Clinical correlates of social adjustment in patients with obsessive-compulsive disorder

Background: Patients with obsessive-compulsive disorder (OCD) frequently show poor social adjustment, which has been associated with OCD severity. Little is known about the effects that age at symptom onset, specific OCD symptoms, and psychiatric comorbidities have on social adjustment. The objective of this study was to investigate the clinical correlates of social functioning in OCD patients. Methods: Cross-sectional study involving 815 adults with a primary DSM-IV diagnosis of OCD participating in the Brazilian Research Consortium on Obsessive-Compulsive Spectrum Disorders. Patients were assessed with the Social Adjustment Scale, the Medical Outcomes Study 36-item Short-Form Health Survey, the Yale-Brown Obsessive-Compulsive Scale, the Dimensional Yale-Brown Obsessive-Compulsive Scale, and the Structured Clinical Interview for DSM-IV Axis I Disorders. Clinical correlates of social adjustment were assessed with generalized linear models with gamma distribution. Results: Poor overall social functioning was associated with greater OCD severity (p = 0.02); hoarding symptoms (p = 0.004); sexual/religious obsessions (p = 0.005); current major depressive disorder (p = 0.004); current post-traumatic stress disorder (p = 0.002); and current eating disorders (p = 0.02). Poor social adjustment was also associated with impaired quality of life. Conclusions: Patients with OCD have poor social functioning in domains related to personal relationships and professional performance. Hoarding symptoms and sexual/religious obsessions seem to have the strongest negative effects on social functioning. Early age at OCD symptom onset seems to be associated with professional and academic underachievement and impairment within the family unit, whereas current psychiatric comorbidity worsen overall social functioning. In comparison with quality of life, social adjustment measures seem to provide a more comprehensive overview of the OCD-related burden. (C) 2012 Elsevier Ltd. All rights reserved.

Influence diagnostics for elliptical semiparametric mixed models

In this paper we extend semiparametric mixed linear models with normal errors to elliptical errors in order to permit distributions with heavier and lighter tails than the normal ones. Penalized likelihood equations are applied to derive the maximum penalized likelihood estimates (MPLEs) which appear to be robust against outlying observations in the sense of the Mahalanobis distance. A reweighed iterative process based on the back-fitting method is proposed for the parameter estimation and the local influence curvatures are derived under some usual perturbation schemes to study the sensitivity of the MPLEs. Two motivating examples preliminarily analyzed under normal errors are reanalyzed considering some appropriate elliptical errors. The local influence approach is used to compare the sensitivity of the model estimates.

Stigma toward schizophrenia: do all psychiatrists behave the same? Latent profile analysis of a national sample of psychiatrists in Brazil

Background: An important issue concerning the worldwide fight against stigma is the evaluation of psychiatrists’ beliefs and attitudes toward schizophrenia and mental illness in general. However, there is as yet no consensus on this matter in the literature, and results vary according to the stigma dimension assessed and to the cultural background of the sample. The aim of this investigation was to search for profiles of stigmatizing beliefs related to schizophrenia in a national sample of psychiatrists in Brazil. Methods: A sample of 1414 psychiatrists were recruited from among those attending the 2009 Brazilian Congress of Psychiatry. A questionnaire was applied in face-to-face interviews. The questionnaire addressed four stigma dimensions, all in reference to individuals with schizophrenia: stereotypes, restrictions, perceived prejudice and social distance. Stigma item scores were included in latent profile analyses; the resulting profiles were entered into multinomial logistic regression models with sociodemographics, in order to identify significant correlates. Results: Three profiles were identified. The “no stigma” subjects (n = 337) characterized individuals with schizophrenia in a positive light, disagreed with restrictions, and displayed a low level of social distance. The “unobtrusive stigma” subjects (n = 471) were significantly younger and displayed the lowest level of social distance, although most of them agreed with involuntary admission and demonstrated a high level of perceived prejudice. The “great stigma” subjects (n = 606) negatively stereotyped individuals with schizophrenia, agreed with restrictions and scored the highest on the perceived prejudice and social distance dimensions. In comparison with the first two profiles, this last profile comprised a significantly larger number of individuals who were in frequent contact with a family member suffering from a psychiatric disorder, as well as comprising more individuals who had no such family member. Conclusions: Our study not only provides additional data related to an under-researched area but also reveals that psychiatrists are a heterogeneous group regarding stigma toward schizophrenia. The presence of different stigma profiles should be evaluated in further studies; this could enable anti-stigma initiatives to be specifically designed to effectively target the stigmatizing group.

