Lesbian, gay, bisexual, trans and queer psychology:an introduction

This exciting and engaging textbook introduces students to the psychology of lesbian, gay, bisexual, trans and queer lives and experiences. It covers a broad range of topics including diversity, prejudice, health, relationships, parenting and lifespan experiences from youth to old age. The book includes ‘key researcher’ boxes, which outline the contributions of significant individuals and their motivations for conducting their research in their own words. Key issues and debates are discussed throughout the book, and questions for discussion and classroom exercises help students reflect critically and apply their learning. There are extensive links to further resources and information, as well as ‘gaps and absences’ sections, indicating major limitations of research in a particular area. This is the essential textbook for anyone studying LGBTQ Psychology, Psychology of Sexuality or related courses. It is also a useful supplement to courses on Gender and Developmental Psychology.

Development of a probabilistic graphical structure from a model of mental health clinical expertise

This thesis explores the process of developing a principled approach for translating a model of mental-health risk expertise into a probabilistic graphical structure. Probabilistic graphical structures can be a combination of graph and probability theory that provide numerous advantages when it comes to the representation of domains involving uncertainty, domains such as the mental health domain. In this thesis the advantages that probabilistic graphical structures offer in representing such domains is built on. The Galatean Risk Screening Tool (GRiST) is a psychological model for mental health risk assessment based on fuzzy sets. In this thesis the knowledge encapsulated in the psychological model was used to develop the structure of the probability graph by exploiting the semantics of the clinical expertise. This thesis describes how a chain graph can be developed from the psychological model to provide a probabilistic evaluation of risk that complements the one generated by GRiST’s clinical expertise by the decomposing of the GRiST knowledge structure in component parts, which were in turned mapped into equivalent probabilistic graphical structures such as Bayesian Belief Nets and Markov Random Fields to produce a composite chain graph that provides a probabilistic classification of risk expertise to complement the expert clinical judgements

Developing a probabilistic graphical structure from a model of mental-health clinical risk expertise

This paper explores the process of developing a principled approach for translating a model of mental-health risk expertise into a probabilistic graphical structure. The Galatean Risk Screening Tool [1] is a psychological model for mental health risk assessment based on fuzzy sets. This paper details how the knowledge encapsulated in the psychological model was used to develop the structure of the probability graph by exploiting the semantics of the clinical expertise. These semantics are formalised by a detailed specification for an XML structure used to represent the expertise. The component parts were then mapped to equivalent probabilistic graphical structures such as Bayesian Belief Nets and Markov Random Fields to produce a composite chain graph that provides a probabilistic classification of risk expertise to complement the expert clinical judgements. © Springer-Verlag 2010.