Single Subject (N-of-1) Research Design, Data Processing, and Personal Science

A Conceptual Framework for Personal Science

“…Personal science as a concept was derived from work of noted physical chemist and philosopher of science Michael Polanyi, whose work emphasized the tacit and subjective dimensions of mainstream scientific practice (Polanyi, 1958). Although in its origin the term personal science has wide scope, it has more recently been used to refer to the kinds of self-research described here (Roberts, 2014;de Groot et al, 2017;Heyen, 2017). In a well-informed and sensitive analysis that draws extensively on research conducted in the Quantified Self community, the sociologist Nils Heyen proposed "personal science" as the specific term labeling the practice of exploring one's own personal questions using empirical methods .…”

Digital Twins and the Emerging Science of Self: Implications for Digital Health Experience Design and “Small” Data

“…A variety of authors from diverse disciplines have spoken about the value of N-of-1 research (Guyatt et al, 1986;Lillie et al, 2011;Barnett et al, 2012;Parker and Vannest, 2012;Dallery et al, 2013;Duan et al, 2013;Kravitz and Duan, 2014;Schork, 2015;Strathmann, 2015;Vohra et al, 2015;De Groot and Martin-Sanchez, 2017;Lobo et al, 2017;Mirza et al, 2017). The U.S. Department of Health's Agency for Healthcare Research and Quality has even published its own user guide to N-of-1 trials (AHRQ, 2014), and CONSORT has issued reporting guidelines (Vohra et al, 2015).…”

“…. self-scientists (Parker and Vannest, 2012;Strathmann, 2015;Karkar et al, 2016;De Groot and Martin-Sanchez, 2017;Wicks, 2018).…”

The Quantified Self-in-Place: Opportunities and Challenges for Place-Based N-of-1 Datasets

“…The proliferation of GPS and GIS technologies present particular opportunities to those interested in single-subject or N-of-1 investigations (De Groot et al, 2017). As identified by a recent systematic review of GPS measures in built environment-physical activity studies by Yi and colleagues, individual-level, geolocated datasets might also help address selection bias in place-based research by helping account for potentially influential individual characteristics, and enabling improved experimental or quasiexperimental research designs (Yi et al, 2019).…”