Self-tracking the microbiome: where do we go from here?

Abstract

The quantified self community brings together enthusiasts who are using technological devices to monitor their health and social media to share their personal data with others online. In light of the growing popularity of this movement, self-trackers are challenging the health-care system by raising important questions about data ownership and risk-taking. As we enter a new era of consumer genomics, a significant number of quantified self (QS) individuals are now interested in the monitoring of their microbiome and performing personal interventions. In this paper, we discuss the scientific validity of experiments involving serial observations of a single individual as opposed to randomized clinical trials. We look at self-tracking from an ethical standpoint by questioning the risks and assessing the potential benefits for personalized medicine in general and for microbiome research in particular.

Single-Subject Studies in Translational Nutrition Research

“…This interest is taken to the extreme by individuals within the ‘quantified self’ movement in which participants knowingly experiment on themselves to determine optimal ways of living. (25, 33, 49, 92, 103) However, most studies pursued by people within the quantified self-movement are anecdotal and lack the scientific rigor of N-of-1 trials, although this could change if the individuals within the movement were exposed to N-of-1 trial methodologies. Second, there is tremendous interest in improving the sophistication of data collection devices for health monitoring purposes, making them more reliable, cost-efficient, and transparent to the user.…”

An open innovation approach to co-produce scientific knowledge: an examination of citizen science in the healthcare ecosystem

“…An overview of citizenscience projects' attributes from the realist literature review EJIM partners of expert scientists, collaborating with them in the co-design and co-delivery of research endeavours and contributing both in data collection and evidence interpretation (Grant et al, 2019). Lastly, lay people may act as the main driver of research activities, guiding the process of distributed data collection and extracting relevant information from retrieved data (Gimbert and Lapointe, 2015). Different mechanisms enable lay people's engagement in citizen science projects.…”

How to distinguish medicalization from over-medicalization?

“…Accordingly, diverse phenomena have been blamed to be the factors contributing to over-medicalization, some deriving from the biomedical model, such as: extension of official classifications of diseases—ICD-10, DSM-IV (Sedler 2016) and overdemanding health-related norms and standards, quite different depending on the scientific society that has established them,3 or self-tracking practices, that is to say monitoring the state of one’s own body (e.g. blood pressure, pulse, calories burned, blood sugar) using mobile devices and applications (Gimbert and Lapointe 2015), as well as Eastern medicine, based on the holistic idea of internal harmony (Hsu 2013, p. 197), or finally treating medicine as a tool of wish-fulfilling and helping patients improve their functioning or accomplish their life goals (Pellegrino 2004; Maturo 2013).…”