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Health Sociology Review
ISSN: 1446-1242 (Print) 1839-3551 (Online) Journal homepage: http://www.tandfonline.com/loi/rhsr20
Self-tracking, health and medicine
To cite this article: Deborah Lupton (2017) Self-tracking, health and medicine, Health Sociology
Review, 26:1, 1-5, DOI: 10.1080/14461242.2016.1228149
To link to this article: http://dx.doi.org/10.1080/14461242.2016.1228149
Published online: 21 Nov 2017.
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Self-tracking, health and medicine
Self-tracking has featured as a central practice in health promotion and healthcare for centu-
ries. People have paid attention to the details of their bodily functions and sensations, their
diet, body weight, drug use and exercise habits, as part of attempting to achieve good health
or manage illness and disease. Over the past few years, a fascination with self-tracking and
its implications for concepts of self, identity, social relations and embodiment has emerged
in sociological and other social research. This interest has partly sprung from increasing cover-
age in the mass media of the potential for new digital technologies to facilitate self-tracking in
novel ways. The possibilities for new mobile media and apps to be used to monitor and
measure human bodies have also been championed in medical publications (Swan, 2012;
The ‘quantified self’to describe digital self-tracking has taken on particular cultural reson-
ance. This term first emerged in 2007, when two Wired magazine editors, Kevin Kelly and
Gary Wolf invented it to describe behaviours that they had observed among colleagues and
friends involving the use of digital technologies such as apps and wearable devices to generate
detailed personal information about their bodies and elements of their everyday lives. They
began organising meetings of people interested in self-tracking and eventually launched a
website: The Quantified Self. The quantified self term soon began to appear in the mass
media, helped by articles and blog posts penned by Wolf and Kelly for Wired and other influ-
ential media like The New York Times. It began to supplant the older ‘lifelogging’, which had
attracted research interest since the emergence of personal computing, particularly among
human–computer interaction (HCI) researchers (Lupton, 2013).
In response to these developments, a body of literature from social researchers has rapidly
developed, with at least two books (Lupton, 2016a; Neff & Nafus, 2016) and two edited book
collections (Nafus, 2016; Selke, 2016) appearing in 2016. Numerous articles and book chapters
about self-tracking have been published since 2012 (for reading lists, see Lupton, 2016b,
2016c). Self-tracking is not always about health and medical issues, but these are key elements.
People who engage in reflexive self-monitoring collect information about themselves, and
reflect on how this information can be used to improve their lives in some way. These data
are often about their bodies and health states: their medical symptoms and medical treatments,
sleeping, eating, alcohol and drug use and exercising habits, body weight, blood glucose levels,
pulse, moods and stress levels and reproductive and sexual functioning and activities.
While many people engage in self-tracking using non-digital forms of recording their
details, such as pen-and-paper or even just relying on their memories (Fox & Duggan,
2013), a vast array of digital technologies have come onto the market that can be used for
highly detailed and often automated self-monitoring. There are now over 160,000 health
and medical apps on the market, and apps for counting calories, fitness tracking and menstrual
cycle tracking are among the most popular in terms of downloads (IMS Institute for Health-
care Informatics, 2015). Wearable devices such as Fitbit, Jawbone Up and Misfit, as well as
smartwatches like Apple Watch, have been designed to feature self-tracking sensors and soft-
ware that can monitor and measure health and bodily movements. Patients with chronic
© 2016 Informa UK Limited, trading as Taylor & Francis Group
HEALTH SOCIOLOGY REVIEW, 2017
VOL. 26, NO. 1, 1–5
diseases like diabetes, mental health conditions and high blood pressure can use mobile self-
monitoring devices and apps to engage in self-care. Patient support platforms such as Patient-
sLikeMe encourage people to monitor their symptoms and treatments and share these data
with others. Exergaming devices like Wii Fit and Kinect Xbox include digital sensors that
can monitor and record players’physical activities. Some game apps not obviously directed
at self-tracking, such as Pokemon Go, now often include a physical activity monitor as part
of the gamification of preventive health.
