Beyond quantified self
Proceedings of the extended abstracts of the 32nd annual ACM conference on Human factors in computing systems - CHI EA '14
Social sharing has been widely integrated into selftracking tools. By aggregating design recommendations from the prior work on these tools, we can offer general design principles for sharing personally collected data. In this work, we break down sharing into a series of dimensions and offer design considerations for each. From these considerations, we can prescribe how applications in new, unexplored areas can effectively integrate social sharing. Abstract Smartphone Apps hold potential to
... ciently support those with long-term conditions monitor and manage their symtoms. Despite the availability of Apps, little research has been done around effective design approaches. We present initial findings of a qualitative interview study aimed to generate a rich account of how people with asthma and diabetes decide to use an app to manage their condition. We discuss App usage, personal data usage, and clinical data usage. We draw out different purposes for which the data is used and question whether the design should focus so specifically on the data itself rather than the collection process. Abstract A growing number of people are living with chronic conditions, and tracking data about their health and bodies on a daily basis. There's an opportunity for the Quantified Self movement and future self-tracking solutions to not only help this population more effectively monitor and manage their conditions, but to provide real-time and in-context decision-making support for improved health and lifestyle outcomes. Designers will need to address unique requirements for people living with chronic conditions, as well as open issues around privacy, instinct, identity, and attention. Abstract Lifestyle diseases may result from inappropriate personal behavior such as poor diet, smoking, alcohol and other drugs, or lack of exercise. Modifying behavior may be all that is necessary to prevent the disease. We believe that pervasive logging and awareness interfaces can be useful for maintaining long term efforts to modify behavior and enhance health by enabling people to evaluate personal quantified hypotheses. We aim to explore which classes of interfaces are most effective for this. Abstract We discuss the potential for a new source of data for personal health maintenance, community-level data sourced from a variety of social networking sites. We present some preliminary results on extracting this kind of data from dating sites catering to men who have sex with men (MSM), and discuss possible user communities for this information.