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- How Health Literacy impacts Polytechnic of Leiria Students?Publication . Teixeira Ascenso, Rita Margarida; Luis, Luis; Dias, Sara; Gonçalves, DulceIn 2021, aHealth Literacy(HL) evaluation among university students revealed notable limitations in HL. To assess the general HL of populations comprehensively, the European HLSurvey Questionnaire (HLS-EU-Q) was developed, encompassing 12 subdomains to provide a broad perspective on public health. In 2014, the questionnaire was adapted for use in Portugal, resulting in the HLS-EU-PT version, validated through a 16-question survey (HLS-EU-PT-Q16).Global HL andthreedomains’ indexes and levelswere determined, namely Healthcare (HC), Disease prevention (DP), and Health Promotion (HP). The HLSEU-Q16-PT assessment demonstrated satisfactory internal consistency, with 0.8834Cronbach's alpha coefficient.In this study, an online survey distributedbetween 2020-2021among Polytechnic of Leiria academia allowed data collection from various stakeholders, including 251 students, 109 professors, 15 researchers, and 55 other staff. From the430 responses,75 questions were analysed. The saved data wasthefocus of this work, regarding a thesis of the first edition of the master’s in data science to analysethe 251 surveyed studentsand their HL. The results revealed that thesestudents have lower HL index, and, in this case study,health areadegreeor school impactsHL.
- Decision support system using mobile app statisticsPublication . Constante, Fabian; Guevara, Juan; Silva, Catarina; Gonçalves, Dulce; Marcelino, LuisNowadays to make the right decision about where and how to request or buy a service, a user is often supported by a mobile device that offers more than simple descriptive data. Nevertheless, not all information on services is fully accessible. The difficulty in keeping track of changes in services’ costs causes delays and can result in waste of time and money. In fact, the decision of which service to use usually involves some level of uncertainty and risk. Hence, the user should have access to some form of decision support system that could be easily available through mobile applications. The power of these devices allows to apply knowledge areas already developed, carrying statistics with dynamic and interactive graphics, thus allowing for a more systematic control of services and corresponding expenses. In this work we analyze the existing related work on mobile decision support systems and propose an architecture of a decision support system using Mobile App Statistics. Tests were carried out with a car fuel app to support the decision of choosing the gas station at each point. Results show that using the additional statistical information provided users can take better decisions during the request of a service.