The Role of Society in Engineering Risk Analysis: A Capabilities-Based Approach

This article proposes a new conceptual framework in engineering risk analysis to account for the net impact of hazards on individuals in a society. It analyzes four limitations of prevailing approaches to risk analysis and suggests a way to overcome them. These limitations are a result of how societal impacts are characteristically accounted for and valued. Prevailing approaches typically focus too narrowly on the consequences of natural or man-made hazards, not accounting for the broader societal impacts of such hazards. Such approaches lack a uniform and consistent metric for accounting for the impact of the nonquantifiable consequences (like psychological trauma or societal impacts) and rely upon implicit and potentially inaccurate value judgments when evaluating risks. To overcome these limitations, we propose an alternative, Capabilities-Based Approach to the treatment of society in risk analysis. A similar approach is currently used by the United Nations to quantitatively measure the degree of development in countries around the world. In a Capabilities-Based Approach, the potential benefits and losses due to a hazard are measured and compared in a uniform way by using individual capabilities (functionings individuals are able, still able, or unable to achieve) as a metric. This Capabilities-Based Approach provides a foundation for identifying and quantifying the broader, complex societal consequences of hazards and is based on explicit, value judgments. The Capabilities-Based Approach can accommodate different methods or techniques for risk determination and for risk evaluation and can be used in assessing risk in diverse types of hazards (natural or man-made) and different magnitudes that range from minor to catastrophic. In addition, implementing a Capabilities-Based Approach contributes to the development of a single standard for public policy decision making, since a Capabilities-Based Approach is already in use in development economics and policy.     

Optimal dynamic treatment regimes

Summary. A dynamic treatment regime is a list of decision rules, one per time interval, for how the level of treatment will be tailored through time to an individual's changing status. The goal of this paper is to use experimental or observational data to estimate decision regimes that result in a maximal mean response. To explicate our objective and to state the assumptions, we use the potential outcomes model. The method proposed makes smooth parametric assumptions only on quantities that are directly relevant to the goal of estimating the optimal rules. We illustrate the methodology proposed via a small simulation.     

Adjusting for Time‐Varying Confounding in Survival Analysis

In this paper we illustrate how directly including endogenous time‐varying confounders in the model of the effect of an exposure on a response can lead to bias in discrete time survival analysis. An alternative to this method is Hernán, Brumback, and Robins'(1999) use of sample weights to adjust for endogenous time‐varying confounding. We discuss when this method can be used to provide unbiased estimators, and we illustrate the method by addressing a substantive research question using existing survey data. We also critically examine the robustness of the weighting method to violations of the underlying assumptions via a simulation analysis.     

Concurrent and Across Time Prediction of Young Adolescents' Social Functioning: The Role of Emotionality and Regulation

The social functioning of 64 young adolescents (10‐ to 12‐year olds) was examined in relation to negative emotionality and regulation during early adolescence, as well as two, four, and six years earlier. Young adolescents who were viewed as relatively high in social functioning (i.e., high teacher‐rated school social competence; low mother‐ or father‐rated problem behavior) were generally viewed as relatively low on negative emotionality and high on regulatory abilities during early adolescence as well as two, four, and six years earlier. Furthermore, negative emotionality and regulation during early adolescence, and in some cases at previous time periods, contributed unique variance to the prediction of social functioning during early adolescence. Young adolescents who were consistently low in social functioning across time were higher on negative emotionality and lower on regulation than were young adolescents who were consistently high on social functioning over time.     

AIDS and kitchen gardens: insights from a village in Western Kenya

In rural Africa, indigenous farming and natural resource management systems exemplified by kitchen gardens are being reshaped by the HIV/AIDS epidemic and its negative impacts (illness, stigma and mortality, and economic costs) and positive opportunities (organizational responses to the epidemic). Subtle changes in crops and farm techniques can be traced to these diverse influences of HIV+ infection, illness, mortality, widowhood, foster child care, and AIDS support groups, as well as the organizations, ideas, and flow of funding from outside. These findings draw on original field data: a village census, in-depth interviews with gardeners, and group discussions in a village in Bungoma District (in 2005 and 2007). This part of western Kenya is a typical small-farm zone that has faced a moderate HIV/AIDS epidemic since the 1990s, following decades of demographic, environmental, technological, and institutional changes. Implications of this case study for further research on HIV/AIDS and on micro-level population–environment change suggest that households are useful but imperfect analytical units and are best seen as part of complex social networks, shaping connections to markets. These important “mediating institutions” link AIDS as a demographic and economic force with environmental outcomes in cultivated landscapes.     

Strategy Alternatives for Homeland Air and Cruise Missile Defense

Air and cruise missile defense of the U.S. homeland is characterized by a requirement to protect a large number of critical assets nonuniformly dispersed over a vast area with relatively few defensive systems. In this article, we explore strategy alternatives to make the best use of existing defense resources and suggest this approach as a means of reducing risk while mitigating the cost of developing and acquiring new systems. We frame the issue as an attacker‐defender problem with simultaneous moves. First, we outline and examine the relatively simple problem of defending comparatively few locations with two surveillance systems. Second, we present our analysis and findings for a more realistic scenario that includes a representative list of U.S. critical assets. Third, we investigate sensitivity to defensive strategic choices in the more realistic scenario. As part of this investigation, we describe two complementary computational methods that, under certain circumstances, allow one to reduce large computational problems to a more manageable size. Finally, we demonstrate that strategic choices can be an important supplement to material solutions and can, in some cases, be a more cost‐effective alternative.     

A mixture of experts latent position cluster model for social network data

Social network data represent the interactions between a group of social actors. Interactions between colleagues and friendship networks are typical examples of such data.The latent space model for social network data locates each actor in a network in a latent (social) space and models the probability of an interaction between two actors as a function of their locations. The latent position cluster model extends the latent space model to deal with network data in which clusters of actors exist — actor locations are drawn from a finite mixture model, each component of which represents a cluster of actors.A mixture of experts model builds on the structure of a mixture model by taking account of both observations and associated covariates when modeling a heterogeneous population. Herein, a mixture of experts extension of the latent position cluster model is developed. The mixture of experts framework allows covariates to enter the latent position cluster model in a number of ways, yielding different model interpretations.Estimates of the model parameters are derived in a Bayesian framework using a Markov Chain Monte Carlo algorithm. The algorithm is generally computationally expensive — surrogate proposal distributions which shadow the target distributions are derived, reducing the computational burden.The methodology is demonstrated through an illustrative example detailing relationships between a group of lawyers in the USA.     

The Benefits of Dispositional Mindfulness in Physical Health: A Longitudinal Study of Female College Students

Abstract

Objective: This article examines the relationship between dispositional mindfulness, health behaviors (eg, sleep, eating, and exercise), and physical health. Participants: Participants included 441 college women. Methods: Women completed self-report surveys at the beginning and end of a 10-week academic quarter. The study was conducted over 5 academic quarters from fall 2008 to fall 2010. Results: Findings indicated that higher levels of dispositional mindfulness were related to healthier eating practices, better quality of sleep, and better physical health. Dispositional mindfulness contributed to better physical health even after controlling for traditional health habits. Finally, bidirectional mediational relationships were found between healthy eating and dispositional mindfulness as well as between sleep quality and dispositional mindfulness when physical health was the outcome variable. Conclusions: Findings suggest that incorporating mindfulness training into programming on college campuses may be beneficial, as results indicate that dispositional mindfulness is related to positive physical health among college students.