Identified Versus Statistical Lives

The identified lives effect describes the fact that people demonstrate a stronger inclination to assist persons and groups identified as at high risk of great harm than those who will or already suffer similar harm, but endure unidentified. As a result of this effect, we allocate resources reactively rather than proactively, prioritizing treatment over prevention. For example, during the August 2010 gold mine cave-in in Chile, where ten to twenty million dollars was spent by the Chilean government to rescue the 33 miners trapped underground. Rather than address the many, more cost effective mine safety measures that should have been implemented, the Chilean government and international donors concentrated efforts in large-scale missions that concerned only the specific group. Such bias as illustrated through this incident raises practical and ethical questions that extend to almost every aspect of human life and politics. What can social and cognitive sciences teach us about the origin and triggers of the effect? Philosophically and ethically, is the effect a "bias" to be eliminated or is it morally justified? What implications does the effect have for health care, law, the environment and other practice domains? This volume is the first to take an interdisciplinary approach toward answering this issue of identified versus statistical lives by considering a variety of perspectives from psychology, public health, law, ethics, and public policy.

The identified lives effect describes the fact that people demonstrate a stronger inclination to assist persons and groups identified as at high risk of great harm than those who will or already suffer similar harm, but endure unidentified. As a result of this effect, we allocate resources reactively rather than proactively, prioritizing treatment over prevention. For example, during the August 2010 gold mine cave-in in Chile, where ten to twenty million dollars was spent by the Chilean government to rescue the 33 miners trapped underground. Rather than address the many, more cost effective mine safety measures that should have been implemented, the Chilean government and international donors concentrated efforts in large-scale missions that concerned only the specific group. Such bias as illustrated through this incident raises practical and ethical questions that extend to almost every aspect of human life and politics. What can social and cognitive sciences teach us about the origin and triggers of the effect? Philosophically and ethically, is the effect a "bias" to be eliminated or is it morally justified? What implications does the effect have for health care, law, the environment and other practice domains? This volume is the first to take an interdisciplinary approach toward answering this issue of identified versus statistical lives by considering a variety of perspectives from psychology, public health, law, ethics, and public policy.

Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.

Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research--from funders, to researchers, to journals, to physicians, and ultimately, to patients.

On October 16 and 17, 2000, we hosted an international workshop entitled "Statistical Design, Measurement, and Analysis of Health Related Quality of Life." The workshop was held in the beautiful city of Arradon, South Brittany, France with the main goal of fostering an interdisciplinary forum for discussion of theoretical and applied statistical issues arising in studies of health-related quality of life (HRQoL). Included were biostatisticians, psychometricians and public health professionals (e.g., physicians, sociologists, psychologists) active in the study ofHRQoL. In assembling this volume, we invited each conference participant to contribute a paper based on his or her presentation and the ensuing and very interesting discussions that took place in Arradon. All papers were peer-reviewed, by anonymous reviewers, and revised before final editing and acceptance. Although this process was quite time consuming, we believe that it greatly improved the volume as a whole, making this book a valuable contribution to the field ofHRQoL research. The volume presents a broad spectrum of papers presented at the Workshop, and thus illustrates the range of current research related to the theory, methods and applications of HRQoL, as well as the interdisciplinary nature ofthis work. Following an introduction written by Sir David Cox, it includes 27 articles organized into the following chapters.

"Clinical versus Statistical Prediction" is Paul Meehl's famous examination of benefits and disutilities related to the different ways of combining information to make predictions. It is a clarifying analysis as relevant today as when it first appeared. A major methodological problem for clinical psychology concerns the relation between clinical and actuarial methods of arriving at diagnoses and predicting behavior. Without prejudging the question as to whether these methods are fundamentally different, we can at least set forth the obvious distinctions between them in practical applications. The problem is to predict how a person is going to behave: What is the most accurate way to go about this task? "Clinical versus Statistical Prediction" offers a penetrating and thorough look at the pros and cons of human judgment versus actuarial integration of information as applied to the prediction problem. Widely considered the leading text on the subject, Paul Meehl's landmark analysis is reprinted here in its entirety, including his updated preface written forty-two years after the first publication of the book. This classic work is a must-have for students and practitioners interested in better understanding human behavior, for anyone wanting to make the most accurate decisions from all sorts of data, and for those interested in the ethics and intricacies of prediction. As Meehl puts it, " "When one is dealing with human lives and life opportunities, it is immoral to adopt a mode of decision-making which has been demonstrated repeatedly to be either inferior in success rate or, when equal, costlier to the client or the taxpayer.""

In the United States, some populations suffer from far greater disparities in health than others. Those disparities are caused not only by fundamental differences in health status across segments of the population, but also because of inequities in factors that impact health status, so-called determinants of health. Only part of an individual's health status depends on his or her behavior and choice; community-wide problems like poverty, unemployment, poor education, inadequate housing, poor public transportation, interpersonal violence, and decaying neighborhoods also contribute to health inequities, as well as the historic and ongoing interplay of structures, policies, and norms that shape lives. When these factors are not optimal in a community, it does not mean they are intractable: such inequities can be mitigated by social policies that can shape health in powerful ways. Communities in Action: Pathways to Health Equity seeks to delineate the causes of and the solutions to health inequities in the United States. This report focuses on what communities can do to promote health equity, what actions are needed by the many and varied stakeholders that are part of communities or support them, as well as the root causes and structural barriers that need to be overcome.

Although most Canadians are familiar with surveillance cameras and airport security, relatively few are aware of the extent to which the potential for surveillance is now embedded in virtually every aspect of our lives. We cannot walk down a city street, register for a class, pay with a credit card, hop on an airplane, or make a telephone call without data being captured and processed. Where does such information go? Who makes use of it, and for what purpose? Is the loss of control over our personal information merely the price we pay for using social media and other forms of electronic communication, or should we be wary of systems that make us visible—and thus vulnerable—to others as never before? The work of a multidisciplinary research team, Transparent Lives explains why and how surveillance is expanding—mostly unchecked—into every facet of our lives. Through an investigation of the major ways in which both government and private sector organizations gather, monitor, analyze, and share information about ordinary citizens, the volume identifies nine key trends in the processing of personal data that together raise urgent questions of privacy and social justice. Intended not only to inform but to make a difference, the volume is deliberately aimed at a broad audience, including legislators and policymakers, journalists, civil liberties groups, educators, and, above all, the reading public. http://surveillanceincanada.org/