Intervenção de grupo em crianças com fendas lábio-palatinas: perspetiva clínica e perspetiva familiar

Dissertação de mestrado em Educação Especial (área de especialização em Intervenção Precoce)

A aprendizagem do léxico na compreensão leitora

Relatório de estágio de mestrado em Ensino do Português no 3.º Ciclo do Ensino Básico e no Ensino Secundário e do Espanhol nos Ensinos Básico e Secundário

Brazelton Neonatal Behavioral Assessment Scale: a psychometric study in a Portuguese sample

Background: The Neonatal Behavioral Assessment Scale (NBAS, Brazelton & Nugent, 1995) is an instrument conceived to observe the neonatal neurobehavior. Data analysis is usually performed by organizing items into groups. The most widely used data reduction for the NBAS was developed by Lester, Als, and Brazelton (1982). Objective: Examine the psychometric properties of the NBAS items in a sample of 213 Portuguese infants. Method: The NBAS was performed in the first week of infant life (3 days±2) and in the seventh week of life (52 days±5). Results: Principal component analyses yielded a solution of four components explaining 55.13% of total variance. Construct validity was supported by better neurobehavioral performance of 7-week-old infants compared with 1-week-old infants. Conclusion: Changes in the NBAS structure for the Portuguese sample are suggested compared to Lester factors in order to reach better internal consistency of the scale.

Psychological approach to endometriosis: Women's pain experience and quality of life improvement

Endometriosis is a chronic condition affecting 10 to15% of women in childbearing age. Understanding the impact of this disease on women’s well-being is still a challenge, namely to intervene. Pain is the most current and troublesome symptom. Although medical treatments for pain relief are effective, recurrence rate remains significant, calling for a better understanding and development of new approaches for pain management. A group Cognitive Behavioral Therapy (CBT) for management of associated co-morbidities is suggested, paying special attention to Chronic Pelvic Pain (CPP). CBT design can be grounded on information collected from focus groups and a one-group exploratory trial. Evaluation of therapy effectiveness is possible to be performed by comparing group CBT to Usual Care (UC) and Support Group (SG) in a randomized controlled trial. Research in this area could represent an important step in providing a solution to the management of endometriosis and, to the best of our knowledge, the first national psychological approach for its understanding and treatment.

Pervasive decision support to predict football corners and goals by means of data mining

Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.

SI2ME: um serviço de informação para o trabalho no binómio monitorização-melhoria, no setor educativo não superior em Portugal

Tese de Doutoramento em Tecnologias e Sistemas de Informação.