The Relationship Between Depression and Other Psychosocial Problems in a Sample of Adolescent Pregnancy Termination Patients

At-risk adolescents experience troubling levels of depression but there is a dearth of research related to the levels of depression and associated psychosocial problems experienced by adolescent abortion patients. The relationship between depression and 16 other psychosocial life problems is examined in a sample of adolescent pregnancy termination patients. Using the Multidimensional Adolescent Assessment Scale (MAAS), depression and related psychosocial problems are assessed in a sample of 120 U.S. abortion patients ages 14–21. In general, patients scoring above the clinical cutscore for depression also reported higher levels of psychosocial problems in the other areas. Depression was significantly associated with problems with self-esteem, stress, guilt and confused thinking. Implications for practice and research are discussed.     

A Novel Approach to Chemical Mixture Risk Assessment—Linking Data from Population‐Based Epidemiology and Experimental Animal Tests

Humans are continuously exposed to chemicals with suspected or proven endocrine disrupting chemicals (EDCs). Risk management of EDCs presents a major unmet challenge because the available data for adverse health effects are generated by examining one compound at a time, whereas real‐life exposures are to mixtures of chemicals. In this work, we integrate epidemiological and experimental evidence toward a whole mixture strategy for risk assessment. To illustrate, we conduct the following four steps in a case study: (1) identification of single EDCs (“bad actors”)—measured in prenatal blood/urine in the SELMA study—that are associated with a shorter anogenital distance (AGD) in baby boys; (2) definition and construction of a “typical” mixture consisting of the “bad actors” identified in Step 1; (3) experimentally testing this mixture in an in vivo animal model to estimate a dose–response relationship and determine a point of departure (i.e., reference dose [RfD]) associated with an adverse health outcome; and (4) use a statistical measure of “sufficient similarity” to compare the experimental RfD (from Step 3) to the exposure measured in the human population and generate a “similar mixture risk indicator” (SMRI). The objective of this exercise is to generate a proof of concept for the systematic integration of epidemiological and experimental evidence with mixture risk assessment strategies. Using a whole mixture approach, we could find a higher rate of pregnant women under risk (13%) when comparing with the data from more traditional models of additivity (3%), or a compound‐by‐compound strategy (1.6%).     

Tests for noninferiority trials with binomial endpoints: A guide to modern and quasi‐exact methods for biomedical researchers

Applied statisticians and pharmaceutical researchers are frequently involved in the design and analysis of clinical trials where at least one of the outcomes is binary. Treatments are judged by the probability of a positive binary response. A typical example is the noninferiority trial, where it is tested whether a new experimental treatment is practically not inferior to an active comparator with a prespecified margin δ. Except for the special case of δ = 0, no exact conditional test is available although approximate conditional methods (also called second‐order methods) can be applied. However, in some situations, the approximation can be poor and the logical argument for approximate conditioning is not compelling. The alternative is to consider an unconditional approach. Standard methods like the pooled z‐test are already unconditional although approximate. In this article, we review and illustrate unconditional methods with a heavy emphasis on modern methods that can deliver exact, or near exact, results. For noninferiority trials based on either rate difference or rate ratio, our recommendation is to use the so‐called E‐procedure, based on either the score or likelihood ratio statistic. This test is effectively exact, computationally efficient, and respects monotonicity constraints in practice. We support our assertions with a numerical study, and we illustrate the concepts developed in theory with a clinical example in pulmonary oncology; R code to conduct all these analyses is available from the authors.     

Manufacturing American Identity Among Immigrant Workers: Colorado Fuel & Iron Company at the Turn of the 20th Century

Extant research indicates that white racial framing is utilized to rationalize discrimination, but less work has examined how the white racial frame becomes filtered into institutional settings such as corporations and instilled within its programs and practices. This paper analyzes white racial framing in the Colorado Fuel & Iron Company during the early twentieth century as part of its effort to Americanize and control its racially diverse workforce. The company developed a special unit headed by a physician and proponent of eugenics to promote “social betterment.” Our findings show how dominant racial ideologies were embedded within the company's conceptualization of social betterment and how these ideas influenced corporate programs aimed at mollifying the workforce and increasing productivity. We discuss the implications of our research for future analyses of historically embedded racial framing.     

Are Conventional Farmers Conventional? Analysis of the Environmental Orientations of Conventional New Zealand Farmers*

Abstract Within the political economy of agriculture and agrofood literatures there are examples of approaches that reject simple dichotomies between alternatives and the mainstream. In line with such approaches, we challenge the assumption that alternative agriculture, and its attendant improved environmental practices, alternative management styles, less intensive approaches, and better approaches to animal and ecosystem welfare, is the only source of agricultural sustainability. This article uses national farm‐survey results for New Zealand's sheep and beef, dairy, and horticulture sectors to examine conventional farmers, measure their assessments of farming practices, and assess their environmental orientation. Analysis identifies a proenvironmental cluster of farmers in each sector characterized by a higher environmental‐orientation score and distinct ratings of other farm practices queried in the survey. We interpret the results in terms of the exposure of different agricultural sectors to the effects of market‐based, audited, best‐practice schemes. The presence of shades of “greenness” among conventional farmers has important implications for environmental management and for our understanding of the various and complex pathways toward the greening of agrofood systems.     

The Impact of Local Labor Market Conditions on Work and Welfare Decisions: Revisiting an Old Question Using New Data

Using Maryland administrative data between 1996 and 2005, this paper examines the impact of local labor market conditions on work and welfare use among single mothers. Our estimates rely on the new Census Bureau Quarterly Workforce Indicators database, which provides county-level economic indicators filtered by industry, gender, and age-group. We specify a multinomial choice model to estimate the effects of these local labor market variables on the full set of work–welfare combinations. The results indicate that lower unemployment rates and increased new hires and new hires’ earnings in key industries increase the likelihood that women choose alternatives that include work. African American women and those with fewer years of education respond differently to changing economic conditions. Our results are robust to controls for fixed effects, county-specific time trends, and endogenous migration.     

Asymptotic behavior of the grenander estimator at density flat regions

Over forty years ago, Grenander derived the MLE of a monotone decreasing density f with known mode. Prakasa Rao obtained the asymptotic distribution of this estimator at a fixed point x where f' (x) < 0. Here, we obtain the asymptotic distribution of this estimator at a fixed point x when f is constant and nonzero in some open neighborhood of x. This limiting distribution is expressible as the convolution of a closed-form density and a rescaled standard normal density. Groeneboom (1983) derived the aforementioned closed-form density and we provide an alternative, more direct derivation.