Brief report: the relationship between multiple forms of oppression and subjective health among Black lesbian and bisexual women

This study was designed to explore the relationships between multiple forms of oppression and subjective physical health among a community sample of 85 Black lesbian and bisexual women. Self-report surveys assessing health behaviors, physical and mental health status, and experiences with discrimination were administered during a weekend retreat of a community-based organization serving this population. Structural equation modeling showed there were significant, but different, relationships between subjective health and two types of oppression, heterosexism and weight-based discrimination. Further research on the independent and intersectional effects of multiple forms of oppression on health is needed.     

Leading Practice Improvement in Front Line Child Protection

Front line child protection managers are a vital conduit foreffective outcomes for children, young people and their families.However, little is known about the change processes that theyneed to implement to effectively intervene in such a complexcontext to support improved practice. This article describeshow organizational action research and Organizational LinkageTheory were used to establish an in-depth understanding of theinhibitors and facilitators of the implementation of an outcome-focusedmanagement model in three child protection offices. This analysisidentified that five interrelated compensatory processes actedto offset the impact of the implementation inhibitors. This,in turn, enabled direct service staff to experience an increasedcapacity to undertake effective service activities. This articleexplores each of these compensatory processes and makes a numberof suggestions for how child protection managers and their organizationsmight seek to embed them.     

BAYESIAN MODEL SEARCH AND MULTILEVEL INFERENCE FOR SNP ASSOCIATION STUDIES

Technological advances in genotyping have given rise to hypothesis-based association studies of increasing scope. As a result, the scientific hypotheses addressed by these studies have become more complex and more difficult to address using existing analytic methodologies. Obstacles to analysis include inference in the face of multiple comparisons, complications arising from correlations among the SNPs (single nucleotide polymorphisms), choice of their genetic parametrization and missing data. In this paper we present an efficient Bayesian model search strategy that searches over the space of genetic markers and their genetic parametrization. The resulting method for Multilevel Inference of SNP Associations, MISA, allows computation of multilevel posterior probabilities and Bayes factors at the global, gene and SNP level, with the prior distribution on SNP inclusion in the model providing an intrinsic multiplicity correction. We use simulated data sets to characterize MISA's statistical power, and show that MISA has higher power to detect association than standard procedures. Using data from the North Carolina Ovarian Cancer Study (NCOCS), MISA identifies variants that were not identified by standard methods and have been externally "validated" in independent studies. We examine sensitivity of the NCOCS results to prior choice and method for imputing missing data. MISA is available in an R package on CRAN.     

Building a statistical model to predict reactor temperatures

This paper describes the various stages in building a statistical model to predict temperatures in the core of a reactor, and compares the benefits of this model with those of a physical model. We give a brief background to this study and the applications of the model to rapid online monitoring and safe operation of the reactor. We describe the methods, of correlation and two dimensional spectral analysis, which we use to identify the effects that are incorporated in a spatial regression model for the measured temperatures. These effects are related to the age of the reactor fuel and the spatial geometry of the reactor. A remaining component of the temperature variation is a slowly varying temperature surface modelled by smooth functions with constrained coefficients. We assess the accuracy of the model for interpolating temperatures throughout the reactor, when measurements are available only at a reduced set of spatial locations, as is the case in most reactors. Further possible improvements to the model are discussed.     

Information theory and risk in capital markets

The present empirical study applies the methodology of information theory to the problem of assessing and separating capital market risk, which is separated into its systematic and unsystematic components. Monthly return relatives for all securities traded on the New York Stock Exchange are examined for the period 1926 to 1971, which is segmented into six 7-year subperiods. The securities are combined into portfolios of various sizes and ranked. It is concluded that although both systematic and unsystematic risks have increased over the 45-year interval—particularly between the pre-1940 and post-1940 periods—they have maintained their relative share of the total risk over the same period.     

Assessment of an e-training tool for college students to improve accuracy and reduce effort associated with reading nutrition labels

Objective: Nutrition labels are often underutilized due to the time and effort required to read them. We investigated the impact of label-reading training on effort, as well as accuracy and motivation. Participants: Eighty college students (21 men and 59 women). Methods: The training consisted of a background tutorial on nutrition followed by three blocks of practice reading labels to decide which of two foods was the relatively better choice. Label-reading effort was assessed using an eye tracker and motivation was assessed using a 6-item scale of healthy food-choice empowerment. Results: Students showed increases in label-reading accuracy, decreases in label-reading effort, and increases in empowerment. Conclusions: The nutrition label e-training tool presented here, whether used alone or as part of other wellness and health programs, may be an effective way to boost students’ label-reading skills and healthy food choices, before they settle into grocery shopping habits.     

The Prioritization of Island Nations as Refuges from Extreme Pandemics

In this conceptual article with illustrative data, we suggest that it is useful to rank island nations as potential refuges for ensuring long-term human survival in the face of catastrophic pandemics (or other relevant existential threats). Prioritization could identify the several island nations that are most suitable for targeting social and political preparations and further investment in resiliency. We outline a prioritization methodology and as an initial demonstration, we then provide example rankings by considering 20 sovereign island states (all with populations greater than 250,000 and no land borders). Results describe each nation in nine resilience-relevant domains covering location, population, resources, and society according to published data. The results indicate that the most suitable island nations for refuge status are Australia, followed closely by New Zealand, and then Iceland, with other nations all well behind (including the relatively high-income ones of Malta and Japan). Nevertheless, some key contextual factors remain relatively unexplored. These include the capacity of the jurisdiction to rapidly close its borders when the emerging threat was first detected elsewhere, and whether or not large subnational islands should be the preferred focus for refuge design (e.g., the Australian state of Tasmania, the island of Hokkaido in Japan, or the South Island of New Zealand). Overall, this work provides conceptual thinking with some initial example analysis. Further research could refine the selection of metrics, how best to weight the relevant domains, and how the populations of prioritized island nations view their nation's selection as a potential refuge for human survival.