Help-seeking for 'memory loss' by older adults in India : patient, caregiver and health providers' perspectives

ABSTRACT: Background. In India, prevalence rates of dementia and prodromal amnestic Mild Cognitive Impairment (MCI) are 3.1% and 4.3% respectively. Most Indians refer to the full spectrum of cognitive disorders simply as ‘memory loss.’ Barring prevention or cure, these conditions will rise rapidly with population aging. Evidence-based policies and practices can improve the lives of affected individuals and their caregivers, but will require timely and sustained uptake. Objectives. Framed by social cognitive theories of health behavior, this study explores the knowledge, attitudes and practices concerning cognitive impairment and related service use by older adults who screen positive for MCI, their primary caregivers, and health providers. Methods. I used the Montreal Cognitive Assessment to screen for cognitive impairment in memory camps in Mumbai. To achieve sampling diversity, I used maximum variation sampling. Ten adults aged 60+ who had no significant functional impairment but screened positive for MCI and their caregivers participated in separate focus groups. Four other such dyads and six doctors/ traditional healers completed in-depth interviews. Data were translated from Hindi or Marathi to English and analyzed in Atlas.ti using Framework Analysis. Findings. Knowledge and awareness of cognitive impairment and available resources were very low. Physicians attributed the condition to disease-induced pathology while lay persons blamed brain malfunction due to normal aging. Main attitudes were that this condition is not a disease, is not serious and/or is not treatable, and that it evokes stigma toward and among impaired persons, their families and providers. Low knowledge and poor attitudes impeded help-seeking. Conclusions. Cognitive disorders of aging will take a heavy toll on private lives and public resources in developing countries. Early detection, accurate diagnosis, systematic monitoring and quality care are needed to compress the period of morbidity and promote quality of life. Key stakeholders provide essential insights into how scientific and indigenous knowledge and sociocultural attitudes affect use and provision of resources.

The stigma and prejudice of leprosy: influence on the human condition

INTRODUCTION: To analyze the knowledge, feelings and perceptions involving patients affected by leprosy, as a better understanding of these factors may be useful to decrease the stigma and prejudice associated with the condition. METHODS: The study cohort consisted of 94 patients who underwent treatment for leprosy at the Health Units in the City of Cuiabá, Mato Grosso (MT), Brazil. The study questionnaire included items to collect information on socio-demographic data, knowledge about the disease, stigma, prejudice, self-esteem and quality of life of leprosy patients. Bivariate analyses were used to assess the data based on the chi-square test with a 5% significance threshold. RESULTS: The results revealed that the study population consisted predominantly of males (55.3%) with an income between 1 and 3 times the minimum wage (67%). The survey respondents reported that the most significant difficulties related to the treatment were the side effects (44.7%) and the duration of the treatment (28.7%). A total of 72.3% of the subjects were knowledgeable about the disease, of whom 26.6% had the leprosy reaction. Stigma and prejudice were cited by 93.6% of the participants. Based on the responses, 40.4% of patients reported being depressed and sad, and 69.1% of the subjects encountered problems at work after being diagnosed. A total of 45.7% of the patients rated their quality of life between bad and very bad. CONCLUSIONS: Our results suggest that leprosy causes suffering in patients beyond pain and discomfort and greatly influences social participation.

"Virar a Sala de Aula”: centrar a aprendizagem no aluno recorrendo a ferramentas cognitivas

Relatório de projeto de mestrado em Ensino de Informática

Crescer com os outros: a aprendizagem cooperativa e o trabalho de grupo como estratégias fundamentais no desenvolvimento de competências sociais: o contributo do Projeto Curricular Integrado

Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1º Ciclo do Ensino Básico

Industrial engineering and management curriculum profile: Developing a framework of competences

This paper presents a framework of competences developed for Industrial Engineering and Management that can be used as a tool for curriculum analysis and design, including the teaching and learning processes as well as the alignment of the curriculum with the professional profile. The framework was applied to the Industrial Engineering and Management program at University of Minho (UMinho), Portugal, and it provides an overview of the connection between IEM knowledge areas and the competences defined in its curriculum. The framework of competences was developed through a process of analysis using a combination of methods and sources for data collection. The framework was developed according to four main steps: 1) characterization of IEM knowledge areas; 2) definition of IEM competences; 3) survey; 4) application of the framework at the IEM curriculum. The findings showed that the framework is useful to build an integrated vision of the curriculum. The most visible aspect in the learning outcomes of IEM program is the lack of balance between technical and transversal competences. There was not almost any reference to the transversal competences and it is fundamentally concentrated on Project-Based Learning courses. The framework presented in this paper provides a contribution to the definition of IEM professional profile through a set of competences which need to be explored further. In addition, it may be a relevant tool for IEM curriculum analysis and a contribution for bridging the gap between universities and companies.

