This book provides an introduction to and a dynamic description of a new psychological paradigm that balances the excesses and distortions of the positive psychology paradigm. It offers valuable theoretical and practical content to its readers on the vital need for, nature of and potential for the reality psychology paradigm. It includes concrete steps for this new paradigm to restore the real power of vital psychological knowledge and techniques, which need to be brought back from their association with artificial positivity. This will provide real human benefits, including real mindfulness, real resilience, real behaviour change, and real communication. The book features a presentation of the underlying principles of reality psychology - including the value of a full connection with reality as it really is - rather than as we would like it to be. This will help people thrive in response to as well as survive our great real-life challenges, by developing a deeply practical understanding of reality psychology knowledge and related practice techniques. The book provides considerable theoretical and practical benefits to students of a variety of psychological courses, including positive psychology related courses, and also of many other wellbeing related courses. The book also provides valuable benefits to non-student readers - expert and non-expert.

This book describes mindfulness and meditation practices and programs for adolescents by situating the topic in a bio-psychosocial-cultural approach. Using this framework, the benefits of these practices and programs for adolescents- with an emphasis on evidence-based practices-are explored. In addition to programs based on mindfulness, meditation programs using Transcendental Meditation, Herbert Benson's Relaxation Response, and the Center for Mind Body Medicine's group programs are discussed. The book is targeted toward educators, mental health professionals, researchers, and graduate students interested in the application, development, and study of mindfulness and meditation practices and programs for adolescents.

In the World Library of Psychologists series, international experts present career-long collections of what they judge to be their finest pieces - extracts from books, key articles, salient research findings, and their major practical theoretical contributions. In this fascinating collection, Professor Gordon Claridge charts the development of a model of mental health that blurs the line between madness and sanity, conditions such as schizophrenia and other forms of psychosis seen as dimensions of 'normal' personality and temperament rather than separate abnormalities. Working with, and influenced by, the late Hans Eysenck, Claridge is celebrated for evolving research on personality and psychological disorders into a revised view of the spectrum of psychotic traits. The concept of schizotypy, re-evaluated by Claridge, sees mental illness not as a pathology suffered by a few, but as the end of a continuum experienced by us all. Psychopathology and Personality Dimensions brings together some of the author's most influential publications on the topics of schizotypy and psychoticism, personality disorders, and the use of drug techniques to investigate normal and abnormal individual differences. Interspersed throughout with specially-written retrospectives by Professor Claridge, looking back at his work and contextualising where it sits in the wider literature, the collection illustrates a radical and influential model of mental illness that continues to resonate today. This book is an essential resource for all those engaged or interested in the field of personality and psychological disorders.

This work brings together different perspectives on psychological methods and particularly methods involving experimentation. To encourage a reflective use of research methods, the authors illuminate the historical, philosophical, and scientific dimensions of methodology, providing both defenses and criticisms of experimental psychology. The primary audience of the work are students and researchers in psychological and behavioral sciences, who have an interest in methodology

Neuropsychology for Occupational Therapists is a bestselling, comprehensive guide to the assessment and rehabilitation of impaired cognitive function and brain damage. Divided into two parts, the first introduces the fundamental role cognition has in occupational performance, before moving on to examine the theoretical frameworks behind cognitive rehabilitation. The second part covers the key components of each cognitive function, including attention, visual perception, movement, memory, and executive functions, and the disorders associated with them. Revised throughout, this invaluable new edition includes: * Updated theory and evidence base of neuropsychology * Frameworks and guidelines for assessment and intervention in practice * Updated content on attention, memory and executive functions * A new chapter on cognitive function in later years, and working with people to maintain cognitive health. Written in a clear and engaging style by an experienced author team of academic occupational therapists, with contributions from expert practising clinicians, it is full of a range of learning features, including case studies, summaries, and reflective activities, as well as for the first time narratives of the lived experience of cognitive impairment. Neuropsychology for Occupational Therapists is essential reading for students, newly qualified practitioners, and all those who work within neuropsychology and cognitive rehabilitation.