Comparison between the complete Bayesian method and empirical Bayesian method for ARCH models using Brazilian financial time series

In this work we compared the estimates of the parameters of ARCH models using a complete Bayesian method and an empirical Bayesian method in which we adopted a non-informative prior distribution and informative prior distribution, respectively. We also considered a reparameterization of those models in order to map the space of the parameters into real space. This procedure permits choosing prior normal distributions for the transformed parameters. The posterior summaries were obtained using Monte Carlo Markov chain methods (MCMC). The methodology was evaluated by considering the Telebras series from the Brazilian financial market. The results show that the two methods are able to adjust ARCH models with different numbers of parameters. The empirical Bayesian method provided a more parsimonious model to the data and better adjustment than the complete Bayesian method.

Análise de concorrência no mercado mundial de café verde

A literatura argumenta que o Brasil, embora ainda seja o maior exportador mundial de café verde, tem perdido poder neste mercado, pois a concorrência (rivalidade e probabilidade de entrada) imposta por países como a Colômbia e o Vietnã é forte o suficiente para tornar este mercado bastante competitivo. Assim, este artigo avalia o padrão recente de concorrência do mercado mundial de café verde utilizando uma metodologia econométrica mais usualmente empregada em análise antitruste. Para avaliar o comportamento dos consumidores, foram estimadas as elasticidades-preço da demanda mundial de café verde, por tipo de café, usando o modelo de demanda Logit Multinomial Antitruste. Para avaliar o comportamento de equilíbrio de mercado foram realizados testes de instabilidade de share de quantidade por meio de análise de cointegração em painel. Os resultados apontam para aumento da concorrência à variedade de café brasileiro por parte da demanda e manutenção de sharede quantidades como configuração de equilíbrio de mercado.

The impact of asymptomatic vertebral fractures on quality of life in older community-dwelling women: the São Paulo Ageing & Health Study

OBJECTIVES: The aim of this study was to investigate the impact of asymptomatic vertebral fractures on the quality of life in older women as part of the Sao Paulo Ageing & Health Study. METHODS: This study was a cross-sectional study with a random sample of 180 women 65 years of age or older with or without vertebral fractures. The Quality of Life Questionnaire of the European Foundation for Osteoporosis was administered to all subjects. Anthropometric data were obtained by physical examination, and the body mass index was calculated. Lateral thoracic and lumbar spine X-ray scans were obtained to identify asymptomatic vertebral fractures using a semi-quantitative method. RESULTS: Women with asymptomatic vertebral fractures had lower total scores [61.4(15.3) vs. 67.1(14.2), p = 0.03] and worse physical function domain scores [69.5(20.1) vs. 77.3(17.1), p = 0.02] for the Quality of Life Questionnaire of the European Foundation for Osteoporosis compared with women without fractures. The total score of this questionnaire was also worse in women classified as obese than in women classified as overweight or normal. High physical activity was related to a better total score for this questionnaire (p = 0.01). Likewise, lower physical function scores were observed in women with higher body mass index values (p<0.05) and lower physical activity levels (p,0.05). Generalized linear models with gamma distributions and logarithmic link functions, adjusted for age, showed that lower total scores and physical function domain scores for the Quality of Life Questionnaire of the European Foundation for Osteoporosis were related to a high body mass index, lower physical activity, and the presence of vertebral fractures (p<0.05). CONCLUSION: Vertebral fractures are associated with decreased quality of life mainly physical functioning in older community-dwelling women regardless of age, body mass index, and physical activity. Therefore, the results highlight the importance of preventing and controlling asymptomatic vertebral fractures to reduce their impact on quality of life among older women.