Contribuições de experiências de estágio em CAPS III para a formação interdisciplinar em Saúde Mental na perspectiva da Reforma Psiquiátrica

Introdução: A formação dos profissionais da área da saúde é fundamental para a transformação das práticas de cuidado e consolidação dos princípios e diretrizes do Sistema Único de Saúde (SUS). Sendo um desafio do SUS, esta questão também está presente no campo da Saúde Mental e é necessária para a consolidação da Reforma Psiquiátrica e construção e fortalecimento da Rede de Atenção Psicossocial. Proposição: Investigar e refletir sobre as experiências dos estudantes que realizaram estágio no Centro de Atenção Psicossocial (CAPS) III Itaim Bibi entre 2009 e 2014, no tocante à formação profissional em Saúde Mental na perspectiva da Reforma Psiquiátrica. Materiais e Métodos: Estudo qualitativo, com construção dos dados a partir da leitura de relatórios dos estudantes e de questionários com perguntas referentes à experiência dos estágios, que foram apresentadas aos participantes conforme orientações do método Delphi. As questões abordaram: motivos; expectativas; forma e qualidade de participação nas atividades; temas e estudos; trabalho em equipe; situações vivenciadas; influência na atuação profissional; apresentação do estágio e sugestões de alterações. As informações foram trabalhadas por meio de Análise de Conteúdo Temática. Resultados: Dos 52 convidados, 28 participaram da primeira rodada (53,85%), sendo: 14 terapeutas ocupacionais, 9 enfermeiros, 3 psicólogos e 2 estudantes de Serviço Social. O segundo questionário foi composto por afirmativas presentes nas respostas recebidas para que os participantes as avaliassem conforme grau de concordância da escala Likert. Nesta fase foram recebidas 26 respostas. Conclusões: Apesar das dificuldades vivenciadas, avaliou-se que a maior parte das experiências dos estágios foi positiva e possibilitou aprendizagens significativas sobre o modelo de atenção psicossocial, o funcionamento e dinâmica da instituição, o trabalho em equipe interdisciplinar e as produções de convivência, principalmente aos sujeitos que realizaram estágios com maior carga horária. Identificaram como importantes aprendizados as experiências de acompanhamento individual e grupal dos usuários, a construção de Projeto Terapêutico Singular e de redes, o trabalho territorial e intersetorial. A participação em reuniões, supervisões clínico-institucionais, multiprofissionais e em oficinas de reflexão com as docentes das Universidades foi considerada importante para a formação. O aprendizado de manejo de situações de crise e de conflitos e de técnicas de contenção foi considerado superficial. Identificou-se que modelo de gestão e o trabalho da equipe influenciam no desenvolvimento de autonomia e protagonismo dos estagiários. O fortalecimento da integração ensino-serviço-comunidade é necessário e a flexibilização das propostas instituídas poderia facilitar a construção conjunta dos planos de estágios. Como produtos desta pesquisa foram elaboradas propostas de modificações para melhor organização dos estágios no CAPS e para a integração ensino-serviço e de Plano de Estágio Supervisionado em Terapia Ocupacional para os estágios extracurriculares. Realizou-se também uma Revisão Integrativa das publicações científicas brasileiras sobre a formação de estudantes de graduação em Saúde Mental na perspectiva da Reforma Psiquiátrica. Por fim, compreendeu-se que as experiências ressoam nas práticas profissionais dos graduados de modo positivo. Os participantes que não atuam neste campo, disseram levar consigo a experiência do trabalho em equipe e de formas éticas e humanizadas de cuidado.

Open business intelligence: on the importance of data quality awareness in user-friendly data mining

Citizens demand more and more data for making decisions in their daily life. Therefore, mechanisms that allow citizens to understand and analyze linked open data (LOD) in a user-friendly manner are highly required. To this aim, the concept of Open Business Intelligence (OpenBI) is introduced in this position paper. OpenBI facilitates non-expert users to (i) analyze and visualize LOD, thus generating actionable information by means of reporting, OLAP analysis, dashboards or data mining; and to (ii) share the new acquired information as LOD to be reused by anyone. One of the most challenging issues of OpenBI is related to data mining, since non-experts (as citizens) need guidance during preprocessing and application of mining algorithms due to the complexity of the mining process and the low quality of the data sources. This is even worst when dealing with LOD, not only because of the different kind of links among data, but also because of its high dimensionality. As a consequence, in this position paper we advocate that data mining for OpenBI requires data quality-aware mechanisms for guiding non-expert users in obtaining and sharing the most reliable knowledge from the available LOD.

A Model to Visualize Information in a Complex Streets’ Network

his paper discusses a process to graphically view and analyze information obtained from a network of urban streets, using an algorithm that establishes a ranking of importance of the nodes of the network itself. The basis of this process is to quantify the network information obtained by assigning numerical values to each node, representing numerically the information. These values are used to construct a data matrix that allows us to apply a classification algorithm of nodes in a network in order of importance. From this numerical ranking of the nodes, the process finish with the graphical visualization of the network. An example is shown to illustrate the whole process.

