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BACKGROUND: Wearables have been used widely for monitoring health in general, and recent research results show that they can be used to predict infections based on physiological symptoms. To date, evidence has been generated in large, population-based settings. In contrast, the Quantified Self and Personal Science communities are composed of people who are interested in learning about themselves individually by using their own data, which are often gathered via wearable devices. OBJECTIVE: This study aims to explore how a cocreation process involving a heterogeneous community of personal science practitioners can develop a collective self-tracking system for monitoring symptoms of infection alongside wearable sensor data. METHODS: We engaged in a cocreation and design process with an existing community of personal science practitioners to jointly develop a working prototype of a web-based tool for symptom tracking. In addition to the iterative creation of the prototype (started on March 16, 2020), we performed a netnographic analysis to investigate the process of how this prototype was created in a decentralized and iterative fashion. RESULTS: The Quantified Flu prototype allowed users to perform daily symptom reporting and was capable of presenting symptom reports on a timeline together with resting heart rates, body temperature data, and respiratory rates measured by wearable devices. We observed a high level of engagement; over half of the users (52/92, 56%) who engaged in symptom tracking became regular users and reported over 3 months of data each. Furthermore, our netnographic analysis highlighted how the current Quantified Flu prototype was a result of an iterative and continuous cocreation process in which new prototype releases sparked further discussions of features and vice versa. CONCLUSIONS: As shown by the high level of user engagement and iterative development process, an open cocreation process can be successfully used to develop a tool that is tailored to individual needs, thereby decreasing dropout rates.
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Dispositivos Eletrônicos Vestíveis , HumanosRESUMO
More than ever, humanity relies on robust scientific knowledge of the world and our place within it. Unfortunately, our contemporary view of science is still suffused with outdated ideas about scientific knowledge production based on a naive kind of realism. These ideas persist among members of the public and scientists alike. They contribute to an ultra-competitive system of academic research, which sacrifices long-term productivity through an excessive obsession with short-term efficiency. Efforts to diversify this system come from a movement called democratic citizen science, which can serve as a model for scientific inquiry in general. Democratic citizen science requires an alternative theory of knowledge with a focus on the role that diversity plays in the process of discovery. Here, we present such an epistemology, based on three central philosophical pillars: perspectival realism, a naturalistic process-based epistemology, and deliberative social practices. They broaden our focus from immediate research outcomes towards cognitive and social processes which facilitate sustainable long-term productivity and scientific innovation. This marks a shift from an industrial to an ecological vision of how scientific research should be done, and how it should be assessed. At the core of this vision are research communities that are diverse, representative, and democratic.
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Although adherence to Mertonian values of science (i.e., communism, universalism, organized skepticism, disinterestedness) is desired and promoted in academia, such adherence can cause friction with the normative structures and practices of Open Science. Mertonian values and Open Science practices aim to improve the conduct and communication of research and are promoted by institutional actors. However, Mertonian values remain mostly idealistic and contextualized in local and disciplinary cultures and Open Science practices rely heavily on third-party resources and technology that are not equally accessible to all parties. Furthermore, although still popular, Mertonian values were developed in a different institutional and political context. In this article, we argue that new normative structures for science need to look beyond nostalgia and consider aspirations and outcomes of Open Science practices. To contribute to such a vision, we explore the intersection of several Open Science practices with Mertonian values to flesh out challenges involved in upholding these values. We demonstrate that this intersection becomes complicated when the interests of numerous groups collide and contrast. Acknowledging and exploring such tensions informs our understanding of researchers' behavior and supports efforts that seek to improve researchers' interactions with other normative structures such as research ethics and integrity frameworks.
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The United Nations' Sustainable Development Goals (SDGs) highlight priority areas for global sustainable development, such as reducing inequalities and protecting the environment. Digital platforms, such as Goteo.org, facilitate financial support from individuals for SDG-related initiatives through crowdfunding and match-funding campaigns. Match-funding is a type of crowdfunding, where individual donations are matched or multiplied by public and private organizations. There remains a lack of open data, however, to study the effectiveness of match-funding as a way to finance these civic initiatives. The Goteo.org platform's approach to data transparency and open source principles have allowed these data to be collected, and here we present a dataset for 487 civic crowdfunding campaigns. This dataset presents a unique opportunity to compare the behaviour of different crowdfunding modalities in parallel with the SDGs.
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[This corrects the article DOI: 10.1016/j.heliyon.2019.e01447.].