Social phobia in obsessive-compulsive disorder: Prevalence and correlates

Background: Social Phobia (SP) is an anxiety disorder that frequently co-occurs with obsessive-compulsive disorder (OCD); however, studies that evaluate clinical factors associated with this specific comorbidity are rare. The aim was to estimate the prevalence of SP in a large multicenter sample of OCD patients and compare the characteristics of individuals with and without SP. Method: A cross-sectional study with 1001 patients of the Brazilian Research Consortium on Obsessive-Compulsive Spectrum Disorders using several assessment instruments, including the Dimensional Yale-Brown Obsessive-Compulsive Scale and the Structured Clinical Interview for DSM-IV Axis I Disorders. Univariate analyses were followed by logistic regression. Results: Lifetime prevalence of SP was 34.6% (N=346). The following variables remained associated with SP comorbidity after logistic regression: male sex, lower socioeconomic status, body dysmorphic disorder, specific phobia, dysthymia, generalized anxiety disorder, agoraphobia, Tourette syndrome and binge eating disorder. Limitations: The cross-sectional design does not permit the inference of causal relationships; some retrospective information may have been subject to recall bias; all patients were being treated in tertiary services, therefore generalization of the results to other samples of OCD sufferers should be cautious. Despite the large sample size, some hypotheses may not have been confirmed due to the small number of cases with these characteristics (type 2 error). Conclusion: SP is frequent among OCD patients and co-occurs with other disorders that have common phenomenological features. These findings have important implications for clinical practice, indicating the need for broader treatment approaches for individuals with this profile. (C) 2012 Elsevier B.V. All rights reserved.

Cointegration: Bayesian Significance Test

To estimate causal relationships, time series econometricians must be aware of spurious correlation, a problem first mentioned by Yule (1926). To deal with this problem, one can work either with differenced series or multivariate models: VAR (VEC or VECM) models. These models usually include at least one cointegration relation. Although the Bayesian literature on VAR/VEC is quite advanced, Bauwens et al. (1999) highlighted that "the topic of selecting the cointegrating rank has not yet given very useful and convincing results". The present article applies the Full Bayesian Significance Test (FBST), especially designed to deal with sharp hypotheses, to cointegration rank selection tests in VECM time series models. It shows the FBST implementation using both simulated and available (in the literature) data sets. As illustration, standard non informative priors are used.