Introdução à análise de dados em saúde com Python / Introduction to healthcare data analysis with Python

Este eBook foi elaborado no contexto do curso de capacitação Introdução à Análise de Dados em Saúde com Python ofertado pelo Centro de Inovação em Inteligência Artificial para Saúde. O curso tem como objetivo introduzir o estudo exploratório de bases de dados de saúde, com a utilização do Python. Neste eBook, procura-se apresentar uma abordagem preliminar à Ciência de Dados, que explora e descreve um conjunto de dados com técnicas da estatística descritiva e inferencial por meio da linguagem de programação Python. O público alvo que pretende-se atingir caracteriza-se por profissionais de saúde, alunos de graduação e pós-graduação, docentes e pesquisadores da área das ciências da saúde, exatas ou demais interessados em utilizar os recursos computacionais para análise de bases de dados em saúde. A linguagem Python tem se destacado como uma ferramenta poderosa para análise de dados em saúde, possuindo uma ampla gama de bibliotecas e recursos, o Python pode ser usado para limpar, processar, analisar e visualizar dados de saúde. Além disso, a comunidade de utilizadores da linguagem Python é muito colaborativa, com muitos recursos disponíveis, incluindo documentação, tutoriais e fóruns de suporte. O conteúdo foi agrupado em conceitos iniciais sobre a utilização dos dados em saúde, introdução ao Python para utilização de dados, conceitos de limpeza e tratamento de dados, aplicação da estatística descritiva com os sumários estatísticos e gráficos, técnicas de amostragens, aplicação da estatística inferencial com os testes de hipótese, de associação, de médias, de medianas e correlações, além de explorar a estilização de gráficos.

A Mobile Serious Game About the Pandemic (COVID-19 - Did You Know?): Design and Evaluation Study.

BACKGROUND: No treatment for COVID-19 is yet available; therefore, providing access to information about SARS-CoV-2, the transmission route of the virus, and ways to prevent the spread of infection is a critical sanitary measure worldwide. Serious games have advantages in the dissemination of reliable information during the pandemic; they can provide qualified content while offering interactivity to the user, and they have great reach over the internet. OBJECTIVE: This study aimed to develop a serious game with the purpose of providing science-based information on the prevention of COVID-19 and personal care during the pandemic while assessing players' knowledge about COVID-19-related topics. METHODS: The study was conducted with the interdisciplinary collaboration of specialists in health sciences, computing, and design at the Federal University of Minas Gerais, Brazil. The health recommendations were grouped into six thematic blocks, presented in a quiz format. The software languages were based on the progressive web app development methodology with the Ionic framework, JavaScript, HTML5, cascading style sheets, and TypeScript (Angular). Open data reports of how users interact with the serious game were obtained using the Google Analytics application programming interface. The visual identity, logo, infographics, and icons were carefully developed by considering a selection of colors, typography, sounds, and images that are suitable for young audiences. Cards with cartoon characters were introduced at the end of each thematic topic to interact with the player, reinforcing their correct answers or alerting them to the need to learn more about the disease. The players' performance was assessed by the rate of incorrect and correct answers and analyzed by linear correlation coefficient over 7 weeks. The agile SCRUM development methodology enabled quick and daily interactions of developers through a webchat and sequential team meetings. RESULTS: The game "COVID-19-Did You Know?" was made available for free on a public university website on April 1, 2020. The game had been accessed 17,571 times as of September 2020. Dissemination actions such as reports on social media and television showed a temporal correspondence with the access number. The players' error rate in the topic "Mask" showed a negative trend (r=-.83; P=.01) over the weeks of follow-up. The other topics showed no significant trend over the weeks. CONCLUSIONS: The gamification strategy for health education content on the theme of COVID-19 reached a young audience, which is considered to be a priority in the strategy of orientation toward social distancing. Specific educational reinforcement measures were proposed and implemented based on the players' performance. The improvement in the users' performance on the topic about the use of masks may reflect an increase in information about or adherence to mask use over time.