A particularly intriguing feature of contemporary digitised self-tracking is ‘function creep’,
or the spread of the mentalities, motivations and technologies for self-tracking beyond the per-
sonal, domestic or medical sphere into other social domains. I have identified five modes of
self-tracking: private, pushed, communal, imposed and exploited (Lupton, 2016a). Many
people choose to engage in reflexive self-monitoring voluntarily for their own reasons
(‘private self-tracking’): because they have decided that they want to lose weight, improve
their sleep, get fitter and stronger, feel better, have more energy, feel happier, control their
stress levels or be a more productive worker. Self-trackers often find value and comfort in
sharing their personal data with other people on social media or specialised physical activity
tracking platforms and apps like Strava and providing support to others engaged in similar
pursuits (‘communal self-tracking’). However, in some instances people are pushed into
self-tracking by others. Children may be required to participate in heart-rate monitoring or
behaviour monitoring at school using apps or software. Patients with chronic health con-
ditions are sent home by their doctors with the expectation that they will engage in the pre-
scribed self-monitoring program. Employers expect their employees to sign up to workplace
‘wellness’programs requiring health and fitness self-tracking. Health and life insurers are
beginning to invite clients to upload their medical and exercise data to receive rewards or
lower premiums. In other cases, self-tracking is imposed on people: for example, as part of
alcohol and other drug monitoring programs. They may have little option but to comply.
The data generated from many of these activities are exploited by many different actors and
agencies for commercial, managerial, governmental or research purposes.
This special issue of Health Sociology Review was designed to highlight recent sociological
research and theorising about self-tracking in health and medicine. The seven articles pub-
lished here cover a range of self-tracking techniques, contexts and geographical locations:
fitness tracking using the wearable Fitbit device in the UK (Fotopolou and O’Riordan),
English adolescent girls’use of health and fitness apps (Depper and Howe), stress and recovery
monitoring software and devices in a group of healthy Finns (Pantzar, Ruckenstein and Mus-
tonen), self-monitoring by young Australian illicit drug users (Pereira and Scott), an Italian
diabetes self-care program using an app and web-based software (Piras and Miele) and
‘show-and-tell’videos uploaded to the Quantified Self website about people’s experiences of
self-tracking (Smith and Vonthethoff). Rich and Miah’s article takes the form of a review.
Focusing on lifestyle apps, they draw attention to the key theoretical perspectives and issues
that can be employed to critically analyse these self-tracking artefacts.
The research methods used in the articles are nearly all qualitative. In their studies, Pereira
and Scott and Piras and Miele used the classic qualitative method of one-to-one interviews,
while Depper and Howe adopted the focus group discussion approach. Smith and Vonthethoff
undertook a critical discourse analysis of self-tracking videos and included interviews with two
self-trackers to supplement their findings. The authors of two articles experimented with some
alternative approaches. Fotopolou and O’Riordan employed a combination of autoethnogra-
phy, interface analysis of the Fitbit app, device screen and website and qualitative media analy-
sis of news and blogs about Fitbit. Pantzar and colleagues used a combination of analysing the
quantitative stress data derived from a self-tracking device plus participants’diary entries and
Major themes running across the collection include the emphasis on self-responsibility and
self-management on which self-tracking rationales and devices tend to rely, the biopedagogical
function of self-tracking (teaching people about how to be both healthy and productive bioci-
tizens) and the reproduction of social norms and moral meanings concerning health states and
embodiment (good health can be achieved through self-tracking, while illness can be avoided
or better managed). Analysing the ways in which people’s bodies and health states are datafied,
or rendered into digital data assemblages, and subject to dataveillance, or forms of watching
using these data, is addressed in most of the articles.
