The Greater Ability of Graphical Versus Numerical Displays to Increase Risk Avoidance Involves a Common Mechanism

By displaying a risk reduction of 50% graphically rather than numerically, Stone, Yates, and Parker significantly increased professed risk-avoidant behavior. The current experiments replicated this effect at various risk ratios. Specifically, participants were willing to spend more money to reduce a risk when the risk information was displayed by asterisks rather than by numbers for risk-reduction ratios ranging from 3% to 97%. Transforming the amount participants were willing to spend to logarithms significantly improved a linear fit to the data, suggesting that participants convert this variable within the decision-making process. Moreover, a log-linear model affords an exceptional fit to both the graphical and numerical data, suggesting that a graphical presentation elicits the same decision-making mechanism as does the numerical display. In addition, the data also suggest that each person removed from harm is weighted more by some additional factor in the graphical compared to the numerical presentations.     

To participate or not to participate: that is the question

Do I wish to participate or not to participate in this program? That is the question that young people ask themselves when considering a new opportunity. What can be done to increase the likelihood that they will choose to participate in out-of-school-time (OST) programs? This chapter describes a qualitative study that examined reasons for participating or not participating in OST programs. Some common reasons emerged, but the study also revealed differences among youth from different ethnic groups. It is clear that those who design and conduct programs must understand the processes through which diverse adolescents initiate their participation in programs and either persist or drop out. Given the apparent benefits of active participation in youth programs, it is important to remove barriers and increase access and, equally important, design programs that are of interest to youth in the contexts in which they live.     

An economic analysis of public sector collective bargaining and strike activity

This paper develops a theory of public sector collective bargaining and uses it to investigate the economic determinants of public sector strike activity. The model considers union leaders, union members, bureaucrats, politicians, and voters, with the intention of explicitly recognizing both the constraints placed on the bargaining parties by their constituents and the differences between public and private sector collective bargaining. The empirical results indicate that only in cases where both negotiating parties are motivated by self-interest can we expect frequent strikes and strikes of long duration. The results also suggest that public sector strikes are countercyclical and principally influenced by the business cycle and its impact on state and local revenues.     

Making the health care delivery system accountable.

Accountability has become the fact of life for the health care provider and the delivery system. Until recently, accountability has been viewed primarily through the judicial process as issues of fraud and liability, or by managed care entities through evaluation of the financial bottom line. It is this second consideration and its ramifications that will be explored in this article. Appropriate measurement tools are needed to evaluate services, delivery, performance, customer satisfaction, and outcomes assessment. Measurement tools will be considered in light of the industry's unique considerations and realities. All participants, including insurers, employers, management, and health care providers and recipients, bear responsibilities which necessitate assessment and analysis. However, until the basic question, "Who is the customer?" is resolved, accountability issues remain complex and obscured. Accountability costs and impacts must be evaluated over time. They go way beyond bottom line cost containment and reduction. Accountability will be accomplished when the health care industry implements quality and measurement concepts that yield the highest levels of validity and appropriateness for health care delivery.     

Can a treatment be licenced on the basis of post‐treatment predictive biomarkers?

In recent years, there has been a great deal of literature published concerning the identification of predictive biomarkers and indeed, an increasing number of therapies have been licenced on this basis. However, this progress has been made almost exclusively on the basis of biomarkers measured prior to exposure to treatment. There are quite different challenges when the responding population can only be identified on the basis of outcomes observed following exposure to treatment, especially if it represents only a small proportion of patients. The purpose of this paper is to explore whether or when a treatment could be licenced on the basis of post‐treatment predictive biomarkers (PTPB), the focus is on oncology but the concepts should apply to all therapeutic areas. We review the potential pitfalls in hypothesising the presence of a PTPB. We also present challenges in trial design required to confirm and licence on the basis of a PTPB: what's the control population?, could there be a detriment to non‐responders by exposure to the new treatment?, can responders be identified rapidly?, could prior exposure to the new treatment adversely affect performance of the control in responders? Nevertheless, if the patients to be treated could be rapidly identified after prior exposure to treatment, and without harm to non‐responders, in appropriately designed and analysed trials, may be more targeted therapies could be made available to patients. Copyright © 2014 John Wiley & Sons, Ltd.