Many technological, socio-economic, environmental, biomedical phenomena exhibit an underlying graph structure. Valued graph allows one to incorporate the connections or links among the population units in addition. The links may provide effectively access to the part of population that is the primary target, which is the case for many unconventional sampling methods, such as indirect, network, line-intercept or adaptive cluster sampling. Or, one may be interested in the structure of the connections, in terms of the corresponding graph properties or parameters, such as when various breadth- or depth-first non-exhaustive search algorithms are applied to obtain compressed views of large often dynamic graphs. Graph sampling provides a statistical approach to study real graphs from either of these perspectives. It is based on exploring the variation over all possible sample graphs (or subgraphs) which can be taken from the given population graph, by means of the relevant known sampling probabilities. The resulting design-based inference is valid whatever the unknown properties of the given real graphs. One-of-a-kind treatise of multidisciplinary topics relevant to statistics, mathematics and data science. Probabilistic treatment of breadth-first and depth-first non-exhaustive search algorithms in graphs. Presenting cutting-edge theory and methods based on latest research. Pathfinding for future research on sampling from real graphs. Graph Sampling can primarily be used as a resource for researchers working with sampling or graph problems, and as the basis of an advanced course for post-graduate students in statistics, mathematics and data science.

El trabajo aborda una serie de criterios psicopedagogicos, que deben tenerse en cuenta para la formacion de valores tales como: En que sujetos deseamos educar valores?. Que valores posee ese joven universitario?. Cual es su nivel de motivacion profesional? Cuales valores educar? Como concebir a la personalidad? De cuales principios psicopedagogicos partir? Estos criterios fueron la base de la metodologia elaborada para la formacion de valores desde la disciplina Gestion del Talento Humano, en la Universidad Agostinho Neto, cuyos pasos se muestran a continuacion. Primer paso: Realizar un diagnostico inicial. Segundo paso: disenar el proyecto educativo de la disciplina. Tercer paso: realizar un diagnostico de salida. La puesta en practica de dicha metodologia durante varios anos, ha permitido incrementar la eficiencia y eficacia del proceso de ensenanza aprendizaje, lo cual se manifiesta en una mejor preparacion cientifico-tecnica y moral de los egresados. Palabras Claves: Formacion de Valores

The topic of consciousness is truly multidisciplinary, attracting researchers and theorists from diverse backgrounds. It is now widely accepted that previously disparate areas all have contributions to make to the understanding of the nature of consciousness. Thus, we now have computational scientists, neuroscientists, and philosophers all engaged in the same effort. This book illustrates these three approaches, with chapters provided by some of the most important and provocative figures in the field. The first section is concerned with philosophical approaches to consciousness. One of the fundamental issues here is that of subjective feeling or qualia. The second section focuses on approaches from cognitive neuroscience. Patients with different types of neurological problems, and new imaging techniques, provide rich sources of data for studying how consciousness relates to brain function. The third section includes computational approaches looking at the quantitative relationship between brain processes and conscious experience. Cognition, Computation, and Consciousness represents a uniquely integrated and current account of this most fascinating and intractable subject.

Data Analytics for the Social Sciences is an introductory, graduate-level treatment of data analytics for social science. It features applications in the R language, arguably the fastest growing and leading statistical tool for researchers. The book starts with an ethics chapter on the uses and potential abuses of data analytics. Chapters 2 and 3 show how to implement a broad range of statistical procedures in R. Chapters 4 and 5 deal with regression and classification trees and with random forests. Chapter 6 deals with machine learning models and the "caret" package, which makes available to the researcher hundreds of models. Chapter 7 deals with neural network analysis, and Chapter 8 deals with network analysis and visualization of network data. A final chapter treats text analysis, including web scraping, comparative word frequency tables, word clouds, word maps, sentiment analysis, topic analysis, and more. All empirical chapters have two "Quick Start" exercises designed to allow quick immersion in chapter topics, followed by "In Depth" coverage. Data are available for all examples and runnable R code is provided in a "Command Summary". An appendix provides an extended tutorial on R and RStudio. Almost 30 online supplements provide information for the complete book, "books within the book" on a variety of topics, such as agent-based modeling. Rather than focusing on equations, derivations, and proofs, this book emphasizes hands-on obtaining of output for various social science models and how to interpret the output. It is suitable for all advanced level undergraduate and graduate students learning statistical data analysis.

"Automated scoring engines [...] require a careful balancing of the contributions of technology, NLP, psychometrics, artificial intelligence, and the learning sciences. The present handbook is evidence that the theories, methodologies, and underlying technology that surround automated scoring have reached maturity, and that there is a growing acceptance of these technologies among experts and the public." From the Foreword by Alina von Davier, ACTNext Senior Vice President Handbook of Automated Scoring: Theory into Practice provides a scientifically grounded overview of the key research efforts required to move automated scoring systems into operational practice. It examines the field of automated scoring from the viewpoint of related scientific fields serving as its foundation, the latest developments of computational methodologies utilized in automated scoring, and several large-scale real-world applications of automated scoring for complex learning and assessment systems. The book is organized into three parts that cover (1) theoretical foundations, (2) operational methodologies, and (3) practical illustrations, each with a commentary. In addition, the handbook includes an introduction and synthesis chapter as well as a cross-chapter glossary.

