Today’s breakout session preview for the upcoming QS conference comes from Daniel Gartenberg, organizer of the Washington DC QS meetup group. Here is Daniel describing his session “Is QS Science? The Role of QS in Scientific Discovery:”
Do you believe in the power of using Quantified Self to solve some of science’s toughest questions, but have concerns about the validity of QS data? There is actually a long scientific tradition of N=1 studies (i.e. studies conducted with a single participant). Additionally, there are various advantages of N=1 studies, such as repeated, longitudinal, and naturalistic data. These advantages of N=1 studies enable the personalization of treatments because they can take into account individual differences.
Yet N=1 studies are atypical in current scientific research. We will be discussing why the scientific community frowns on N=1 studies, and how we can alleviate some of the scientific community’s concerns regarding QS. This involves understanding what makes something ‘Science.’ Additionally, this will involve identifying threats to validity when conducting studies and QS research. Threats to validity include, but are not limited to: Mortality, History, Maturation, Treatment Fidelity, Treatment Interaction, Compensatory Rivalry, Regression Towards the Mean, and Reactivity.
If done correctly, QS can be a new standard in scientific rigor, but this will require a concerted and collaborative effort by the QS community that will involve developing a system where QSers can post their data to the cloud and have the data aggregated and analyzed across individuals (e.g. curetogether). The potentials and challenges for creating a QS database will be discussed.
Come to this breakout session if you are trying to make sense of your QS data, are interested in the scientific method, are interested in data analysis techniques, or want to create systems and tools that make QS data meaningful to the general population.