Capacity Updating Rules and Rational Belief Change

Choquet expected utility substitutes capacities for subjective probabilities to explain uncertainty aversion and related phenomena. This paper studies capacities as models of belief. The notions of inner and outer acceptance context are defined. These are shown to be the natural acceptance contexts when belief expansion is described by naïve Bayesian and Dempster–Shafer updating of capacities respectively. We also show that Eichberger and Kelsey's (1999b) use of Dempster–Shafer updating as a model of belief revision may lead to violations of the AGM axioms for rational belief change.     

Building Citizenship: How Student Voice in Service-Learning Develops Civic Values

Objective . Though many decry the decline in political participation and interest, few academic studies present a clear approach to help reverse these trends. This paper examines the impact of service-learning programs on students' self-concept, political engagement, and attitudes toward out-groups. Methods . The data come from a pre and post survey given to more than 200 high school students in 10 different schools. We use Huber regression to assess the impact of student voice in the service-learning project on six dependent variables. Results . We show that if students are involved in service-learning projects in which they have a high degree of voice and ownership, their self-concept and political engagement will improve, and they become more tolerant toward out-groups. Conclusion . In short, having a voice in service-learning programs builds citizenship.     

Demographic,Behavioural and Normative Risk Factors for Gambling Problems Amongst Sports Bettors

Sports betting is growing exponentially, is heavily marketed and successfully targets young adult males. Associated gambling problems are increasing. Therefore, understanding risk factors for problem gambling amongst sports bettors is an increasingly important area of research to inform the appropriate design and targeting of public health and treatment interventions. This study aimed to identify demographic, behavioural and normative risk factors for gambling problems amongst sports bettors. An online survey of 639 Australian sports bettors using online, telephone and retail betting channels was conducted. Results indicated that vulnerable sports bettors for higher risk gambling are those who are young, male, single, educated, and employed full-time or a full-time student. Risk of problem gambling was also found to increase with greater frequency and expenditure on sports betting, greater diversity of gambling involvement, and with more impulsive responses to betting opportunities, including in-play live action betting. Normative influences from media advertising and from significant others were also associated with greater problem gambling risk. The results of this study can inform a suite of intervention, protection and treatment initiatives targeted especially at young male adults and adolescents that can help to limit the harm from this gambling form.     

Age Similarities in Interpersonal Perception and Conversation Ability

Older adults tend to perform worse on emotion perception tasks compared to younger adults. How this age difference relates to other interpersonal perception tasks and conversation ability remains an open question. In the present study, we assessed 32 younger and 30 older adults’ accuracy when perceiving (1) static facial expressions, (2) emotions, attitudes, and intentions from videos, (3) and interpersonal constructs (e.g., kinship). Participants’ conversation ability was rated by coders from a videotaped, dyadic problem-solving task. Younger adults were more accurate than older adults perceiving some but not all emotions. No age differences in accuracy were found on any perception task or in conversation ability. Some but not all of the interpersonal perception tasks were related. None of the perception tasks predicted conversation ability. Thus, although the literature suggests a robust age difference in emotion perception accuracy, this difference does not seem to transfer to other interpersonal perception tasks or interpersonal outcomes.     

Vocational Identity Resources in Emerging Adulthood: Associations With Facets of Dispositional Mindfulness

The processes of career development and forming a crystallized identity can be fraught with emotional turmoil. One multidimensional construct known to reduce emotional reactivity is dispositional mindfulness (DM). We used canonical correlation analysis to examine relationships involving measures of resources for establishing a vocational identity (Hirschi, 2012a) and facets of DM in emerging adults (134 women, 38 men). Observing, describing, and nonreactivity to inner experiences contributed uniquely to the first canonical function with career agency and occupational engagement. Observing, describing, and nonjudging contributed uniquely to the second function with occupational engagement and negative career outlook. These results shed light on key facets of DM that help emerging adults to effectively utilize emotion within the context of career‐life planning. Future research should examine relationships between DM facets and additional constructs subsumed within the career resources model. Counselors may find utility in understanding how clients conceptualize conscious emotional experience and use it in career‐life planning.     

Designing and analyzing clinical trials for personalized medicine via Bayesian models

Patients with different characteristics (e.g., biomarkers, risk factors) may have different responses to the same medicine. Personalized medicine clinical studies that are designed to identify patient subgroup treatment efficacies can benefit patients and save medical resources. However, subgroup treatment effect identification complicates the study design in consideration of desired operating characteristics. We investigate three Bayesian adaptive models for subgroup treatment effect identification: pairwise independent, hierarchical, and cluster hierarchical achieved via Dirichlet Process (DP). The impact of interim analysis and longitudinal data modeling on the personalized medicine study design is also explored. Interim analysis is considered since they can accelerate personalized medicine studies in cases where early stopping rules for success or futility are met. We apply integrated two-component prediction method (ITP) for longitudinal data simulation, and simple linear regression for longitudinal data imputation to optimize the study design. The designs' performance in terms of power for the subgroup treatment effects and overall treatment effect, sample size, and study duration are investigated via simulation. We found the hierarchical model is an optimal approach to identifying subgroup treatment effects, and the cluster hierarchical model is an excellent alternative approach in cases where sufficient information is not available for specifying the priors. The interim analysis introduction to the study design lead to the trade-off between power and expected sample size via the adjustment of the early stopping criteria. The introduction of the longitudinal modeling slightly improves the power. These findings can be applied to future personalized medicine studies with discrete or time-to-event endpoints.     

An Integrated Physical Dispersion and Behavioral Response Model for Risk Assessment of Radiological Dispersion Device (RDD) Events

A radiological dispersion device (RDD) or "dirty" bomb is a conventional explosive wrapped in radiological material. Terrorists may use an RDD to disperse radioactive material across a populated area, causing casualties and/or economic damage. Nearly all risk assessment models for RDDs make unrealistic assumptions about public behavior in their health assessments, including assumptions that the public would stand outside in a single location indefinitely. In this article, we describe an approach for assessing the risks of RDD events incorporating both physical dispersion and behavioral response variables. The general approach is tested using the City of Pittsburgh, Pennsylvania as a case study. Atmospheric models simulate an RDD attack and its likely fallout, while radiation exposure models assess fatal cancer risk. We model different geographical distributions of the population based on time of day. We evaluate aggregate health impacts for different public responses (i.e., sheltering-in-place, evacuating). We find that current RDD models in use can be improved with the integration of behavioral components. Using the results from the model, we show how risk varies across several behavioral and physical variables. We show that the best policy to recommend to the public depends on many different variables, such as the amount of trauma at ground zero, the capability of emergency responders to get trauma victims to local hospitals quickly and efficiently, how quickly evacuations can take place in the city, and the amount of shielding available for shelterers. Using a parametric analysis, we develop behaviorally realistic risk assessments, we identify variables that can affect an optimal risk reduction policy, and we find that decision making can be improved by evaluating the tradeoff between trauma and cancer fatalities for various RDD scenarios before they occur.     

Natural disaster and risk-sharing behavior: Evidence from rural Bangladesh

Journal of Risk and Uncertainty - Using a unique field experiment in rural Bangladesh, this paper investigates how exposure to a natural disaster affects risk-sharing behavior. We conducted a...