Sociologists and anthropologists have had a long interest in studying the ways in which cultures shaped different patterns of health, disease, and mortality. Social scientists have documented low rates of chronic disease and disability in non-Western societies and have suggested that social stability, cultural homogeneity and social cohesion may play a part in explaining these low rates. On the other hand, in studies of Western societies, social scientists have found that disease and mortality assume different patterns among various ethnic, cultural and social-economic groups. The role of stress, social change and a low degree of cohesion have been suggested, along with other factors as contributing to the variable rates among different social groups. Social cohesion has been implicated in the cause and recovery from both physical and psychological illnesses. Although there has been a large amount of work established the beneficial effects of cohesion on health and well-being, relatively little work has focused on HOW increased social cohesion sustains or improves health. This work is based on the premise that there are risk factors, including social cohesion that regulate health and disease in groups. One of the challenges is how to measure social cohesion – it can be readily observed and experienced but difficult to quantify. A better understanding of how social cohesion works will be valuable to improving group-level interventions.
"We've all been involved in group decisions--and they're hard. And they often turn out badly. Why? Many blame bad decisions on 'groupthink' without a clear idea of what that term really means. Now, Nudge coauthor Cass Sunstein and leading decision-making scholar Reid Hastie shed light on the specifics of why and how group decisions go wrong--and offer tactics and lessons to help leaders avoid the pitfalls and reach better outcomes"--Dust jacket flap.
In this volume, Carey and Asbury provide a brief, systematic introduction to developing, implementing, and analyzing focus groups in research projects.
This book constitutes the proceedings of the 14th European Conference on Technology Enhanced Learning, EC-TEL 2019, held in Delft, The Netherlands, in September 2019. The 41 research papers and 50 demo and poster papers presented in this volume were carefully reviewed and selected from 149 submissions. The contributions reflect the debate around the role of and challenges for cutting-edge 21st century meaningful technologies and advances such as artificial intelligence and robots, augmented reality and ubiquitous computing technologies and at the same time connecting them to different pedagogical approaches, types of learning settings, and application domains that can benefit from such technologies.
This two-volume encyclopedia covers concepts from across the spectrum, from group phenomena to phenomena influenced by group membership, from small group interaction to intergroup relations on a global scale.
Contextual analysis, the study of the role of the group context on actions and attitudes of individuals, is a useful technique in the study of education, neighborhoods, census tracts, election districts, and the family. However, the effective use of contextual analysis has involved overcoming a number of issues, such as group boundaries, the mobility of the individuals within a group, overlapping groups, missing individual data, and the choice of statistical models. Contextual Analysis offers researchers a guide for selecting the best model to use. Written in a straightforward style, the book explores such topics as contextual analysis with absolute effects, with relative effects, and the choice between regression coefficients as fixed parameters or as random variables.
Longitudinal Analysis provides an accessible, application-oriented treatment of introductory and advanced linear models for within-person fluctuation and change. Organized by research design and data type, the text uses in-depth examples to provide a complete description of the model-building process. The core longitudinal models and their extensions are presented within a multilevel modeling framework, paying careful attention to the modeling concerns that are unique to longitudinal data. Written in a conversational style, the text provides verbal and visual interpretation of model equations to aid in their translation to empirical research results. Overviews and summaries, boldfaced key terms, and review questions will help readers synthesize the key concepts in each chapter. Written for non-mathematically-oriented readers, this text features: A description of the data manipulation steps required prior to model estimation so readers can more easily apply the steps to their own data An emphasis on how the terminology, interpretation, and estimation of familiar general linear models relates to those of more complex models for longitudinal data Integrated model comparisons, effect sizes, and statistical inference in each example to strengthen readers’ understanding of the overall model-building process Sample results sections for each example to provide useful templates for published reports Examples using both real and simulated data in the text, along with syntax and output for SPSS, SAS, STATA, and Mplus at www.PilesOfVariance.com to help readers apply the models to their own data The book opens with the building blocks of longitudinal analysis—general ideas, the general linear model for between-person analysis, and between- and within-person models for the variance and the options within repeated measures analysis of variance. Section 2 introduces unconditional longitudinal models including alternative covariance structure models to describe within-person fluctuation over time and random effects models for within-person change. Conditional longitudinal models are presented in section 3, including both time-invariant and time-varying predictors. Section 4 reviews advanced applications, including alternative metrics of time in accelerated longitudinal designs, three-level models for multiple dimensions of within-person time, the analysis of individuals in groups over time, and repeated measures designs not involving time. The book concludes with additional considerations and future directions, including an overview of sample size planning and other model extensions for non-normal outcomes and intensive longitudinal data. Class-tested at the University of Nebraska-Lincoln and in intensive summer workshops, this is an ideal text for graduate-level courses on longitudinal analysis or general multilevel modeling taught in psychology, human development and family studies, education, business, and other behavioral, social, and health sciences. The book’s accessible approach will also help those trying to learn on their own. Only familiarity with general linear models (regression, analysis of variance) is needed for this text.
Based on cutting-edge NIH studies, a practical, accessible guide to yoga for reduction in stress, anxiety, and depression, with the goal of balanced emotional health. The Yoga Effect helps readers overcome the de-energizing effects of depression and move into a state of calm and focus. Based on the program developed through three NIH-funded studies at Boston University School of Medicine, these sequences are medically proven to trigger a physical and mental release of fear and worry. The book offers: A customizable prescription for maintaining centeredness, confidence, and balance Straightforward, accessible sequences, with 40 black & white photos clearly illustrating the poses A short, well-rounded practice that includes breath work and poses with clear explanation of how each sequence contributes to physical, mental, and emotional wellness Differing levels of practice for readers' varying levels of physical abilities Written with an MD, The Yoga Effect is a proven pathway for cultivating inner strength that can be accessed at any time, offering hope and a solution for anyone looking to transform their mental and emotional health.
