Treatment outcomes of an integrated residential programme for patients with schizophrenia and substance use disorder

About half of all schizophrenic patients have a co-occurring substance use disorder, leading to poorer social and functional outcomes than obtained in non-abusing patients. To improve outcomes, integrated treatments have been designed that address the two conditions simultaneously. Results are, however, conflicting because the available effect studies are hampered by various methodological issues, among which are heterogeneous patient samples.

A prediction model for assessing residential radon concentration in Switzerland

Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the nationwide Swiss radon database collected between 1994 and 2004. Of these, 80% randomly selected measurements were used for model development and the remaining 20% for an independent model validation. A multivariable log-linear regression model was fitted and relevant predictors selected according to evidence from the literature, the adjusted R², the Akaike's information criterion (AIC), and the Bayesian information criterion (BIC). The prediction model was evaluated by calculating Spearman rank correlation between measured and predicted values. Additionally, the predicted values were categorised into three categories (50th, 50th-90th and 90th percentile) and compared with measured categories using a weighted Kappa statistic. The most relevant predictors for indoor radon levels were tectonic units and year of construction of the building, followed by soil texture, degree of urbanisation, floor of the building where the measurement was taken and housing type (P-values <0.001 for all). Mean predicted radon values (geometric mean) were 66 Bq/m³ (interquartile range 40-111 Bq/m³) in the lowest exposure category, 126 Bq/m³ (69-215 Bq/m³) in the medium category, and 219 Bq/m³ (108-427 Bq/m³) in the highest category. Spearman correlation between predictions and measurements was 0.45 (95%-CI: 0.44; 0.46) for the development dataset and 0.44 (95%-CI: 0.42; 0.46) for the validation dataset. Kappa coefficients were 0.31 for the development and 0.30 for the validation dataset, respectively. The model explained 20% overall variability (adjusted R²). In conclusion, this residential radon prediction model, based on a large number of measurements, was demonstrated to be robust through validation with an independent dataset. The model is appropriate for predicting radon level exposure of the Swiss population in epidemiological research. Nevertheless, some exposure misclassification and regression to the mean is unavoidable and should be taken into account in future applications of the model.

Self-efficacy as a predictor of outcome after residential treatment programs for alcohol dependence: simply ask the patient one question!

Self-efficacy has been identified as one of the most consistent variables that predict the outcome of alcohol treatment. However, many previous studies in this field failed to control for other important predictors (e.g., dependences severity, psychiatric symptoms, and treatment goal). Our study's first goal was to evaluate the predictive value of self-efficacy when most other relevant variables were statistically controlled. The second goal was to compare the predictive values of self-efficacy assessed with the Situational Confidence Questionnaire (SCQ), and general self-efficacy assessed with a single question.

Invitational rhetoric : alternative rhetorical strategy for transformation of perception and use of energy in the residential built environment from the Keweenaw to Kerala

This dissertation explores the viability of invitational rhetoric as a mode of advocacy for sustainable energy use in the residential built environment. The theoretical foundations for this study join ecofeminist concepts and commitments with the conditions and resources of invitational rhetoric, developing in particular the rhetorical potency of the concepts of re-sourcement and enfoldment. The methodological approach is autoethnography using narrative reflection and journaling, both adapted to and developed within the autoethnographic project. Through narrative reflection, the author explores her lived experiences in advocating for energy-responsible residential construction in the Keweenaw Peninsula of Michigan. The analysis reveals the opportunities for cooperative, collaborative advocacy and the struggle against traditional conventions of persuasive advocacy, particularly the centrality of the rhetor. The author also conducted two field trips to India, primarily the state of Kerala. Drawing on autoethnographic journaling, the analysis highlights the importance of sensory relations in lived advocacy and the resonance of everyday Indian culture to invitational principles. Based on field research, the dissertation proposes autoethnography as a critical development in encouraging invitational rhetoric as an alternative mode of effecting change. The invitational force of autoethnography is evidenced in portraying the material advocacy of the built environment itself, specifically the sensual experience of material arrangements and ambience, as well as revealing the corporeality of advocacy, that is, the body as the site of invitational engagement, emotional encounter, and sensory experience. This study concludes that vulnerability of self in autoethnographic work and the vulnerability of rhetoric as invitational constitute the basis for transformation. The dissertation confirms the potential of an ecofeminist invitational advocacy conveyed autoethnographically for transforming perceptions and use of energy in a smaller-scale residential environment appropriate for culture, climate, and ultimately part of the challenge of sustaining life on this planet.

Hating the neighbors: The role of hate crime in the perpetuation of black residential segregation

Grounded in group conflict theory and the defended neighborhoods thesis, this nationwide empirical study of cities and their residential segregation levels, examines the occurrence of hate crime using data on for all U.S. cities with populations over 95,000, and data compiled from the Uniform Crime Report for hate crime, in conjunction with 2000 census data. Hate crime is any illegal act motivated by pre-formed bias against, in this case, a person’s real or perceived race. This research asks: Do hate crime levels predict white/black segregation levels? How does hate crime predict different measures of white/black segregation? I use the dissimilarity index measure of segregation operationalized as a continuous, binary and ordinal variable, to explore whether hate crime predicts segregation of blacks from whites. In cities with higher rates of hate crime there was higher dissimilarity between whites and blacks, controlling for other factors. The segregation level was more likely to be “high” in a city where hate crime occurred. Blacks are continually multiply disadvantaged and distinctly affected by hate crime and residential segregation. Prior studies of residential segregation have focused almost exclusively on individual choice, residents’ lack of finances, or discriminatory actions that prevent racial minorities from moving, to explore the correlates of segregation. Notably absent from these studies are measures reflecting the level of hate crime occurring in cities. This study demonstrates the importance of considering hate crime and neighborhood conflict when contemplating the causes of residential segregation.