67 resultados para UDI
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Objectives: To assess whether stress or mixed urinary incontinence (UI) is associated with deficits in executive functioning among community-dwelling women. Design: An observational study comparing the performance, using multivariate analyses of variance (MANOVAs) and Bonferroni post hoc test, of continent women and women with stress or mixed UI during executive control tasks. Setting: The research center of the Institut universitaire de gériatrie de Montréal. Participants: One hundred and fifty-five community-dwelling women aged 60 and older participated in the study. Measurements: Based on the Urogenital Distress Inventory (UDI), participants were split into three groups: 35 continent women, 43 women with stress UI, and 78 women with mixed UI. Participants completed a battery of neuropsychological tests and a computerized dual-task test. Results: Women with mixed UI showed poorer performances than continent and stress UI women in executive control functions. Deficits were specific to tests involving switching and sharing/dividing attention between two tasks. Conclusion: Results of this study suggest that mixed UI can be associated with executive control deficits in community-dwelling older women. Future intervention studies in the treatment of UI should take the higher risk of an executive control deficit in women with UI under consideration.
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Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.
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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.
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User Quality of Experience (QoE) is a subjective entity and difficult to measure. One important aspect of it, User Experience (UX), corresponds to the sensory and emotional state of a user. For a user interacting through a User Interface (UI), precise information on how they are using the UI can contribute to understanding their UX, and thereby understanding their QoE. As well as a user’s use of the UI such as clicking, scrolling, touching, or selecting, other real-time digital information about the user such as from smart phone sensors (e.g. accelerometer, light level) and physiological sensors (e.g. heart rate, ECG, EEG) could contribute to understanding UX. Baran is a framework that is designed to capture, record, manage and analyse the User Digital Imprint (UDI) which, is the data structure containing all user context information. Baran simplifies the process of collecting experimental information in Human and Computer Interaction (HCI) studies, by recording comprehensive real-time data for any UI experiment, and making the data available as a standard UDI data structure. This paper presents an overview of the Baran framework, and provides an example of its use to record user interaction and perform some basic analysis of the interaction.
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An overview is given of a user interaction monitoring and analysis framework called BaranC. Monitoring and analysing human-digital interaction is an essential part of developing a user model as the basis for investigating user experience. The primary human-digital interaction, such as on a laptop or smartphone, is best understood and modelled in the wider context of the user and their environment. The BaranC framework provides monitoring and analysis capabilities that not only records all user interaction with a digital device (e.g. smartphone), but also collects all available context data (such as from sensors in the digital device itself, a fitness band or a smart appliances). The data collected by BaranC is recorded as a User Digital Imprint (UDI) which is, in effect, the user model and provides the basis for data analysis. BaranC provides functionality that is useful for user experience studies, user interface design evaluation, and providing user assistance services. An important concern for personal data is privacy, and the framework gives the user full control over the monitoring, storing and sharing of their data.
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A comprehensive user model, built by monitoring a user's current use of applications, can be an excellent starting point for building adaptive user-centred applications. The BaranC framework monitors all user interaction with a digital device (e.g. smartphone), and also collects all available context data (such as from sensors in the digital device itself, in a smart watch, or in smart appliances) in order to build a full model of user application behaviour. The model built from the collected data, called the UDI (User Digital Imprint), is further augmented by analysis services, for example, a service to produce activity profiles from smartphone sensor data. The enhanced UDI model can then be the basis for building an appropriate adaptive application that is user-centred as it is based on an individual user model. As BaranC supports continuous user monitoring, an application can be dynamically adaptive in real-time to the current context (e.g. time, location or activity). Furthermore, since BaranC is continuously augmenting the user model with more monitored data, over time the user model changes, and the adaptive application can adapt gradually over time to changing user behaviour patterns. BaranC has been implemented as a service-oriented framework where the collection of data for the UDI and all sharing of the UDI data are kept strictly under the user's control. In addition, being service-oriented allows (with the user's permission) its monitoring and analysis services to be easily used by 3rd parties in order to provide 3rd party adaptive assistant services. An example 3rd party service demonstrator, built on top of BaranC, proactively assists a user by dynamic predication, based on the current context, what apps and contacts the user is likely to need. BaranC introduces an innovative user-controlled unified service model of monitoring and use of personal digital activity data in order to provide adaptive user-centred applications. This aims to improve on the current situation where the diversity of adaptive applications results in a proliferation of applications monitoring and using personal data, resulting in a lack of clarity, a dispersal of data, and a diminution of user control.
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Introducción Las pacientes con miomas uterinos pueden llegar a sufrir de síntomas urinarios y de disfunción sexual. Es para nosotros importante conocer la frecuencia de estas patologías en pacientes con miomas con indicación de cirugía atendidos en el Hospital Universitario Mayor Méderi y la relación entre estas tres entidades. Metodología Estudio cuasi experimental de antes-después. El estudio se encuentra dividido en dos fases, en esta primera fase a las pacientes se les aplicó los cuestionarios FSFI, IIQ-7 y UDI-6 antes de realizar el procedimiento quirúrgico. En una segunda fase se realizará un nuevo abordaje a los 6 y 12 meses donde se aplicarán los mismos instrumentos. Se utilizó coeficiente de Spearman y Kruskall-Wallis para evaluar la relación. Resultados En esta primera fase se incluyeron 81 participantes, con una mediana de años de 46 (RIQ=42-49) mínimo 33 y máximo 71 años. La mediana de miomas fue de 1 (RIQ1-2) máximo 5 miomas. El resultado total de la FSFI fue de 21(RIQ=18,5-25,5). La mediana de la escala UDI -6 fue de 50,4 (RIQ=0-31,2) y la mediana de IIQ-7 fue de 4,75 (RIQ=0-23,7). Se presentó una correlación negativa débil entre los puntajes de FSFI y los cuestionarios UDI-6 (-0.3604) e IIQ 7 (-0.3530), con una prevalencia de riesgo de disfunción sexual de 61%. Conclusiones En esta primera fase de la investigación se pudo observar una existencia de correlación entre la función sexual y la sintomatología urinaria. La prevalencia de disfunción sexual es mayor que en población de mujeres sin patología de miomas uterino.