The authors take up series of theoretical perspectives to analyse the broader implications of
health and medical self-tracking. Foucauldian theories of biopower and ethical self-formation
are employed in five of the seven articles (Pereira and Scott, Depper and Howe, Fotopolou and
O’Riordan, Rich and Miah, Smith and Vonthethoff). Interestingly, Pereira and Scott identify
the dominance of moral judgements about the importance of self-management expressed in
the young illicit drug users they interviewed. According to these interviewees, ‘good’drug-
using citizens must make sure that they carefully monitor their drug-taking behaviours to
ascribe to guidelines about safe use. Smith and Vonthethoff also take up the work of Beck,
Giddens and Lash and their theory of reflexive modernisation to explain the ways in which
self-tracking practices are used as part of the project of self-optimisation. They further refer
to Bauman’s concept of liquid modernity to explain self-tracking as a never-fulfilled quest
for self-knowledge and happiness. The satisfactions and comforts of self-tracking, they
contend, are ephemeral, because the flows of data generated must constantly be managed
Sociomaterial perspectives are adopted in the articles by Pantzar, Ruckenstein and Musto-
nen and Piras and Miele. Pantzar and colleagues are interested in the intersections between
digital self-tracking devices and human actors. They also refer to the work of Lefebvre in focus-
ing attention on the rhythms of life and how these are interembodied. Piras and Miele point to
the shared nature of self-tracking as a joint endeavour between patients and doctors where
there are often frictions between the different parties’expectations and assumptions of how
it should be undertaken. Some of the diabetes patients in Piras and Miele’s study sought to
challenge or resist the self-tracking practices enjoined upon them by their doctors. They
used the self-tracking technology to achieve greater autonomy from surveillance and interven-
tion by doctors. Piras and Miele demonstrate that when doctors attempted to push self-track-
ing onto patients, patients actively chose how they engage in clinical self-tracking in ways not
always expected (or wanted) by their doctors.
Contributions to the existing literature on self-tracking in health and medicine, including
the articles in this special issue, have begun to cast light on its sociocultural and political
dimensions, including the complex interactions and entanglements between human and non-
human actors and between biology and culture. There are many directions that future socio-
logical research can take. Most research thus far, including the articles published in this special
issue, has focused on the members of privileged social groups located in the Global North who
are tracking their health indicators because they are already conforming to the ideals of the
responsibilised, self-managing and entrepreneurial citizen. We know little as yet about how
the members of marginalised or stigmatised groups engage in self-tracking, resist it or even
re-invent it. How are elderly people, people from minority ethnic or racial groups, people
with poor literacy skills or people with disabilities engaging (or not) in self-tracking? How
are people living outside the Global North using these technologies?
HEALTH SOCIOLOGY REVIEW 3
On the one hand, self-tracking can promote health and wellbeing. On the other hand, it can
further contribute to socioeconomic disadvantage and marginalisation. People who do not
take up suggestions to self-track their health and fitness by their employers or insurers, for
example, may suffer adverse consequences such as being considered as an inadequate
employee or paying higher premiums. Research on these populations is ever-more important
as people are encouraged or coerced to engage in self-tracking in an increasing number of
social domains, and as the personal data generated by self-tracking practices are used in
decision-making about funding and service-delivery and thus shape people’s life chances.
Personal health and medical data have acquired considerable biovalue in the digital data
economy (Lupton, 2016a). They are commonly used for commercial purposes: for instance,
developers on-sell them to advertising, medical device and pharmaceutical companies. Data
mining companies harvest these data, combining them to create profiles and lists of people
identified as having specific medical conditions, and profit from selling these lists to advertis-
ing agencies, financial institutions and potential employers (Ebeling, 2016; Pasquale, 2014).
Repositories of data about people’s sexual activities and preferences, body weight or health
conditions can be used to target them for social shaming, exclusion or denial of insurance,
credit or employment opportunities (Lupton, 2016a). Sociologists and other social researchers
need to identify and draw attention to these uses of personal health and medical data.
Data privacy and security issues also constitute a paramount topic of investigation. The
types of personal information about people’s bodies that are collected by self-tracking practices
can be highly sensitive and revealing of aspects that people may not wish others to know about.
Personal data have a ‘capacity for betrayal’–they can be ‘disloyal’(Nafus, 2014). Medical and
health database breaches, including of the data repositories of major hospitals and public
health agencies (Gajanayake, Lane, Iannella, & Sahama, 2013; Thilakanathan, Chen, Nepal,
Calvo, & Alem, 2014) and health tracking apps (Wicks & Chiauzzi, 2015) frequently occur.
Health and medical data are key targets of cybercriminals and hackers, who use the data for
fraudulent activities (Ablon, Libicki, & Golay, 2015). Sociologists and other social researchers
should continue to investigate these uses of personal health and medical data, both legal and
illicit, and highlight the consequences.
