A promoção da saúde no cuidado humanizado aos familiares de pessoas hospitalizadas em UTI adulta / The promotion of health in humanized care to the relatives of people hospitalized in an adult UTI

Para o paciente hospitalizado, o ambiente hospitalar é percebido como uma experiência desagradável, por isso os pacientes hospitalizados enfrentam muitas dificuldades, incluindo o ambiente desconhecido, a distância do grupo familiar, convivência com estranhos, procedimentos invasivos, limitações impostas pela doença, bem como perda da autonomia de seu próprio corpo. Este é um relato de experiência vivenciada pelos acadêmicos / membros do projeto de pesquisa e extensão Humanização: Humanizando para Humanizar o Curso de Graduação em Enfermagem das Faculdades INTA. A experiência ocorreu de janeiro a dezembro do ano de 2013, realizada na unidade de terapia intensiva adulto, de um hospital de referência no município de Sobral / CE, durante o ano de 2013. Foram realizadas reuniões semanais com o grupo, com a intenção para discutir tudo o que foi observado durante as visitas. O objetivo deste estudo foi oferecer cuidados voltados à humanização das famílias de pessoas internadas em Unidade de Terapia Intensiva. As ações do grupo caracterizam-se pelas ações humanizadoras, pelo acompanhamento e orientação à família, a fim de tranquilizá-las para o estado dos pacientes. Essa intervenção foi de grande relevância na garantia de um cuidado humanizado, mostrando que os familiares apresentavam maior segurança e conhecimento sobre o problema de seu familiar, ficando mais confortados no momento da visita, uma vez que todas as informações necessárias foram repassadas de forma clara e fácil. entender a linguagem. Concluiu-se que os aspectos qualitativos presentes na vida humana são de suma importância na compreensão das necessidades de cada pessoa. 

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