The quantification of the self is proliferated through social desire to share with others information about their physical activities and biodata. It is evident that the quantified self phenomenon and self-tracking culture are bringing about new possibilities to promote a sense of self-awareness and an autonomous approach to health management. However, the use of apps, devices and platforms which enable dataveillance become more and more embedded in our daily lives and activities. Such developments can lead to advancements in medicine and research.
A community of individuals who engage in the quantification of the self are allied through a company called Quantified Self Labs. In 2016, the global movement had over 70,000 members. QSI was set up as a “multidisciplinary network organisation, gathering knowledge about personalised health, generating new knowledge about self- tracking through applied scientific research and translating all this to education and entrepreneurship”. The data that is collected through quantified self-tracking is then used for research, stimulating innovations in healthcare.
Such healthcare tracking models also bring to light the importance of ‘Big Data’ generated through personal use of digital self-tracking devices. The Quantified Self movement relates to the use of wearable digital devices and sensing technology which collect data about a user’s everyday activities, and in the hands of medical researchers and professionals, algorithms could be produced which will be able to detect that certain physical activity patterns may be suggestive of certain medical conditions. Other data analytics tools will also emerge and will reveal how physical activity data may correlate with clinical outcomes for certain conditions. I think we may still be a few years away, because we need a critical mass of users to generate all this data, along with a group of motivated researchers who are willing to dig into all the activity trends and graphs. I believe we will see that in the next decade and will find ourselves in a new era where patient-generated big data will yield clinically meaningful information. The data and analytics need to connect with clinical endeavours to be translated into knowledge and actionable information.