of design and implementation of OO software systems. Then we analyze the similar discipline of ＂negation of negation and compromise＂ between the evolution of network models with different topology characteristics and the development of software modelling methods. According to the analysis of the growth features of software patterns, we propose an object-oriented software network evolution growth method and its algorithms in succession. In addition, we also propose the parameter systems for OO software system metrics based on complex network theory. Based on these parameter systems, it can analyze the features of various nodes, links and local-world, modulate the network topology and guide the software metrics. All these can be helpful to the detailed design, implementation and performance analysis. Finally, we focus on the application of the evolution algorithms and demonstrate it by a case study. Comparing the results from our early experiments with methodologies in empirical software engineering, we believe that the proposed software engineering design method is a computational software engineering approach based on complex network theory. We argue that this method should be greatly beneficial for the design, implementation, modulation and metrics of functionality, structure and performance in large-scale OO software complex system.