4 resultados para mental models

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Objective: The aim of this study was to assess re-hospitalization rates of individuals with psychosis and bipolar disorder and to study determinants of readmission. Methods: Prospective observational study, conducted in Sao Paulo, Brazil. One hundred-sixty-nine individuals with bipolar and psychotic disorder in need of hospitalization in the public mental health system were followed for 12 months after discharge. Their families were contacted by telephone and interviews were conducted at 1, 2, 6 and 12 months post-discharge to evaluate readmission rates and factors related. Results: One-year re-hospitalization rate was of 42.6%. Physical restraint during hospital stay was a risk factor (OR = 5.4-10.5) for readmission in most models. Not attending consultations after discharge was related to the 12-month point readmission (OR = 8.5, 95% CI 2.3-31.2) and to the survival model (OR = 3.2, 95% CI 1.5-7.2). Number of previous admissions was a risk factor for the survival model (OR = 6.6-11.9). Family's agreement with permanent hospitalization of individuals with mental illness was the predictor associated to readmission in all models (OR = 3.5-10.9) and resulted in shorter survival time to readmission; those readmitted were stereotyped as dangerous and unhealthy. Conclusions: Family's stigma towards mental illness might contribute to the increase in readmission rates of their relatives with psychiatric disorders. More studies should be conducted to depict mechanisms by which stigma increases re-hospitalization rates.

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Background Longitudinal epidemiological studies involving child/adolescent mental health problems are scarce in developing countries, particularly in regions characterized by adverse living conditions. We examined the influence of psychosocial factors on the trajectory of child/adolescent mental health problems (CAMHP) over time. Methods A population-based sample of 6- to 13-year-olds with CAMHP was followed-up from 2002–2003 (Time 1/T1) to 2007–2008 (Time 2/T2), with 86 out of 124 eligible children/adolescents at T1 being reassessed at T2 (sample loss: 30.6%). Outcome: CAMHP at T2 according to the Child Behavior Checklist/CBCL’s total problem scale. Psychosocial factors: T1 variables (child/adolescent’s age, family socioeconomic status); trajectory of variables from T1 to T2 (child/adolescent exposure to severe physical punishment, mother exposure to severe physical marital violence, maternal anxiety/depression); and T2 variables (maternal education, child/adolescent’s social support and pro-social activities). Results Multivariate analysis identified two risk factors for child/adolescent MHP at T2: aggravation of child/adolescent physical punishment and aggravation of maternal anxiety/depression. Conclusions The current study shows the importance of considering child/adolescent physical punishment and maternal anxiety/depression in intervention models and mental health care policies.

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Prenatal immune challenge (PIC) in pregnant rodents produces offspring with abnormalities in behavior, histology, and gene expression that are reminiscent of schizophrenia and autism. Based on this, the goal of this article was to review the main contributions of PIC models, especially the one using the viral-mimetic particle polyriboinosinic-polyribocytidylic acid (poly-I:C), to the understanding of the etiology, biological basis and treatment of schizophrenia. This systematic review consisted of a search of available web databases (PubMed, SciELO, LILACS, PsycINFO, and ISI Web of Knowledge) for original studies published in the last 10 years (May 2001 to October 2011) concerning animal models of PIC, focusing on those using poly-I:C. The results showed that the PIC model with poly-I:C is able to mimic the prodrome and both the positive and negative/cognitive dimensions of schizophrenia, depending on the specific gestation time window of the immune challenge. The model resembles the neurobiology and etiology of schizophrenia and has good predictive value. In conclusion, this model is a robust tool for the identification of novel molecular targets during prenatal life, adolescence and adulthood that might contribute to the development of preventive and/or treatment strategies (targeting specific symptoms, i.e., positive or negative/cognitive) for this devastating mental disorder, also presenting biosafety as compared to viral infection models. One limitation of this model is the incapacity to model the full spectrum of immune responses normally induced by viral exposure.

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OBJECTIVE: The aim of this study was to assess re-hospitalization rates of individuals with psychosis and bipolar disorder and to study determinants of readmission. METHODS: Prospective observational study, conducted in São Paulo, Brazil. One hundred-sixty-nine individuals with bipolar and psychotic disorder in need of hospitalization in the public mental health system were followed for 12 months after discharge. Their families were contacted by telephone and interviews were conducted at 1, 2, 6 and 12 months post-discharge to evaluate readmission rates and factors related. RESULTSOne-year re-hospitalization rate was of 42.6%. Physical restraint during hospital stay was a risk factor (OR = 5.4-10.5) for readmission in most models. Not attending consultations after discharge was related to the 12-month point readmission (OR = 8.5, 95%CI 2.3-31.2) and to the survival model (OR = 3.2, 95%CI 1.5-7.2). Number of previous admissions was a risk factor for the survival model (OR = 6.6-11.9). Family's agreement with permanent hospitalization of individuals with mental illness was the predictor associated to readmission in all models (OR = 3.5-10.9) and resulted in shorter survival time to readmission; those readmitted were stereotyped as dangerous and unhealthy. CONCLUSIONS: Family's stigma towards mental illness might contribute to the increase in readmission rates of their relatives with psychiatric disorders. More studies should be conducted to depict mechanisms by which stigma increases re-hospitalization rates.