The ways in which people incorporate and conceptualise the personal health and medical
data they generate from self-tracking as part of their everyday lives and notions of identity and
embodiment also require more sustained research. This could include investigations into how
people make choices about which kind of information to collect and what practices and devices
they use to do so. We have yet to fully understand how people engage with the personal data
produced from self-tracking. These data are lively, constantly moving and changing as they are
generated and contribute to new forms of data assemblages (Lupton, 2016a). I use the term
‘data sense’to encapsulate the complexity of the entanglements between human senses,
digital sensors and sense-making in response to these lively data (Lupton, 2016d). How do
these data become meaningful –how do they lose meaning? How do people negotiate what
their self-tracking devices tell them about their bodies and health, and what their bodily
senses reveal to them? What are the sensory and affective dimensions of data sense? In
what ways do personal data provide comfort or reassurance –and how do they frustrate or
disappoint people? Related to these questions are those concerning data materialisations, or
the ways in which digital data are rendered into formats so that people can view them (or
in the case of 3D printed objects, even handle them (Lupton, 2015)).
Finally, the ways in which self-tracking technologies and practices are invented, brought
onto the market, advocated and incorporated into organisations and institutions also
require more attention. What are the decision-making processes by which developers
choose to work on self-tracking apps, other software and devices, and what are the tacit
assumptions, expectations and norms about bodies and selves underpinning these processes?
How are schools and higher education institutions, workplaces, hospitals and other healthcare
providers and insurance companies promoting or requiring health and medical self-tracking?
What are the intersections between the entrepreneurs and developers working on self-tracking
technologies and these institutions and organisations?
The sociology of self-tracking is in its nascent stages. As self-tracking expands further into
the domains of social life, and as more people voluntarily take up quantifying themselves or are
pushed or coerced to do so, all of these questions, and many more, remain to be answered.
Ablon, L., Libicki, M., & Golay, A. (2015). Markets for cybercrime tools and stolen data. Santa Monica, CA:
Ebeling, M. (2016). Healthcare and big data: Digital specters and phantom objects. Houndmills: Palgrave
Fox, S., & Duggan, M. (2013). Tracking for health. Retrieved from http://www.pewinternet.org/files/old-media//
Gajanayake, R., Lane, B., Iannella, R., & Sahama, T. (2013). Accountable-ehealth systems: The next step forward
for privacy. Electronic Journal of Health Informatics,8(2), 11. Retrieved from http://www.ejhi.net/ojs/index.
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barriers to mainstream acceptance. Parsipanny, NJ: IMS Institute for Healthcare Informatics.
Lupton, D. (2013). Understanding the human machine. IEEE Technology & Society Magazine,32(4), 25–30.
Lupton, D. (2015). Fabricated data bodies: Reflections on 3D printed digital body objects in medical and health
domains. Social Theory & Health,13(2), 99–115.
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Lupton, D. (2016b). Critical research on self-tracking: A reading list. This Sociological Life. Retrieved from
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Lupton, D. (2016d). Living digital data research program. This Sociological Life. Retrieved from https://
Nafus, D. (2014). Stuck data, dead data, and disloyal data: The stops and starts in making numbers into social
practices. Distinktion: Scandinavian Journal of Social Theory,15(2), 208–222.
Nafus, D. (Ed.). (2016). Quantified: Biosensing technologies in everyday life. Cambridge, MA: MIT Press.
Neff, G., & Nafus, D. (2016). Self-tracking. Cambridge, MA: MIT Press.
Pasquale, F. (2014). The dark market for personal data. The New York Times. Retrieved from http://www.
Selke, S. (Ed.). (2016). Lifelogging: Digital self-tracking and lifelogging –between disruptive technology and cul-
tural transformation. Wiesbaden: Springer VS.
Swan, M. (2012). Health 2050: The realization of personalized medicine through crowdsourcing, the quantified
self, and the participatory biocitizen. Journal of Personalized Medicine,2(3), 93–118.
Thilakanathan, D., Chen, S., Nepal, S., Calvo, R., & Alem, L. (2014). A platform for secure monitoring and
sharing of generic health data in the cloud. Future Generation Computer Systems,35, 102–113.
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News and Media Research Centre, Faculty of Arts and Design, University of Canberra, Australia
HEALTH SOCIOLOGY REVIEW 5