Requires minimal prerequisites Explained in basic terms Illustrated with binary datasets and real life examples Covers primary concepts and methods Accessible to undergraduates Suitable for a heterogeneous audience

Interpreting Basic Statistics gives students valuable practice in interpreting statistical reporting as it actually appears in peer-reviewed journals. Features of the ninth edition: * Covers a broad array of basic statistical concepts, including topics drawn from the New Statistics * Up-to-date journal excerpts reflecting contemporary styles in statistical reporting * Strong emphasis on data visualization * Ancillary materials include data sets with almost two hours of accompanying tutorial videos, which will help students and instructors apply lessons from the book to real-life scenarios About this book Each of the 63 exercises in the book contain three central components: 1) an introduction to a statistical concept, 2) a brief excerpt from a published research article that uses the statistical concept, and 3) a set of questions (with answers) that guides students into deeper learning about the concept. The questions on the journal excerpts promote learning by helping students * interpret information in tables and figures, * perform simple calculations to further their interpretations, * critique data-reporting techniques, and * evaluate procedures used to collect data. The questions in each exercise are divided into two parts: (1) Factual Questions and (2) Questions for Discussion. The Factual Questions require careful reading for details, while the discussion questions show that interpreting statistics is more than a mathematical exercise. These questions require students to apply good judgment as well as statistical reasoning in arriving at appropriate interpretations. Each exercise covers a limited number of topics, making it easy to coordinate the exercises with lectures or a traditional statistics textbook.

This step-by-step guide shows you how to use R to get data analysis right. The book explores the entire process of analysis, covering key steps from preparing your data to putting your analysis together and writing up your findings. It helps you get to grips with doing different statistical techniques in R and: Equips you with practical data visualisation tools to create graphs and tables. Shows you how to prepare and present your research for assessment, publication and dissemination. Covers key issues facing today's social scientists, such as making research reproducible. Features include an introduction to each chapter, and end-of-chapter exercises to check your understanding of the material. The online resources for this text include data sets that you can perform your own analysis on, and links to publications that are relevant to programming with R. A good starting point for any postgraduate student conducting a research project, this book will help you develop your statistics and programming knowledge and get quickly up to speed.

This book provides an overview of the developments in the area of Bayesian evaluation of informative hypotheses that took place since the publication of the ?rst paper on this topic in 2001 [Hoijtink, H. Con?rmatory latent class analysis, model selection using Bayes factors and (pseudo) likelihood ratio statistics. Multivariate Behavioral Research, 36, 563-588]. The current state of a?airs was presented and discussed by the authors of this book during a workshop in Utrecht in June 2007. Here we would like to thank all authors for their participation, ideas, and contributions. We would also like to thank Sophie van der Zee for her editorial e?orts during the construction of this book. Another word of thanks is due to John Kimmel of Springer for his con?dence in the editors and authors. Finally, we would like to thank the Netherlands Organization for Scienti?c Research (NWO) whose VICI grant (453-05-002) awarded to the ?rst author enabled the organization of the workshop, the writing of this book, and continuation of the research with respect to Bayesian evaluation of informative hypotheses.

This book presents a critical examination of the development of user involvement within research, and investigates the issues currently preventing a productive integration of Mad knowledges within research and practice. Drawing on social, linguistic and critical theories, it proposes the conditions needed to address the development of Mad epistemologies. The author's unique approach deliberately highlights her own positionality and draws on decades of experience as a service recipient, survivor, activist and researcher to illustrate the structural and symbolic barriers faced. Employing concepts including epistemic injustice, individualization, normalization and structural violence, it suggests a radically new way of articulating 'what's the matter with us?' In doing so, the book itself goes some way towards enacting the radical challenge to academic and epistemic hierarchies which, it is argued, will be required to further advance mad knowledges and user-led research. Crucially, it demonstrates how this approach can be both methodologically and conceptually rigorous. This novel work holds important insights for students and scholars across the humanities and social sciences; particularly those working in the areas of critical psychology, disability studies, Mad studies, feminist studies, critical race theory, and Queer theory.

