Programas de self-management em pacientes com DPOC: uma revisão sistemática

Introdução: Programas de self-management têm como objectivo habilitar os pacientes com estratégias necessárias para levar a cabo procedimentos específicos para a patologia. A última revisão sistemática sobre selfmanagament em DPOC foi realizada em 2007, concluindo-se que ainda não era possível fornecer dados claros e suficientes acerca de recomendações sobre a estrutura e conteúdo de programas de self-managament na DPOC. A presente revisão tem o intuito de complementar a análise da revisão anterior, numa tentativa de inferir a influência do ensino do self-management na DPOC. Objectivos: verificar a influência dos programas de self-management na DPOC, em diversos indicadores relacionados com o estado de saúde do paciente e na sua utilização dos serviços de saúde. Estratégia de busca: pesquisa efectuada nas bases de dados PubMed e Cochrane Collaboration (01/01/2007 – 31/08/2010). Palavras-chave: selfmanagement education, self-management program, COPD e pulmonary rehabilitation. Critérios de Selecção: estudos randomizados sobre programas de selfmanagement na DPOC. Extracção e Análise dos Dados: 2 investigadores realizaram, independentemente, a avaliação e extracção de dados de cada artigo. Resultados: foram considerados 4 estudos randomizados em selfmanagement na DPOC nos quais se verificaram benefícios destes programas em diversas variáveis: qualidade de vida a curto e médio prazo, utilização dos diferentes recursos de saúde, adesões a medicação de rotina, controle das exacerbações e diminuição da sintomatologia. Parece não ocorrer alteração na função pulmonar e no uso de medicação de emergência, sendo inconclusivo o seu efeito na capacidade de realização de exercício. Conclusões: programas de self-management aparentam ter impacto positivo na qualidade de vida, recurso a serviços de saúde, adesão à medicação, planos de acção e níveis de conhecimento da DPOC. Discrepâncias nos critérios de selecção das amostras utilizadas, períodos de seguimento desiguais, consistência das variáveis mensuradas, condicionam a informação disponibilizada sobre este assunto.

User perception and influencing factors of technology in everyday life

An increasing amount of research is being developed in the area where technology and humans meet. The success or failure of technologies and the question whether technology helps humans to fulfill their goals or whether it hinders them is in most cases not a technical one. User Perception and Influencing Factors of Technology in Everyday Life addresses issues of human and technology interaction. The research in this work is interdisciplinary, ranging from more technical subjects such as computer science, engineering, and information systems, to non-technical descriptions of technology and human interaction from the point of view of sociology or philosophy. This book is perfect for academics, researchers, and professionals alike as it presents a set of theories that allow us to understand the interaction of technology and humans and to put it to practical use.

Impacto de um programa de relaxamento na percepção de stress nos cuidadores formais de um lar do concelho de Águeda

O papel de cuidador formal é, habitualmente, exercido por profissionais devidamente qualificados, designadamente, médicos, enfermeiros psicólogos, assistentes sociais, terapeutas ocupacionais, fisioterapeutas e auxiliares. A sua formação académica, profissional é específica para o desempenho deste papel, integrada no contexto de uma actividade profissional onde são exercidas competências, no âmbito da saúde. Nos lares, hospitais, instituições comunitárias, entre outros, existem indivíduos que se enquadram no perfil traçado, a actividade é desgastante, quer física, quer psicologicamente, o que muitas vezes facilita o aparecimento da ansiedade e a percepção do stress. O relaxamento enquanto técnica terapêutica poderá atenuar o seu surgimento. Este trabalho teve como objectivo avaliar o impacto de um programa de relaxamento, na percepção de stress, nos cuidadores formais do lar da Liga de Amigos de Aguada de Cima. Para este fim, consideramos adequado um estudo do tipo experimental. Assim aplicámos á nossa amostra, dezasseis funcionárias, antes e depois da aplicação do programa de relaxamento progressivo de Jacobson, questionários de auto-preenchimento, adaptados à população portuguesa. Para além disso, nas dezasseis sessões que efectuámos, medimos a tensão arterial e a frequência cardíaca com um esfigmomanómetro digital de pulso, no período antes e depois da implementação do programa. Pela análise dos resultados que obtivemos, constatámos que não houve diferenças significativas do ponto de vista estatístico, entre a ansiedade e a percepção do stress, após o programa de relaxamento Jacobson. Confirmámos porém, que existiram diferenças em alguns itens dos questionários após a implementação do programa de relaxamento, assim como uma diminuição da pressão arterial diastólica e da correlação positiva entre a ansiedade e a percepção de stress. Desta forma, parece existir uma indicação de que o programa de relaxamento progressivo de Jacobson talvez tenha contribuído para minimizar o nível de stress das funcionárias do lar da Liga de Amigos de Aguada de Cima

Communication: The criticality of self-assembled rigid rods on triangular lattices

The criticality of self-assembled rigid rods on triangular lattices is investigated using Monte Carlo simulation. We find a continuous transition between an ordered phase, where the rods are oriented along one of the three (equivalent) lattice directions, and a disordered one. We conclude that equilibrium polydispersity of the rod lengths does not affect the critical behavior, as we found that the criticality is the same as that of monodisperse rodson the same lattice, in contrast with the results of recently published work on similar models. (C) 2011 American Institute of Physics. [doi:10.1063/1.3556665]

