VIOLENTAS OU VITIMADAS? A REDE DE ASSISTÊNCIA E ATENÇÃO SOCIAL E SUA DESATENÇÃO QUANTO À FAMÍLIA

A presente pesquisa tem como objetivo principal falar sobre estruturas familiares em situações de violências referenciadas no âmbito do Centro de Referência Especializado de Assistência Social - CREAS, e as modificações destas dinâmicas parentais contextualizadas nos diversos cotidianos. Discorremos sobre as várias formas de violência que essas famílias são submetidas como também, se fazem violentas como efeito de relações de descuido e desatenção da rede de assistência social, salientando as diferentes ocorrências deste movimento que emergem como demanda nos estabelecimentos que estivemos estagiando durante o ano de 2016. Ao discorrer sobre esta pesquisa, falamos das vivências do Estágio Supervisionado Curricular Obrigatório Específico I, da Universidade Paranaense – Unipar, do Curso de Psicologia 4º ano que se faz através de práticas localizadas em territórios que denominamos aqui como sociais. Optamos por trabalhar com a pesquisa bibliográfica, referenciada pela observação participante, utilizando-se da metodologia calçada por perspectivas histórico sociais e por obras de estudiosos contemporâneos que dialogam sobre famílias e contextos da assistência social

Glossário de responsabilidade social

Este Glossário de Responsabilidade Social é um produto da RSO PT, pelo que as referências ao mesmo deverão ser efetuadas mencionando o nome do documento e os seus autores: Rede RSO PT, GT ISO 26000, Glossário de Responsabilidade Social, (2013)Este Glossário de Responsabilidade Social foi desenvolvido no âmbito da Rede RSO PT, no Grupo de Trabalho da ISO 26 000 (GT ISO 26000). A missão do GT ISO 26000 consiste em promover e aprofundar o conhecimento sobre a norma NP ISO 26000 Linhas de Orientação para a Responsabilidade Social. O Glossário de Responsabilidade Social seguiu a estrutura da norma de referência NP ISO 26000 Linhas de orientação para a responsabilidade social, pelo que os termos se encontram associados aos sete temas da norma.APEE; APSHSTDC; BSD; Câmara Municipal da Amadora; Câmara Municipal de Loures; Câmara Municipal de Oliveira de Azeméis; CIG; CITE; Coordenada Social; CTCV; Edit Value; GEBALIS; IAPMEI; Instituto de Informática, IP; Instituto Português da Qualidade; Montepio; Process Advice; State of The Art; Universidade Abert

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Assessment of risk scores to predict mortality of COVID-19 patients admitted to the intensive care unit

ObjectivesTo assess the ABC2-SPH score in predicting COVID-19 in-hospital mortality, during intensive care unit (ICU) admission, and to compare its performance with other scores (SOFA, SAPS-3, NEWS2, 4C Mortality Score, SOARS, CURB-65, modified CHA2DS2-VASc, and a novel severity score).Materials and methodsConsecutive patients (≥ 18 years) with laboratory-confirmed COVID-19 admitted to ICUs of 25 hospitals, located in 17 Brazilian cities, from October 2020 to March 2022, were included. Overall performance of the scores was evaluated using the Brier score. ABC2-SPH was used as the reference score, and comparisons between ABC2-SPH and the other scores were performed by using the Bonferroni method of correction. The primary outcome was in-hospital mortality.ResultsABC2-SPH had an area under the curve of 0.716 (95% CI 0.693–0.738), significantly higher than CURB-65, SOFA, NEWS2, SOARS, and modified CHA2DS2-VASc scores. There was no statistically significant difference between ABC2-SPH and SAPS-3, 4C Mortality Score, and the novel severity score.ConclusionABC2-SPH was superior to other risk scores, but it still did not demonstrate an excellent predictive ability for mortality in critically ill COVID-19 patients. Our results indicate the need to develop a new score, for this subset of patients

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Democracia e violência: a modernização por baixo Democracy and violence

A violência no Rio, ao contrário do que se é levado a crer pela sua reelaboração mítica, não é produzida primordialmente pela pobreza e pela exclusão. O déficit do Estado é uma causa muito mais importante do fenômeno nos anos 80. E há certas formas de violência juvenil no Rio - o "surfe ferroviário", o "arrastão" - que devem ser entendidas em termos de uma modernização por baixo da sociedade brasileira.<br>Contrarily to what one is lead to believe by its mytical reelabo-ration violence in Rio is not primordially produced by poverty and exclusion. The lack of state services is much more important as a cause of violence during the eighties. Moreover, some forms of youthfull violence are best understood as a kind of restricted modernization

Palliative care and COVID-19: acknowledging past mistakes to forge a better future

ContextCOVID-19 induces complex distress across physical, psychological, and social realms and palliative care (PC) has the potential to mitigate this suffering significantly.ObjectivesTo describe the clinical characteristics and outcomes of COVID-19 patients with an indication of PC, compared to patients who had no indication, in different pandemic waves.MethodsThis retrospective multicenter observational cohort included patients from 40 hospitals, admitted from March 2020 to August 2022. Patients who had an indication of palliative care (PC) described in their medical records were included in the palliative care group (PCG), while those who had no such indication in their medical records were allocated to the non-palliative care group (NPCG).ResultsOut of 21,158 patients, only 6.7% had indication for PC registered in their medical records. The PCG was older, had a higher frequency of comorbidities, exhibited higher frailty, and had a higher prevalence of clinical complications and mortality (81.4% vs. 17.7%, p &lt; 0.001), when compared to the NPCG. Regarding artificial life support, the PCG had a higher frequency of dialysis (20.4% vs. 10.1%, p &lt; 0.001), invasive mechanical ventilation (48.2% vs. 26.0%, p &lt; 0.001) and admission to the intensive care unit (53.6% vs. 35.4%, p &lt; 0.001). These differences were consistent across all three waves.ConclusionA low proportion of patients received PC. Patients in PCG were more fragile, had more clinical complications, and had a higher mortality. On the contrary to our expectations, they received more artificial life support in all three waves. Taken together, these findings suggest that decisions regarding PC indication were made too late, within a context of end-of-life and therapeutic failure

Table_3_Assessment of risk scores to predict mortality of COVID-19 patients admitted to the intensive care unit.docx

ObjectivesTo assess the ABC2-SPH score in predicting COVID-19 in-hospital mortality, during intensive care unit (ICU) admission, and to compare its performance with other scores (SOFA, SAPS-3, NEWS2, 4C Mortality Score, SOARS, CURB-65, modified CHA2DS2-VASc, and a novel severity score).Materials and methodsConsecutive patients (≥ 18 years) with laboratory-confirmed COVID-19 admitted to ICUs of 25 hospitals, located in 17 Brazilian cities, from October 2020 to March 2022, were included. Overall performance of the scores was evaluated using the Brier score. ABC2-SPH was used as the reference score, and comparisons between ABC2-SPH and the other scores were performed by using the Bonferroni method of correction. The primary outcome was in-hospital mortality.ResultsABC2-SPH had an area under the curve of 0.716 (95% CI 0.693–0.738), significantly higher than CURB-65, SOFA, NEWS2, SOARS, and modified CHA2DS2-VASc scores. There was no statistically significant difference between ABC2-SPH and SAPS-3, 4C Mortality Score, and the novel severity score.ConclusionABC2-SPH was superior to other risk scores, but it still did not demonstrate an excellent predictive ability for mortality in critically ill COVID-19 patients. Our results indicate the need to develop a new score, for this subset of patients.</p