Estudo das vias de acesso aos cuidados psiquiátricos na equipa de Sintra

Resumo: O estudo das vias de acesso à consulta de Psiquiatria permite identificar os parceiros mais importantes no acesso dos utentes aos serviços psiquiátricos. O modelo de Goldberg-Huxley considera que o acesso às consultas de Psiquiatria se faz principalmente através dos cuidados de saúde primários. Material e Métodos: Para estudar as vias de acesso aos cuidados psiquiátricos utilizamos a Encounter Form, questionário desenvolvido por Gater. Foi também avaliada a classe social dos utentes utilizando a Escala de Graffar. Este inquérito foi passado na Consulta de Psiquiatria de Sintra a utentes de primeira consulta. A amostra estudada foi de 93 utentes. O objectivo do estudo foi conhecer a trajectória do utente desde que teve necessidade de ser consultado até chegar à consulta de Psiquiatria, os sintomas que determinaram a decisão de procurar ajuda e a influência da classe social no tempo de percurso. Resultados: Observa-se que os utentes passam pela Medicina Geral e Familiar em 71 % dos casos, pela Urgência Psiquiátrica em 16,1 % dos casos, pela Medicina Especializada Hospitalar em 10,7 % dos casos e pela Urgência Geral em 1,1 % dos casos. Na escala de Graffar a classe social prevalente é a média (Classe III). O tempo de percurso foi maior que em estudo similar realizado em 1991. A classe Social III foi a que teve tempo de percurso maior. Conclusões: O estudo conclui que o acesso a esta consulta de Psiquiatria se faz principalmente através da Medicina Geral e Familiar. O tempo de percurso é maior que o desejável por falta de recursos humanos.------- ABSTRACT: Introduction: The study of the Pathways to Psychiatric Care identifies the most important partners in accessing psychiatric services. The Goldberg- Huxley model believes that access to Psychiatric consultation is done preferably through the primary health care. Material and Methods: This survey included 93 first-time users of the Psychiatric Consultation of Sintra. The aim was to study the trajectory of the user since he had felt a need to be consulted until the consultation of Psychiatry, the symptoms that led to the decision to seek help and influence of social class in time spent in pathways. This study used the Encounter Form, a questionnaire developed by Gater. Social class of users was also assessed using the Scale of Graffar. Results: We observed that users have contact with General Practitionaires in 71% of cases, the Psychiatric Urgency in 16.1% of cases, the Hospital Medical Specialist in 10.7% of cases and the General Urgency in 1,1% of cases. On the Graffar scale middle class (Class III) was the most prevalent. The travel time spend in pathways was reater than that obtained in a similar study carried out in 1991. Social Class III group had a greater time spent on pathways. Conclusions: The study concludes that access to this Psychiatric consultation is principally through general practice. The time spent in pathways is greater than desirable due to lack of resources.

Fractional discrete-time signal processing: scale conversion and linear prediction

Nonlinear Dynamics, Vol. 29

Information technology service management: an experimental approach towards IT service prediction

Dissertation presented to obtain a Masters degree in Computer Science

Evaluating Dynamic Signage for Emergency Evacuation using an Immersive Video Environment

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Creation of a web application for smart park system and parking prediction study for system integration

In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.