Depressive symptoms as a predictor of alcohol relapse after residential treatment programs for alcohol use disorder

Alcohol use disorder (AUD) and depressive disorders often co-occur. Findings on the effects of major depressive disorder (MDD) or depressive symptoms on posttreatment alcohol relapse are controversial. The study's aim is to examine the association of MDD and depressive symptoms with treatment outcomes after residential AUD programs. In a naturalistic-prospective, multisite study with 12 residential AUD treatment programs in the German-speaking part of Switzerland, 64 patients with AUD with MDD, 283 patients with AUD with clinically significant depressive symptoms at admission, and 81 patients with AUD with such problems at discharge were compared with patients with AUD only on alcohol use, depressive symptoms, and treatment service utilization. MDD was provisionally identified at admission and definitively defined at discharge. Whereas patients with MDD did not differ from patients with AUD only at 1-year follow-up, patients with AUD with clinically significant depressive symptoms had significantly shorter time-to-first-drink and a lower abstinence rate. These patients also had elevated AUD indices and treatment service utilization for psychiatric disorders. Our results suggest that clinically significant depressive symptoms are a substantial risk factor for relapse so that it may be important to treat them during and after residential AUD treatment programs.

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.

Arsenic volatilization in model anaerobic biogas digesters

Arsenic is a class 1 non-threshold carcinogen which is highly ubiquitous. Arsenic undergoes many different transformations (biotic or abiotic) between and within environmental compartments, leading to a number of different chemical species possessing different properties and toxicities. One specific transformation is As biotic volatilization which is coupled with As biomethylation and has been scarcely studied due to inherent sampling issues. Arsenic methylation/volatilization is also linked with methanogenesis and occurs in anaerobic environments. In China, rice straw and animal manure are very often used to produce biogas and both can contain high amounts of As, especially if the rice is grown in areas with heavy mining or smelting industries and if Roxarsone is fed to the animals. Roxarsone is an As-containing drug which is widely used in China to control coccidian intestinal parasites, to improve feed efficiency and to promote rapid growth. Previous work has shown that this compound degrades to inorganic As under anaerobic conditions. In this study the focus is on biotic transformations of As in small microcosms designed as biogas digester models (BDMs) using recently validated As traps, thus, enabling direct quantification and identification of volatile As species. It is shown that although there was a loss of soluble As in the BDMs, their conditions favored biomethylation. All reactors produced volatile As, especially the monomethylarsonic acid spiked ones with 413 ± 148 ng As (mean ± SD, n = 3) which suggest that the first methylation step, from inorganic As, is a limiting factor. The most abundant species was trimethylarsine, but the toxic arsine was present in the headspace of most of the BDMs. The results suggest that volatile As species should be monitored in biogas digesters in order to assess risks to humans working in biogas plants and those utilizing the biogas.

Prediction of residential radon exposure of the whole Swiss population: comparison of model-based predictions with measurement-based predictions

Radon plays an important role for human exposure to natural sources of ionizing radiation. The aim of this article is to compare two approaches to estimate mean radon exposure in the Swiss population: model-based predictions at individual level and measurement-based predictions based on measurements aggregated at municipality level. A nationwide model was used to predict radon levels in each household and for each individual based on the corresponding tectonic unit, building age, building type, soil texture, degree of urbanization, and floor. Measurement-based predictions were carried out within a health impact assessment on residential radon and lung cancer. Mean measured radon levels were corrected for the average floor distribution and weighted with population size of each municipality. Model-based predictions yielded a mean radon exposure of the Swiss population of 84.1 Bq/m(3) . Measurement-based predictions yielded an average exposure of 78 Bq/m(3) . This study demonstrates that the model- and the measurement-based predictions provided similar results. The advantage of the measurement-based approach is its simplicity, which is sufficient for assessing exposure distribution in a population. The model-based approach allows predicting radon levels at specific sites, which is needed in an epidemiological study, and the results do not depend on how the measurement sites have been selected.

Association of alcohol craving and proximal outcomes of a residential treatment program for patients with alcohol use disorders

Background: Alcohol craving is an essential construct in research and treatment of alcohol use disorders (AUD). Craving is mostly investigated in association with concurrent variables or distal treatment outcomes at follow-up. Objectives: The aim of this study is to examine craving at admission and its relevance for essential proximal outcomes at discharge from AUD treatment such as positive alcohol expectancy, abstinent-related self-efficacy, and substance-related coping, as well as patients’ demographic and AUD characteristics. Methods: In total, 36 patients were recruited within an inpatient treatment AUD program. Results: An association between craving and positive alcohol expectancies at discharge was found in the regression model even when the respective expectancies, age, gender, and severity of alcohol dependence at admission were controlled for (F(2,29)1⁄432.71, p50.001). Craving explained 2.3% of the variance of change in positive alcohol expectancy. Conclusion: The results suggest a low predictive value of craving for positive alcohol expectancy. In addition, we found significant associations between the craving and the severity of AUD and alcohol consumption before admission. Future studies should include proximal outcomes related to treatment efficacy as well as distal outcomes.

Motivation as a predictor of drinking outcomes after residential treatment programs for alcohol dependence

OBJECTIVES: Patients' motivation to change their substance use is usually viewed as a crucial component of successful treatment. The objective of this study was to examine whether motivation contributes to drinking outcomes after residential treatment for alcohol dependence. METHODS: Our sample included 415 Swiss patients from 12 residential alcohol treatment programs. We statistically controlled for important predictors, such as sex, employment, alcohol consumption before admission, severity of alcohol dependence, severity of psychiatric symptoms at admission, and alcohol-related self-efficacy at discharge. Abstinence, alcohol consumption, and time to first drink were used as primary outcome measures and were assessed 1 year after discharge from treatment. RESULTS: Action-oriented motivation to change substance use had a modest impact on drinking outcomes. At the 1-year follow-up, only the Taking Steps subscale of the Stages of Change Readiness and Treatment Eagerness Scale and alcohol-related self-efficacy were found to be significant predictors of abstinence and the number of standard drinks. CONCLUSIONS: The impact of action-oriented motivation at admission to residential treatment is modest but still relevant, compared with other outcome predictors. It may be useful to focus treatment on improving action-oriented motivation to reduce substance use