Digital Health

Evidence-informed policy and practice comes from statistical and narrative health data. Evaluations to determine the effectiveness of interventions or policies, come from people like you and your own state of health. I plan to strike a conversation about how people feel about scientific data informing policies based on their own bodies.

Through auto-ethnographic #quantifiedself research, in which I am the subject and source of health-related data, I have become frustrated at the limits of an n=1 study spanning 10+ years. Sure, I identify patterns, change behaviour and set goals. I can also share information with friends. But I can’t stream my ‘small data’ into a larger project… for the advancement of science. Through this provocative talk, I will argue that my body should be our body in that we might collectively reap the benefits to be realised – through a bricolage of individual contributions for new kinds of big data.

Being overweight has consequences for many health outcomes including the fertility of both women and men. Weight loss is recommended, however, weight loss programmes suffer high dropout rates, limiting their success. Wearable devices are becoming popular and are now used in research to gain insight into behaviour and health outcomes. We can also use them to identify participants at risk of dropping out, providing an opportunity to intervene. I will discuss how using information surrounding individuals’ adherence to behaviour change could help develop a more effective weight loss programme.