Assisting End-users in Filling Out Web Services

With the quick advance of web service technologies, end-users can conduct various on-line tasks, such as shopping on-line. Usually, end-users compose a set of services to accomplish a task, and need to enter values to services to invoke the composite services. Quite often, users re-visit websites and use services to perform re-occurring tasks. The users are required to enter the same information into various web services to accomplish such re-occurring tasks. However, repetitively typing the same information into services is a tedious job for end-users. It can negatively impact user experience when an end-user needs to type the re-occurring information repetitively into web services. Recent studies have proposed several approaches to help users fill in values to services automatically. However, prior studies mainly suffer the following drawbacks: (1) limited support of collecting and analyzing user inputs; (2) poor accuracy of filling values to services; (3) not designed for service composition. To overcome the aforementioned drawbacks, we need maximize the reuse of previous user inputs across services and end-users. In this thesis, we introduce our approaches that prevent end-users from entering the same information into repetitive on-line tasks. More specifically, we improve the process of filling out services in the following 4 aspects: First, we investigate the characteristics of input parameters. We propose an ontology-based approach to automatically categorize parameters and fill values to the categorized input parameters. Second, we propose a comprehensive framework that leverages user contexts and usage patterns into the process of filling values to services. Third, we propose an approach for maximizing the value propagation among services and end-users by linking a set of semantically related parameters together and similar end-users. Last, we propose a ranking-based framework that ranks a list of previous user inputs for an input parameter to save a user from unnecessary data entries. Our framework learns and analyzes interactions of user inputs and input parameters to rank user inputs for input parameters under different contexts.

Pedestrian accidents occurring on freeways: an investigation of causative factors, accident data collection and analysis. Volume III: appendixes. Final report, phases III and IV.

Federal Highway Administration, Washington, D.C.

Pedestrian accidents occurring on freeways: an investigation of causative factors, accident data collection and analysis. Volume I: executive summary. Final report, phases III and IV.

Federal Highway Administration, Washington, D.C.

Pedestrian accidents occurring on freeways: an investigation of causative factors, accident data collection and analysis. Volume II. Final report, phases III and IV.

Federal Highway Administration, Washington, D.C.

Causative factors and countermeasures for rural and suburban pedestrian accidents: accident data collection and analysis - appendices. Phase I and II.

Federal Highway Administration, Washington, D.C.

The use and analysis of recorded traffic accident data. Final report.

Texas State Department of Highways and Public Transportation, Transportation Planning Division, Austin

The use of computers in literature searching and related reference activities in libraries : papers presented at the 1975 Clinic on Library Applications of Data Processing, April 27-30, 1975 /

Includes bibliographical references.

Final report, data from the national drug and alcoholism treatment utilization survey (NDATUS) /

Title varies slightly.

CYP2D6: a global analysis of phenotypic and genotypic variation in search of radical cure of Plasmodium vivax malaria

Thesis (Master's)--University of Washington, 2016-06

Remotely sensed data for ecosystem analyses: Combining hierarchy and scene models

Remotely sensed data have been used extensively for environmental monitoring and modeling at a number of spatial scales; however, a limited range of satellite imaging systems often. constrained the scales of these analyses. A wider variety of data sets is now available, allowing image data to be selected to match the scale of environmental structure(s) or process(es) being examined. A framework is presented for use by environmental scientists and managers, enabling their spatial data collection needs to be linked to a suitable form of remotely sensed data. A six-step approach is used, combining image spatial analysis and scaling tools, within the context of hierarchy theory. The main steps involved are: (1) identification of information requirements for the monitoring or management problem; (2) development of ideal image dimensions (scene model), (3) exploratory analysis of existing remotely sensed data using scaling techniques, (4) selection and evaluation of suitable remotely sensed data based on the scene model, (5) selection of suitable spatial analytic techniques to meet information requirements, and (6) cost-benefit analysis. Results from a case study show that the framework provided an objective mechanism to identify relevant aspects of the monitoring problem and environmental characteristics for selecting remotely sensed data and analysis techniques.

Fuzzy logic in web data mining for website assessment

This paper proposes a novel application of fuzzy logic to web data mining for two basic problems of a website: popularity and satisfaction. Popularity means that people will visit the website while satisfaction refers to the usefulness of the site. We will illustrate that the popularity of a website is a fuzzy logic problem. It is an important characteristic of a website in order to survive in Internet commerce. The satisfaction of a website is also a fuzzy logic problem that represents the degree of success in the application of information technology to the business. We propose a framework of fuzzy logic for the representation of these two problems based on web data mining techniques to fuzzify the attributes of a website.

Ex ante evaluations of alternate data structures for end user queries: Theory and experimental test

The data structure of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. This research develops a methodology for evaluating, ex ante, the relative desirability of alternative data structures for end user queries. This research theorizes that the data structure that yields the lowest weighted average complexity for a representative sample of information requests is the most desirable data structure for end user queries. The theory was tested in an experiment that compared queries from two different relational database schemas. As theorized, end users querying the data structure associated with the less complex queries performed better Complexity was measured using three different Halstead metrics. Each of the three metrics provided excellent predictions of end user performance. This research supplies strong evidence that organizations can use complexity metrics to evaluate, ex ante, the desirability of alternate data structures. Organizations can use these evaluations to enhance the efficient and effective retrieval of information by creating data structures that minimize end user query complexity.