Analysis of Nursing Dissertations and Theses on Mental Health, Brazil, 1979-2007

This bibliographic study analyzes scientific texts published in the CEPEn database in the mental health field (1979-2007). A total of 280 abstracts were investigated, of which 208 were Masters theses. The individuals investigated in these studies were professionals (57), patients (50), and professors and/or students (18). Among the themes addressed between 2000 and 2007 were the following: Nursing Care in Mental Health (40), Perception in Mental Health (37); and Transversality in Mental Health Care (27). This study provided an overview of the scientific research produced in the mental health field in Brazilian nursing graduate programs. We expect this study to elicit reflections concerning mental health care practice and enable new approaches for nursing promoting health and the prevention of diseases in order to enable patients to recover their citizenship, autonomy and quality of life.Se trata de un estudio bibliográfico, con el objetivo de analizar los textos científicos divulgados en la base de datos CEPEn en el área de salud mental (1979-2007). El total de resúmenes estudiados fueron 280, de los cuales 208 eran disertaciones de maestría. Los sujetos que se destacaron fueron los profesionales (57) y pacientes (50). Entre las temáticas abordadas se evidenciaron (2000-2007): el Cuidado de Enfermería en Salud Mental (40) y la Percepción en Salud Mental (37). Este trabajo posibilitó obtener una visión panorámica sobre la producción científica en salud mental en los cursos de Posgraduación en Enfermería en Brasil. Esperamos que el estudio incentive la reflexión sobre las prácticas de cuidado en salud mental y posibilite nuevos abordajes en enfermería con el objetivo de promover la salud y prevenir daños, de forma a favorecer la ciudadanía, la autonomía y la calidad de vida de los sujetos envueltos.Trata-se de estudo bibliográfico, com o objetivo de analisar os textos científicos, divulgados na base de dados CEPEn, na área de saúde mental (1979-2007). O total de resumos estudados foi 280, dos quais 208 constituíam-se de dissertações de mestrado. Os sujeitos que se destacaram foram os profissionais (57) e pacientes (50). Dentre as temáticas abordadas evidenciaram-se (2000-2007): o cuidado de enfermagem em saúde mental (40) e a percepção em saúde mental (37). Este trabalho possibilitou visualização panorâmica acerca da produção científica em saúde mental nos cursos de pós-graduação em enfermagem, no Brasil. Espera-se, aqui, que o estudo suscite reflexões acerca das práticas de cuidado em saúde mental e possibilite novas abordagens em enfermagem, com vistas à promoção da saúde e prevenção de agravos que favoreçam a cidadania, autonomia e qualidade de vida dos sujeitos envolvidos

Analysis of Nursing Dissertations and Theses on Mental Health, Brazil, 1979-2007

This bibliographic study analyzes scientific texts published in the CEPEn database in the mental health field (1979-2007). A total of 280 abstracts were investigated, of which 208 were Master’s theses. The individuals investigated in these studies were professionals (57), patients (50), and professors and/or students (18). Among the themes addressed between 2000 and 2007 were the following: Nursing Care in Mental Health (40), Perception in Mental Health (37); and Transversality in Mental Health Care (27). This study provided an overview of the scientific research produced in the mental health field in Brazilian nursing graduate programs. We expect this study to elicit reflections concerning mental health care practice and enable new approaches for nursing promoting health and the prevention of diseases in order to enable patients to recover their citizenship, autonomy and quality of life.Se trata de un estudio bibliográfico, con el objetivo de analizar los textos científicos divulgados en la base de datos CEPEn en el área de salud mental (1979-2007). El total de resúmenes estudiados fueron 280, de los cuales 208 eran disertaciones de maestría. Los sujetos que se destacaron fueron los profesionales (57) y pacientes (50). Entre las temáticas abordadas se evidenciaron (2000-2007): el Cuidado de Enfermería en Salud Mental (40) y la Percepción en Salud Mental (37). Este trabajo posibilitó obtener una visión panorámica sobre la producción científica en salud mental en los cursos de Posgraduación en Enfermería en Brasil. Esperamos que el estudio incentive la reflexión sobre las prácticas de cuidado en salud mental y posibilite nuevos abordajes en enfermería con el objetivo de promover la salud y prevenir daños, de forma a favorecer la ciudadanía, la autonomía y la calidad de vida de los sujetos envueltos.Trata-se de estudo bibliográfico, com o objetivo de analisar os textos científicos, divulgados na base de dados CEPEn, na área de saúde mental (1979-2007). O total de resumos estudados foi 280, dos quais 208 constituíam-se de dissertações de mestrado. Os sujeitos que se destacaram foram os profissionais (57) e pacientes (50). Dentre as temáticas abordadas evidenciaram-se (2000-2007): o cuidado de enfermagem em saúde mental (40) e a percepção em saúde mental (37). Este trabalho possibilitou visualização panorâmica acerca da produção científica em saúde mental nos cursos de pós-graduação em enfermagem, no Brasil. Espera-se, aqui, que o estudo suscite reflexões acerca das práticas de cuidado em saúde mental e possibilite novas abordagens em enfermagem, com vistas à promoção da saúde e prevenção de agravos que favoreçam a cidadania, autonomia e qualidade de vida dos sujeitos envolvidos

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

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