Learn How to Infuse Leadership into Your Passion for Scientific Research Leadership and Women in Statistics explores the role of statisticians as leaders, with particular attention to women statisticians as leaders. By paying special attention to women's issues, this book provides a clear vision for the future of women as leaders in scientific and technical fields. It also shows how emerging and current leaders of both genders in many disciplines can expand their leadership potentials. Featuring contributions from leadership experts and statisticians at various career stages, this unique and insightful text: Examines leadership within the roles of statistician and data scientist from international and diverse perspectives Supplies a greater understanding of leadership within teams, research consulting, and project management Encourages reflection on leadership behaviors, promoting both natural and organizational leadership Identifies existing opportunities to foster creative outputs and develop strong leadership voices Includes real-life stories about overcoming barriers to leadership Leadership and Women in Statistics explains how to convert a passion for statistical science into visionary, ethical, and transformational leadership. Although the context focuses on statistics, the material applies to almost all fields of endeavor. This book is a valuable resource for those ready to consider leadership as an important element of their careers, and for those who are already leaders but want to deepen their perspectives on leadership. It makes an ideal text for group leadership training as well as for individual professional development.

Whereas the diagnosis, explanation, and treatment of physical illness are scientifically sound, this is not true of psychiatric care of mental disorder. Depression, the #1 psychiatric diagnosis, illustrates this failure and it is the subject of Grifting Depression: Psychiatry's Failure as a Medical Science. Psychiatry's current form of medicalization began in 1980 with publication of DSM-III, the diagnostic manual that became the basis for the chemical imbalance theory, psychiatry's explanation for depression, and for reliance on antidepressant drugs to treat depression, "revolutionizing psychiatric care." DSM-III became the model for all the DSM manuals that followed. However, unlike other medical diagnostic manuals, the DSM fails to meet scientific and medical standards of reliability and validity. The chemical imbalance theory is based on research that violates basic tenets of the scientific method. Tests of the theory contradict it. In addition, tests of treatment effectiveness find antidepressant drugs to be no better than placebo. Studies show that the benefit attributed to antidepressant drugs is a placebo effect, but unlike placebos, the chemicals in these drugs are harmful to many. Research strongly supports an alternative theory, a behavioral explanation (psychological rather than biological) for most of the mental disorders listed in the DSM, including most cases of depression. Moreover, although it has not been recognized as the treatment of choice for depression, outcome studies convincingly show behavior therapy is more effective than drug treatment and it is safe. Conflict of interest, not science, is determining psychiatric care.

This book offers different theoretical approaches about what clinical research is. Clinical Research in Psychoanalysis is a unique contribution to the attempts to bridge the gap between clinicians and researchers and to create a culture of a more rigorous and systematic inquiry. It provides an innovative experience because for the first time different methods and perspectives were used to analyse one same clinical material. This was done by analysts from different working parties of the International Psychoanalytical Association (IPA), from a range of different schools of psychoanalytic thought. This allows the reader to have a vision of the different methods that are currently being used by some working parties of the IPA and to learn about the strengths of each one for certain situations and types of research. This book revaluates clinical research, intending to make links between the analysts working through the working parties and the different ways of thinking in clinical research. By covering key topics, such as how working parties can facilitate different types of research; the place of metaphor in psychoanalytic research and practice; and the future for psychoanalytic research, this text is a fruitful dialogue between different theoretical conceptions and between clinicians and researchers, that will expand our perspectives on the evidence we find in clinical material and will broaden our views on the patient. This book offers a unique and invaluable experience to psychologists and psychoanalysts who are trying to improve their clinical practice and bring research evidence into their psychoanalytic practice. It is an invaluable contribution to psychoanalytic training of candidates, teachers, and students.

This is the second edition of the comprehensive treatment of statistical inference using permutation techniques. It makes available to practitioners a variety of useful and powerful data analytic tools that rely on very few distributional assumptions. Although many of these procedures have appeared in journal articles, they are not readily available to practitioners. This new and updated edition places increased emphasis on the use of alternative permutation statistical tests based on metric Euclidean distance functions that have excellent robustness characteristics. These alternative permutation techniques provide many powerful multivariate tests including multivariate multiple regression analyses.