Segurança contra incêndios na reabilitação sustentável de edifícios antigos

Dissertação de mestrado em Construção e Reabilitação Sustentáveis

Tax compliance and tax complexity in Portugal: essays on the perception of tax professionals

Tese de Doutoramento em Contabilidade.

Logic programming and artificial neural networks in breast cancer detection

About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.

Ontological representation of tumor-node-metastasis classification and an ontology-driven classifier: a study on colorectal cancer

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

Contributos dos ambientes digitais online para a aprendizagem em contexto de atividades de apoio extraescolar

Dissertação de mestrado em Ciências da Educação (área de especialização em Tecnologia Educativa)

A review of the development of regional sludge treatment centres and a baseline characterisation of Irish sewage sludges

This Study assessed the development of sludge treatment and reuse policy since the original 1993 National Sludge Strategy Report (Weston-FTA, 1993). A review of the 48 sludge treatment centres, current wastewater treatment systems and current or planned sludge treatment and reuse systems was carried out Sludges from all Regional Sludge Treatment Centres (areas) were characterised through analysis of selected parameters. There have been many changes to the original policy, as a result of boundary reviews, delays in developing sludge management plans, development in technology and changes in tendering policy, most notably a move to design-build-operate (DBO) projects. As a result, there are now 35 designated Hub Centres. Only 5 of the Hub Centres are producing Class A Biosolids. These are Ringsend, Killamey, Carlow, Navan and Osberstown. Ringsend is the only Hub Centre that is fully operational, treating sludge from surrounding regions by Thermal Drying. Killamey is producing Class A Biosolids using Autothermal Thermophilic Aerobic Digestion (ATAD) but is not, as yet, treating imported sludge. The remaining three plants are producing Class A Biosolids using Alkaline Stabilisation. Anaerobic Digestion with post pasteurisation is the most common form of sludge treatment, with 11 Hub Centres proposing to use it. One plant is using ATAD, two intend to use Alkaline Stabilisation, seven have selected Thermal Drying and three have selected Composting. While the remaining plants have not decided which sludge treatment to select, this is because of incomplete Sludge Management Plans and on DBO contracts. Analysis of sludges from the Hub Centres showed that all Irish sewage sludge is safe for agricultural reuse as defined by the Waste Management Regulations {Use of Sewage Sludge in Agriculture) (S.I. 267/2001), providing that a nutrient management plan is taken into consideration and that the soil limits of the 1998 (S.I. 148/1998) Waste Management Regulations are not exceeded.

Efficient knowledge retrieval to calibrate input variables in forest fire prediction

Forest fires are a serious threat to humans and nature from an ecological, social and economic point of view. Predicting their behaviour by simulation still delivers unreliable results and remains a challenging task. Latest approaches try to calibrate input variables, often tainted with imprecision, using optimisation techniques like Genetic Algorithms. To converge faster towards fitter solutions, the GA is guided with knowledge obtained from historical or synthetical fires. We developed a robust and efficient knowledge storage and retrieval method. Nearest neighbour search is applied to find the fire configuration from knowledge base most similar to the current configuration. Therefore, a distance measure was elaborated and implemented in several ways. Experiments show the performance of the different implementations regarding occupied storage and retrieval time with overly satisfactory results.

Productivity, Preferences and UIP deviations in an Open Economy Business Cycle Model

We show that a flex-price two-sector open economy DSGE model can explain the poor degree of international risk sharing and exchange rate disconnect. We use a suite of model evaluation measures and examine the role of (i) traded and non-traded sectors; (ii) financial market incompleteness; (iii) preference shocks; (iv) deviations from UIP condition for the exchange rates; and (v) creditor status in net foreign assets. We find that there is a good case for both traded and non-traded productivity shocks as well as UIP deviations in explaining the puzzles.

The Impact of Higher Education Institution-Firm Knowledge Links on Firm-level Productivity in Britain

This paper estimates whether both sourcing knowledge from and/or cooperating on innovation with HEIs (Higher Education Institutions)1 impacts on establishment-level total factor productivity (TFP) using a dataset created by merging the UK government’s Community Innovation Survey (CIS) with the Annual Respondents Database (ARD). It also considers whether higher graduate employment (as a measure of human capital) also impacts positively on TFP at the establishment-level. Many studies have investigated the relationship between university-firm knowledge links and innovation (see, for example, Mansfield, 1991; Becker, 2003; Thorn et al, 2007). Most of these studies find a positive impact. Fewer studies have investigated the impact of university-firm knowledge links on productivity. Belderbos et al. (2004), using the Dutch CIS, find that cooperation with universities has no statistically significant impact on the growth of labour productivity. Medda et al. (2005) find no statistically significant effect of collaborative research undertaken by Italian manufacturing firms and universities on the growth of TFP. Arvanitis et al. (2008), using Swiss data, show that university-firm knowledge and technology transfer has both a direct impact on labour productivity and an indirect impact through its positive impact on innovation. In sum, there is as yet no clear consensus as to the impact of university-firm knowledge links on productivity.

Interactive Epistemology and Reasoning: On the Foundations of Game Theory

Game theory describes and analyzes strategic interaction. It is usually distinguished between static games, which are strategic situations in which the players choose only once as well as simultaneously, and dynamic games, which are strategic situations involving sequential choices. In addition, dynamic games can be further classified according to perfect and imperfect information. Indeed, a dynamic game is said to exhibit perfect information, whenever at any point of the game every player has full informational access to all choices that have been conducted so far. However, in the case of imperfect information some players are not fully informed about some choices. Game-theoretic analysis proceeds in two steps. Firstly, games are modelled by so-called form structures which extract and formalize the significant parts of the underlying strategic interaction. The basic and most commonly used models of games are the normal form, which rather sparsely describes a game merely in terms of the players' strategy sets and utilities, and the extensive form, which models a game in a more detailed way as a tree. In fact, it is standard to formalize static games with the normal form and dynamic games with the extensive form. Secondly, solution concepts are developed to solve models of games in the sense of identifying the choices that should be taken by rational players. Indeed, the ultimate objective of the classical approach to game theory, which is of normative character, is the development of a solution concept that is capable of identifying a unique choice for every player in an arbitrary game. However, given the large variety of games, it is not at all certain whether it is possible to device a solution concept with such universal capability. Alternatively, interactive epistemology provides an epistemic approach to game theory of descriptive character. This rather recent discipline analyzes the relation between knowledge, belief and choice of game-playing agents in an epistemic framework. The description of the players' choices in a given game relative to various epistemic assumptions constitutes the fundamental problem addressed by an epistemic approach to game theory. In a general sense, the objective of interactive epistemology consists in characterizing existing game-theoretic solution concepts in terms of epistemic assumptions as well as in proposing novel solution concepts by studying the game-theoretic implications of refined or new epistemic hypotheses. Intuitively, an epistemic model of a game can be interpreted as representing the reasoning of the players. Indeed, before making a decision in a game, the players reason about the game and their respective opponents, given their knowledge and beliefs. Precisely these epistemic mental states on which players base their decisions are explicitly expressible in an epistemic framework. In this PhD thesis, we consider an epistemic approach to game theory from a foundational point of view. In Chapter 1, basic game-theoretic notions as well as Aumann's epistemic framework for games are expounded and illustrated. Also, Aumann's sufficient conditions for backward induction are presented and his conceptual views discussed. In Chapter 2, Aumann's interactive epistemology is conceptually analyzed. In Chapter 3, which is based on joint work with Conrad Heilmann, a three-stage account for dynamic games is introduced and a type-based epistemic model is extended with a notion of agent connectedness. Then, sufficient conditions for backward induction are derived. In Chapter 4, which is based on joint work with Jérémie Cabessa, a topological approach to interactive epistemology is initiated. In particular, the epistemic-topological operator limit knowledge is defined and some implications for games considered. In Chapter 5, which is based on joint work with Jérémie Cabessa and Andrés Perea, Aumann's impossibility theorem on agreeing to disagree is revisited and weakened in the sense that possible contexts are provided in which agents can indeed agree to disagree.