Validation of Multimedia Models Assessing Exposure to PAHs—The SOLEX Study

Polluted soils have become a public health problem. While population exposure to soil pollutants is generally quantified using multimedia models, their estimations have not been validated, and studies that attempted to do so are scarce. The objective of the SOLEX study was to compare the predictions of pyrene exposure levels (converted into 1 hydroxypyrene) computed by several models with the results of urinary 1-hydropyrene (1-HOP) assays among 110 employees working at three sites polluted during their past use as manufactured gas plants. Four models were used: AERIS (Canada), CalTOX (California, USA), CLEA (UK), and HESP (The Netherlands). Three occupational exposure scenarios--with office, mixed, and outdoor workers--were constructed, based upon job activities during two measurement campaigns, one in winter and one in summer. The exposure levels estimated by the four models could differ markedly (from 7 up to 80 times) according to the exposure scenario. Also, the predominant exposure routes differed according to the model (direct soil ingestion for HESP and CalTOX, inhalation for AERIS, and dermal absorption for CLEA). The predictions of CalTOX are consistent with the 1-HOP measurements for all the scenarios. For HESP, the consistency is observed for the scenarios, office and mixed, for which the pyrene level in the soil is low. AERIS and CLEA yield results that are systematically above the 1-HOP measurements. This study confirms that validation of the models is crucial and points out to the need to proceed to assess components of the models that are the most influential using appropriate statistical analysis in combination with true field data.     

An Integral Approach to Mental Health Recovery: Implications for Social Work

The term recovery has become increasingly popular in the area of mental health care. Recently, it has been described by policy makers as the guiding vision for transforming the mental health system. Problematic, however, is that a lack of clarity continues to exist regarding how recovery is to be defined. Definitional attempts often appear to have competing opinions about what the concept exactly stands for. This causes confusion for both professionals and consumers desiring to adopt a recovery approach. Ken Wilber's integral theory is presented as a framework for organizing and connecting various viewpoints related to the “recovery” concept. Implications for social work are discussed.     

Racial inequality and social control: Historical and contemporary patterns in the U.S. South

Research dealing with disproportionate criminality, arrest, and incarceration among African Americans has tended to emphasize cultural, familial, and structural differences between racial groups while at the same time neglecting patterns and processes of race‐ and class‐based antagonism and subordination that are central, especially in the case of the U.S. South historically. We attempt to address this limitation by posing a model of the contemporary black‐white arrest differential across counties of one southern state. The model itself takes into consideration class‐ and race‐based subordination processes and their impact on local levels of stratification and arrest. Results suggest the continuing influence of racial competition and class dynamics. Racial competition enhances the arrest gap by disproportionately increasing unemployment and family dissolution among African Americans. The existence of a strong and concentrated traditional elite is shown to depress the racial gap, presumably by increasing poverty, unemployment, and family dissolution for both groups or by shaping what it means to go to jail, especially for blacks. In general, the arguments and findings presented suggest that criminological literature and theorizing should take note of local racial and political‐economic processes that, through the perpetuation of race and class inequality, reproduce disparate patterns of criminality, arrest, and incarceration.     

The National Social Distance Study: Ten Years Later

The Bogardus social distance scale, which measures the level of acceptance that Americans feel toward members of the most common ethnic and racial groups in the United States, was administered six times nationally between 1920 and 2001. Replicating the most recent study with its revised list of ethnic and racial groups, the authors of this study analyzed a stratified random sample of 3,166 college students, making it the largest national social distance study ever conducted. The findings indicate an increase since 2001 in the mean level of social distance toward all ethnic groups, as well as in the spread between the groups with the highest and lowest levels of social distance. Further, a consistency between studies in group preferences reaffirms the relevance of the similarity‐attraction bond in accepting those who are racially and culturally different. Mean comparisons and analysis of variance tests also showed that gender, birthplace of respondents and/or their parents, race, and year in college are all significant indicators of the level of social distance toward groups.     

Effects of Video-Guided Group vs. Solitary Meditation on Mindfulness and Social Connectivity: A Pilot Study

Clinical Social Work Journal - Interest in mindfulness meditation continues to grow as accumulating evidence suggests mindfulness training encourages more positive functioning. However, basic...     

Biases in Ethical Decision Making among University Faculty

Over the years, cognitive biases have been examined throughout the decision-making literature, but little work has investigated the cognitive biases operating in ethical decision making. The present effort explores a taxonomy of biases through interviews with university faculty members. Additionally, this study identifies the psychological processes giving rise to these biases in ethical decision making. Results suggest that the biases listed in the taxonomy are indeed operating in the ethical decision making of university faculty. Implications of these results are discussed.     

A network ridesharing experiment with sequential choice of transportation mode

Within the last decade, there has been a dramatic bloom in ridesharing businesses along with the emergence of new enabling technologies. A central issue in ridesharing, which is also important in the general domain of cost-sharing in economics and computer science, is that the sharing of cost implies positive externalities and hence coordination problems for the network users. We investigate these problems experimentally in the present study. In particular, we focus on how sequential observability of transportation mode choices can be a powerful facilitator of coordination in ridesharing. Our study abstracts the essential issues of coordination in ridesharing into a directed network game with experimentally testable predictions. In line with the theoretical analysis, our experimental evidence shows that even a limited extent of sequential choice observability might lead to efficient coordination. However, convergence to efficiency is slower with more limited observability, resulting in a significant increase in travel cost.     

A Bayesian Network Estimation of the Service‐Profit Chain for Transport Service Satisfaction

Bayesian network methodology is used to model key linkages of the service‐profit chain within the context of transportation service satisfaction. Bayesian networks offer some advantages for implementing managerially focused models over other statistical techniques designed primarily for evaluating theoretical models. These advantages are (1) providing a causal explanation using observable variables within a single multivariate model, (2) analysis of nonlinear relationships contained in ordinal measurements, (3) accommodation of branching patterns that occur in data collection, and (4) the ability to conduct probabilistic inference for prediction and diagnostics with an output metric that can be understood by managers and academics. Sample data from 1,101 recent transport service customers are utilized to select and validate a Bayesian network and conduct probabilistic inference.