Self-optimization module for scheduling using case-based reasoning

Metaheuristics performance is highly dependent of the respective parameters which need to be tuned. Parameter tuning may allow a larger flexibility and robustness but requires a careful initialization. The process of defining which parameters setting should be used is not obvious. The values for parameters depend mainly on the problem, the instance to be solved, the search time available to spend in solving the problem, and the required quality of solution. This paper presents a learning module proposal for an autonomous parameterization of Metaheuristics, integrated on a Multi-Agent System for the resolution of Dynamic Scheduling problems. The proposed learning module is inspired on Autonomic Computing Self-Optimization concept, defining that systems must continuously and proactively improve their performance. For the learning implementation it is used Case-based Reasoning, which uses previous similar data to solve new cases. In the use of Case-based Reasoning it is assumed that similar cases have similar solutions. After a literature review on topics used, both AutoDynAgents system and Self-Optimization module are described. Finally, a computational study is presented where the proposed module is evaluated, obtained results are compared with previous ones, some conclusions are reached, and some future work is referred. It is expected that this proposal can be a great contribution for the self-parameterization of Metaheuristics and for the resolution of scheduling problems on dynamic environments.

Meta-heuristics self-configuration for scheduling

Scheduling resolution requires the intervention of highly skilled human problemsolvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. This paper addresses the resolution of complex scheduling problems using cooperative negotiation. A Multi-Agent Autonomic and Meta-heuristics based framework with self-configuring capabilities is proposed.

Self-optimization for dynamic scheduling in manufacturing systems

Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. In this paper, we describe a Self-Optimizing Mechanism for Scheduling System through Nature Inspired Optimization Techniques (NIT).

Parental cognitive dimensions associated with preschool children’s eating habits: an intervention study

Childhood excessive weight and obesity are a major public health concern from early childhood. Early childhood is an important period of development for developing healthy eating habits, that may be associated with an adequate present/future BMI. There is extensive evidence that children’s food intake is shaped by early experiences, suggesting ways in which parenting practices may be promoting obesity. But what leads parents to endorse healthier or detrimental educational practices and routines needs further study. 1. Perception of children’s weight: parents of overweight or obese children often fail to correctly perceive their children as overweight; failing to recognize their children’s excessive weight may impeach parents from implementing the best educational practices. 2. Concern: relation between the adequacy of mothers perception of their children’s weight and the level of concern - parental concern is be associated with parental practices. 3. Attribution of control: also, if parents do not consider their children’s eating behavior at least partially controllable by them, they may relinquish some of their responsibility in this area. Self-efficacy: evidence linking parental self-efficacy to parent competence and to parenting practices and behaviors; low parental self-efficacy related to the control of everyday behavior of young children may lead parents to abandon more consistent health practices and endorse permissive and inconsistent strategies. We designed 2 sequential studies that aim to contribute to the understanding of cognitive determinants of children’s eating patterns.

Case-based reasoning for meta-heuristics self-parameterization in a multi-agent scheduling system

A novel agent-based approach to Meta-Heuristics self-configuration is proposed in this work. Meta-heuristics are examples of algorithms where parameters need to be set up as efficient as possible in order to unsure its performance. This paper presents a learning module for self-parameterization of Meta-heuristics (MHs) in a Multi-Agent System (MAS) for resolution of scheduling problems. The learning is based on Case-based Reasoning (CBR) and two different integration approaches are proposed. A computational study is made for comparing the two CBR integration perspectives. In the end, some conclusions are reached and future work outlined.

Negotiation mechanism for self-organized scheduling system

This paper presents a negotiation mechanism for Dynamic Scheduling based on Swarm Intelligence (SI). Under the new negotiation mechanism, agents must compete to obtain a global schedule. SI is the general term for several computational techniques which use ideas and get inspiration from the social behaviors of insects and other animals. This work is concerned with negotiation, the process through which multiple selfinterested agents can reach agreement over the exchange of operations on competitive resources.

Self-organization for scheduling in agile manufacturing

Agility refers to the manufacturing system ability to rapidly adapt to market and environmental changes in efficient and cost-effective ways. This paper addresses the development of self-organization methods to enhance the operations of a scheduling system, by integrating scheduling system, configuration and optimization into a single autonomic process requiring minimal manual intervention to increase productivity and effectiveness while minimizing complexity for users. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to build future Decision Support Systems (DSS) for Scheduling in agile manufacturing environments.

Case-based reasoning for self-optimizing behavior

In this paper we present a Self-Optimizing module, inspired on Autonomic Computing, acquiring a scheduling system with the ability to automatically select a Meta-heuristic to use in the optimization process, so as its parameterization. Case-based Reasoning was used so the system may be able of learning from the acquired experience, in the resolution of similar problems. From the obtained results we conclude about the benefit of its use.

Self-optimization aspects for dynamic scheduling

Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. At this scenario, self-optimizing arise as the ability of the agent to monitor its state and performance and proactively tune itself to respond to environmental stimuli.

Self-optimizing through CBR learning

In this paper, we foresee the use of Multi-Agent Systems for supporting dynamic and distributed scheduling in Manufacturing Systems. We also envisage the use of Autonomic properties in order to reduce the complexity of managing systems and human interference. By combining Multi-Agent Systems, Autonomic Computing, and Nature Inspired Techniques we propose an approach for the resolution of dynamic scheduling problem, with Case-based Reasoning Learning capabilities. The objective is to permit a system to be able to automatically adopt/select a Meta-heuristic and respective parameterization considering scheduling characteristics. From the comparison of the obtained results with previous results, we conclude about the benefits of its use.

Self-managing agents for dynamic scheduling in manufacturing

The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using cooperative negotiation. Scheduling resolution requires the intervention of highly skilled human problem-solvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing (AC) evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference.