Percorrer por autor "Pimenta, Rui"
A mostrar 1 - 10 de 58
Resultados por página
Opções de ordenação
- Affinity coefficient for clustering autoregressive moving average modelsPublication . Nascimento, Ana Paula; Oliveira, Alexandra; Faria, Brígida Mónica; Pimenta, Rui; Vieira, Mónica; Prudêncio, Cristina; Nicolau, Helena BacelarIn various fields, such as economics, finance, bioinformatics, geology, and medicine, namely, in the cases of electroencephalogram, electrocardiogram, and biotechnology, cluster analysis of time series is necessary. The first step in cluster applications is to establish a similarity/dissimilarity coefficient between time series. This article introduces an extension of the affinity coefficient for the autoregressive expansions of the invertible autoregressive moving average models to measure their similarity between them. An application of the affinity coefficient between time series was developed and implemented in R. Cluster analysis is performed with the corresponding distance for the estimated simulated autoregressive moving average of order one. The primary findings indicate that processes with similar forecast functions are grouped (in the same cluster) as expected concerning the affinity coefficient. It was also possible to conclude that this affinity coefficient is very sensitive to the behavior changes of the forecast functions: processes with small different forecast functions appear to be well separated in different clusters. Moreover, if the two processes have at least an infinite number of π- weights with a symmetric signal, the affinity value is also symmetric.
- Análise fatorial de doenças não transmissíveis em função das taxas de mortalidade ao longo do tempoPublication . Nascimento, Ana Paula; Prudêncio, Cristina; Vieira, Mónica; Faria, Brígida Mónica; Pimenta, Rui; Bacelar-Nicolau, HelenaA Saúde Pública visaestudar, prevenir doenças, prolongar a vida e melhorar a qualidade de vida por meio de esforços organizados e escolhas informadas. Assim, é necessárioconhecer e analisar os fatores de saúde de uma população. A Análise de Dados Multivariada difere da Análise Estatística Multivariada clássica (confirmatória), pois nesta última o papel central está no modelo e nas inferências estatísticas, enquanto que na análise de dados multivariada são os dados que assumem o papel primordial. Atécnica de análise fatorial pode ajudar na procura de causas comuns ou fatores de risco para melhorar a medicina preventiva. Pretende-se, com o presente estudo, encontrar fatores de doenças não transmissíveis eventualmente sugestivos de um comportamento comum das mesmas, utilizando análise fatorial. Para encontrar fatores que expliquem as associações entre doenças não transmissíveis, foi aplicada a análise fatorial separadamente para o sexo masculino e feminino, e considerando como variáveis as taxas de mortalidade padronizadas ao longo do tempo de cada uma das doenças. Foram identificados três fatores de doenças não transmissíveis, no sexo feminino, explicando 80,36% da variância e quatro fatores de doenças não transmissíveis,no sexo masculino, explicando 77,22% da variância. Em ambos os sexos as doenças cerebrovasculares e a cardiopatia isquémica contribuem positivamente para o primeiro fator, o que é comum ser encontrado na literatura no caso do sexo masculino, aplicando métodos de cluster analysis. A análise fatorial juntamente com outras metodologias de análise de dados multivariados, pode ajudar na identificação de causas comuns ou fatores de risco para melhorar a medicina preventiva. O estudo dos fatores de risco e/ou mecanismos fisiopatológicos comuns que de uma forma direta ou indireta, possam potenciar o desenvolvimento comum das patologias encontradas nos grupos/fatores é prioritário dada a relevância das doenças não transmissíveis.
- Assessing diabetes health literacy, knowledge and empowerment in northern PortugalPublication . Morais, Carminda S.; Pimenta, Rui; Ferreira, Pedro Lopes; Boavida, José M.; Amorim, José P.We evaluated the disease management, knowledge and quality of life (QoL) of people with type 2 diabetes, followed in the ambulatory of a Hospital in the North of Portugal. A questionnaire of socio-demographic and clinical characterization, and Portuguese versions of the DES-SF, DKT and EQ-5D were administered to a random sample of 260 individuals. The results showed that people in general feel able of self-management, with a mean±SD score of 3.7±0.7. DKT registered 63.4±12.3% of correct answers among diabetes non-insulin-treated individuals and 65.7±12.4% among the insulin-treated (p<0.001). The QoL, evaluated through EQ-5D index, presented a mean value of 0.65±0.3. We evidenced a significant positive correlation between the ability to control, the knowledge and the QoL. The conclusions obtained may help promote QoL and literacy enhancement, as well as the empowerment of individuals with type 2 diabetes.
- Assessing sleep quality of professional drivers: an analysis based on self-perceived and sleep companions' feedbackPublication . Lopes, T.; Faria, Brigida Monica; Oliveira, Alexandra; Pimenta, Rui; Reis, L. P.Portugal has been ranked as the fourth European country with the highest incidence of falling asleep while driving. The quality of sleep comprises both quantitative aspects, such as sleep duration and sleep latency, and qualitative aspects, such as mood and health status. Neglecting the quality and quantity of sleep can result in fatigue, affecting multiple aspects of safe driving, such as attentiveness to the road. Although quantitative measures of sleep are easy to assess, evaluating subjective aspects of sleep is more challenging. Poor sleep quality and habits were the most commonly cited reasons for falling asleep at the wheel. Given the high prevalence of road accidents in Portugal and the significant impact of sleep quality on driving safety, there is a need for comprehensive research on the sleep quality of professional drivers. Adult sleep is often a shared activity between sleep companions, making it a crucial aspect to investigate for a better understanding of sleep perceptions. The main objective of this study is to analyze the sleep quality of a population of Portuguese professional drivers and compare it with the responses given by their sleep companions.
- Assessing statistical reasoning through project workPublication . Pimenta, RuiNew technologies involve a reformulation of contents and methodology used for teaching statistics. Developing students’ statistical reasoning becomes an important task for teachers of applied statistics. This is particularly true in the field of health sciences. In this work the statistical reasoning ability acquired by health sciences students was evaluated in the context of their final undergraduate project.
- Atitudes face à estatística em diferentes grupos de profissionais de saúde em formaçãoPublication . Pimenta, Rui; Pereira, Ilídio; Costa, Elísio; Vieira, MargaridaUma grande parte das decisões que os profissionais de saúde tomam no seu dia-a-dia tem suporte estatístico num modelo que integre a prática clínica baseada na evidência. A atitude que estes profissionais têm face à estatística pode condicionar o exercício da competência estatística na sua prática clínica e o correcto desenvolvimento da intuição estatística. Neste trabalho, analisámos as diferentes componentes das atitudes face à estatística de estudantes e profissionais em formação, em distintas áreas de formação clínica e em distintos ciclos formativos, através das suas respostas ao Inquérito Atitudes Face à Estatística (SATS 28). Pretendemos, em primeiro lugar, avaliar a e analisar a relação entre as componentes das atitudes na nossa amostra. De seguida, recorremos a técnicas de visualização radial para verificar que componentes das atitudes permitem explicar melhor a variação das respostas dos estudantes. Por último, pretendemos comparar as atitudes face à estatística em diferentes grupos de profissionais em formação tomando em linha de conta a sua situação face à graduação. Recorremos a uma análise de variância a dois factores para estudar a interacção entre os factores área de formação e situação face à graduação e comparar os resultados obtidos nos diferentes grupos que decorrem desta análise. Os nossos resultados mostram que os estudantes das ciências da saúde têm, geralmente, uma atitude positiva face à estatística embora a dificuldade percebida seja mais relevante do que em estudos realizados anteriormente noutras áreas de formação.
- Building instrument to assess user satisfaction in communicating with health professionals based on the consensus of the Delphi methodPublication . Santos, A. H.; Pimenta, Rui; Santos, Paula Clara; Moreira, PauloRecent research in user-health professionals communication have emphasized the need to develop new instruments to evaluate user satisfaction in communicating with health professionals
- Can a statistics course improve health sciences students' attitudes towards statistics?Publication . Pimenta, Rui Esteves; Borges, Janete; Nascimento, Ana Paula; Alves, Sandra; Faria, Brígida; Pereira, Ilídio; Martins, João Paulo; Pimenta, Rui; Borges, Janete; Nascimento, Ana Paula; Alves, Sandra Maria; Faria, Brigida Monica; Oliveira Martins, João PauloIn educating future health professionals, it is not only the technical understanding of statistics that matters, but also how students perceive its relevance and grasp its core concepts. When statistics is presented in a way that feels meaningful and accessible, students are more likely to engage with it, and develop a positive attitude toward statistics (ATS). Positive ATS can make a significant difference—not only in how effectively students learn, but also in whether they are prepared to use data thoughtfully in everyday decision-making. Either personal lives or clinical practice, where evidence-based reasoning plays a central role. If one of the goals of statistics education is to enhance more positive ATS, then it becomes essential to assess students’ ATS both before and after instruction. Doing so allows educators to better understand the impact of statistical training. This study aims to assess the changes in attitudes towards statistics among higher education students in a health science institution, following attendance of a statistics course. Students enrolled in a statistics course at a health sciences school were surveyed at the beginning and end of the course using the Survey of Attitudes Toward Statistics (SATS-28) instrument. STAS-28 is an item scale (5 points Likert scale, Strongly Disagree (1) Strongly Agree (5)) with 4 domains: Affect, Cognitive, Value and Difficulty. The total and domains scores were obtained using the mean response of the corresponding items, higher values correspond to positive attitudes. To evaluate changes in students’ ATS paired-samples t-tests were conducted across the 4 domains and the overall attitudes score. In addition to statistical significance testing, effect sizes were calculated using Cohen’s d to assess the practical significance of observed changes. A total of 152 completed the assessment in the two periods, with a majority being female (88.2%, n=134) and 11.8% male (n=18). About half of the participants were aged between 18-20 years (n=87, 57.2%). Regarding academic status only 11 (7.2%) were working students. About 26% (n=40) of the students had already failed a course. Statistically significant improvements were found in the Affective domain: beginning (M1 = 2.93, SD = 0.53) versus end of the course (M2= 3.08, SD = 0.59), t(151) = 2.91, p = .004 (Cohen’s d = 0.61), Cognitive domain: (M1 = 3.54, SD = 0.63) versus (M2 = 3.74, SD = 0.64), t(151) = 3.92, p < .001 (Cohen’s d = 0.62), and Difficulty domain (M1 = 2.77, SD = 0.57) to (M2 = 2.89, SD = 0.59), t(151) = 2.61, p = .010 (Cohen’s d = 0.58). In the overall attitudes toward statistics, there was also an improvement (M1 = 3.18, SD = 0.45) versus (M2 = 3.31, SD = 0.49), t(151) = 3.37, p < .001 (Cohen’s d = 0.45) . These changes were associated with small to moderate effect sizes, indicating meaningful improvements during the course. Regarding the Value domain, no statistical significant change was identified (M1 = 3.49, SD = 0.67) (M2 = 3.52, SD = 0.68), t(151) = 0.56, p = .575. While perceived value, remain stable, overall, the results indicate that students developed more positive affective and cognitive ATS and perceived it as less difficult by the end of the course. These improvements, while modest in magnitude, suggest a meaningful improvement in students’ overall ATS and can meaningfully impact students’ learning experience and long-term confidence with statistics.
- Cluster analysis of noncommunicable diseases in PortugalPublication . Nascimento, Ana Paula; Prudêncio, Cristina; Vieira, Mónica; Pimenta, Rui; Bacelar-Nicolau, HelenaThe most common noncommunicable diseases, such as cardiovascular diseases, cancer or respiratory diseases, are a problem in global and national growth. The World Health Organization (WHO) considers it a priority to study the specific causes of these diseases for trend monitoring. The aim is to identify a hierarchy of clusters of Portuguese mortality by noncommunicable diseases using the ascending hierarchical classification methodology. The results identifying three clusters A, A2 and B2 of diseases are proposed for study. It is suggested that the risk factors and / or pathophysiological mechanisms that in a direct or indirect way may enhance the common development of the pathologies found in the clusters studied should be an object of priority study.
- Comparing time series forecasting models for health indicators: A clustering analysis approachPublication . Vinhal, Cláudia; Oliveira, Alexandra; Faria, Brígida; Nascimento, Ana Paula; Pimenta, Rui; Oliveira, Alexandra; Faria, Brigida Monica; Pimenta, RuiTime series are the sequence of observations ordered by equal time intervals, crucial for understanding causality, trends, and forecasts. Its analysis can be applied to several areas, such as engineering, finance, and health (1,2). One problem with the time series study is clustering, mainly understanding when two parametric time series are considered similar (3). The sum of mortality and morbidity, referred to as “Burden of Disease”, is measured by a metric called “Disability Adjusted Life Years” (DALYs) (4). These indicators are direct measures of health care needs, reflecting the global burden of disease in the population, and are crucial for public health study and surveillance (5). DALYs can be represented by Autoregressive Integrated Moving Averages (ARIMA) models, and in this context understanding clusters is crucial. The primary goal is to compare different distance measures between ARIMA processes when used in clustering techniques. The study begins by exploring the temporal characteristics of DALYs, highlighting underlying patterns and trends. Then, ARIMA models are applied to represent and describe the time series. It’s on this representation of the time series that the Piccolo, the Maharaj, and the LPC distance measures are applied to use clustering techniques and identify clusters. Additionally, 8 distinct cluster validation metrics are used. Specific to 48 European countries, the results show that the choice of distance measure can greatly influence clustering outcomes and the number of clusters formed. While certain methods revealed geographic patterns, other factors, such as cultural or economic similarities, also influence cluster formation. These insights contribute to advancing the field of public health surveillance and intervention, ultimately aiming to alleviate the global burden of disease. This study offers insights into applying ARIMA processes in clustering techniques for analysing temporal health data. By comparing different distance measures, this research improves our understanding of underlying patterns and trends in health indicators over time.