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...     

Fishing Households,Social Support,and Depression after the Deepwater Horizon Oil Spill

This study contributes to the growing body of knowledge on mental health in the aftermath of disasters by examining depressive symptoms among residents of the U.S. Gulf Coast region 6 years after the onset of the Deepwater Horizon oil spill (DHOS). Using data from the Survey of Trauma, Resilience, and Opportunity in Neighborhoods in the Gulf (STRONG), we test how social support and ties to the fishing industry are related to the likelihood of a positive depression screen. The results show that, among most residents of the Gulf Coast region, social support holds an inverse relationship with the likelihood of a positive depression screen. However, among fishing households, greater social support is associated with a higher probability of screening positive for depression. By showing that fishing households with greater social support are more susceptible to depressive symptoms in this setting, our results uncover a potentially important mechanism that contributes to the unique vulnerability of fishers, which in turn holds implications for differential impacts across social groups in environmental disaster contexts.     

MODERNIZATION,GENDER EQUALITY,AND MORTALITY RATES IN LESS DEVELOPED COUNTRIES

Although greater accessibility to health care and increasing levels of education among residents of less developed countries have clearly contributed to mortality decline, few theoretical models to date have adequately explained the relationship. A comprehensive model of mortality decline should document both the factors that directly drive down mortality rates and the underlying structural dynamics that give rise to such direct effects. The present article draws on fundamental diffusion concepts and a psychosociological model of modernization that attempts to explain how less developed countries increase their availability of health care services and reduce gender inequality. Two diffusion mechanisms are argued to be operating: the transfer of raw material goods and technology through the international capitalist exchange system and the transfer of modern values, ideas, practices, and knowledge through the mass media. The model was tested with data on four measures of mortality for a sample of 43 less developed countries circa 1993. Partial support is found for the model, and suggestions for future research are made.     

Disregulated Alcohol-Related Behavior Among College Drinkers: Associations With Protective Behaviors,Personality, and Drinking Motives

Abstract

Objective: This study investigated the psychometric properties of the Disregulated Alcohol-Related Behaviors Inventory (DARBI), a measure of harmful alcohol-related behavior, and the relationship between protective behavior use and scores on the DARBI and several other measures. Participants: Participants were 281 undergraduate volunteers (60% female) enrolled in introductory psychology sections in Summer and Fall 2007. Methods: Participants completed the DARBI along with paper-and-pencil self-report measures of broad personality domains, trait resilience, protective behavior use, and drinking motivations and consequences. Results: The DARBI's internal consistency was good (alpha = .85). DARBI scores correlated negatively with conscientiousness scores but positively with neuroticism, the Michigan Alcohol Screening Test (MAST), Rutgers Alcohol Problem Index (RAPI), and positive-reinforcement motives scores. The self-reported use of protective behaviors related negatively to DARBI, MAST, RAPI, and enhancement motives scores. Protective behavior use was unrelated to broad personality domains. Conclusions: The DARBI may prove a useful tool in campus interventions. Further research should determine the dispositional and situational determinants of protective behavior use.