This book is a first attempt to combine insights from the two perspectives with regard to the question of meaning by examining a collection of theoretical and empirical works. This volume therefore is destined to become an important addition to psychological literature: both from the viewpoint of the history of ideas (again this would be one of the first times that positive and existentialist psychologies meet) and from the viewpoint of theoretical and empirical research into the meaning concept in psychology.

This is an international and interdisciplinary volume that provides a new look at the general background of the social sciences from a philosophical perspective and provides directions for methodology. It seeks to overcome the limitations of the traditional treatises of a philosophy of science rooted in the physical sciences, as well as extend the coverage of basic science to intentional and socially normative features of the social sciences. The discussions included in this book are divided into four thematic sections: Social and cognitive roots for reflexivity upon the research process Philosophies of explanation in the social sciences Social normativity in social sciences Social processes in particular sciences Social Philosophy of Science for the Social Sciences will find an interested audience in students of the philosophy of science and social sciences. It is also relevant for researchers and students in the fields of psychology, sociology, economics, anthropology, education, and political science.

This book proposes a novel view to explain how we as humans -- contrary to current robots -- can have the impression of consciously feeling things: for example the red of a sunset, the smell of a rose, the sound of a symphony, or a pain.
The book starts off by looking at visual perception. Our ability to see turns out to be much more mysterious than one might think. The eye contains many defects which should seriously interfere with vision. Yet we have the impression of seeing the world in glorious panavision and technicolor. Explaining how this can be the case leads to a new idea about what seeing really is. Seeing is not passively receiving information in the brain, but rather a way of interacting with the world. The role of the brain is not to create visual sensation, but to enable the necessary interactions with the world.
This new approach to seeing is extended in the second part of the book to encompass the other senses: hearing, touch, taste and smell. Taking sensory experiences to be modes of interacting with the world explains why these experiences are different in the way they are. It also explains why thoughts or automatic functions in the body, and indeed the vast majority brain functions, are not accompanied by any real feeling.
The "sensorimotor" approach is not simply a philosophical argument: It leads to scientifically verifiable predictions and new research directions. Among these are the phenomena of change blindness, sensory substitution, "looked but failed to see," as well as results on color naming and color perception and the localisation of touch on the body.
The approach is relevant to the question of what animals and babies can feel, and to understanding what will be necessary for robots to become conscious.

How to Use SPSS (R) is designed with the novice computer user in mind and for people who have no previous experience using SPSS. Each chapter is divided into short sections that describe the statistic being used, important underlying assumptions, and how to interpret the results and express them in a research report. The book begins with the basics, such as starting SPSS, defining variables, and entering and saving data. It covers all major statistical techniques typically taught in beginning statistics classes, such as descriptive statistics, graphing data, prediction and association, parametric inferential statistics, nonparametric inferential statistics and statistics for test construction. More than 270 screenshots (including sample output) throughout the book show students exactly what to expect as they follow along using SPSS. The book includes a glossary of statistical terms and practice exercises. A complete set of online resources including video tutorials and output files for students, and PowerPoint slides and test bank questions for instructors, make How to Use SPSS (R) the definitive, field-tested resource for learning SPSS. New to this edition: Now in full color with additional screenshots Fully updated to the reflect SPSS version 26 (and prior versions) Changes in nonparametric tests Model View incorporated Data and real output are now available for all Phrasing Results sections - eliminating hypothetical output or hypothetical data

Single-Case Methods in Clinical Psychology: A Practical Guide provides a concise and easily-accessible introduction to single-case research. This is a timely response to the increasing awareness of the need to look beyond randomised controlled trials for evidence to support best practice in applied psychology. The book covers the issues of design, the reliability and validity of measurement, and provides guidance on how to analyse single-case data using both visual and statistical methods. Single-case designs can be used to investigate an individual's response to psychological intervention, as well as to contribute to larger scale research projects. This book illuminates the common principles behind these uses. It describes how standardised measures can be used to evaluate change in an individual and how to develop idiographic measures that are tailored to the needs of an individual. The issue of replication and generalising beyond an individual are examined, and the book also includes a section on the meta-analysis of single-case data. The critical evaluation of single-case research is examined, from both the perspective of developing quality standards to evaluate research and maintaining a critical distance in reviewing one's own work. Single Case Methods in Clinical Psychology will provide invaluable guidance to postgraduate psychologists training to enter the professions of clinical, health and counselling psychology and is likely to become a core text on many courses. It will also appeal to clinicians seeking to answer questions about the effectiveness of therapy in individual cases and who wish to use the method to further the evidence-base for specific psychological interventions.