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Quantifying the Body: Monitoring and Measuring Health in the Age of mHealth Technologies

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Abstract

Mobile and wearable digital devices and related Web 2.0 apps and social media tools offer new ways of monitoring, measuring and representing the human body. They are capable of producing detailed biometric data that may be collected by individuals and then shared with others. Health promoters, like many medical and public health professionals, have been eager to seize the opportunities they perceive for using what have been dubbed ‘mHealth’ (‘mobile health’) technologies to promote the public’s health. These technologies are also increasingly used by lay people outside the professional sphere of health promotion as part of voluntary self-tracking strategies (referred to by some as ‘the quantified self’). In response to the overwhelmingly positive approach evident in the health promotion and self-tracking literature, this article adopts a critical sociological perspective to identify some of the social and cultural meanings of self-tracking practices via digital devices. Following an overview of the technologies currently available for such purposes I move on to discuss how they may contribute to concepts of health, embodiment and identity. The discussion focuses particularly on how these technologies promote techno-utopian, enhancement and healthist discourses and the privileging of the visual and the metric in representing the body via these devices.
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QUANTIFYING THE BODY: MONITORING, PERFORMING AND MEASURING
HEALTH IN THE AGE OF mHEALTH TECHNOLOGIES
Deborah Lupton
This is the final version of an article that has been accepted for publication in Critical Public
Health.
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QUANTIFYING THE BODY: MONITORING AND MEASURING HEALTH IN THE
AGE OF mHEALTH TECHNOLOGIES
Abstract
Mobile and wearable digital devices and related Web 2.0 apps and social media tools offer
new ways of monitoring, measuring and representing the human body. They are capable of
producing detailed biometric data that may be collected by individuals and then shared with
others. Health promoters, like many medical and public health professionals, have been eager
to seize the opportunities they perceive for using what have been dubbed ‘mHealth’ (‘mobile
health’) technologies to promote the public’s health. These technologies are also increasingly
used by lay people outside the professional sphere of health promotion as part of voluntary
self-tracking strategies (referred to by some as ‘the quantified self’). In response to the
overwhelmingly positive approach evident in the health promotion and self-tracking
literature, this article adopts a critical sociological perspective to identify some of the social
and cultural meanings of self-tracking practices via digital devices. Following an overview of
the technologies currently available for such purposes I move on to discuss how they may
contribute to concepts of health, embodiment and identity. The discussion focuses
particularly on how these technologies promote techno-utopian, enhancement and healthist
discourses and the privileging of the visual and the metric in representing the body via these
devices.
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Introduction
Over a period of only five years, mobile digital devices connected to the web such as
smartphones, tablet computers, iPods and wearable patches and bands have emerged onto the
market and become widely adopted. Mobile digital devices, which are now very small and
portable, can be taken almost anywhere and are able to connect remotely to the internet from
most locations. Frequent statements are now made in the popular media and in the medical
and public health literature about an imminent revolution in health care, preventive medicine
and public health driven by the use of such devices and their related apps and tools, otherwise
referred to as ‘mHealth’ technologies. Many articles have recently appeared in the health
promotional and preventive medicine literature ruminating on the possibilities of being able
to communicate with the public, monitor their behaviours and conduct health promotion
interventions via the mobile devices that they carry with them or wear throughout their day
(Donner, 2012, Kratzke and Cox, 2012, Chib, 2013, Kaplan and Stone, 2013).
One specific aspect of mHealth that has received attention of late is that of using mobile and
wearable digital devices to collect data on one’s bodily functions and everyday activities
(Kirwan et al., 2010, Cummiskey, 2011, Swan, 2012). Individuals’ bodily movements and
geographical location can be identified and recorded remotely using the GPS systems and
accelerometers that are embedded within these technologies. Such body functions and
indicators as blood glucose, body temperature, breathing rate, blood chemistry readings, body
weight, blood pressure, heart rate, sleep patterns, cardiac output readings and even brain
activity can all be monitored using portable wearable and internal sensors, woven into
clothing or laminated onto ultrathin skin interfaces and placed anywhere on the body. Ski
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goggles, headbands, wristbands, adhesive patches, sports shoes, bathroom weight scales,
pyjamas, fitness clothing and even toothbrushes with tiny digital sensors implanted in them
are now available for purchase as part of the project of producing biometric data. Several
wearable devices can be worn on the body throughout the day and night to provide continual
monitoring (for examples, see Ramirez, 2013).
Many thousands of health-related apps for mobile digital devices have been developed for
commercial use. The Apple App Store alone offers over 13,000 health-related apps
(Strickland, 2012). It has been estimated that in 2012 44 million of these were downloaded
worldwide (Raskin, 2012). These apps provide a range of medical and health information,
from assisting users in self-diagnosing illness, displaying detailed anatomical information
about the human body and allowing users to monitor, log and graph such bodily functions as
exercise habits, diet and drug consumption, mental health and moods, menstrual cycles and
ovulation patterns, sleep patterns and hearing function and to record the incidence and
severity of pain. To motivate users, some apps include built-in reward or docking systems so
that points, badges or real money can be collected or paid if various commitments (to regular
exercise or weight loss goals, for example) are either met or unmet. Data collected from
many of these apps can be uploaded to related websites or to social media platforms such as
Facebook or Twitter, and thus can be shared with many others.
Wearable or mobile devices designed for such monitoring activities include those developed
by the iHealth company (iHealth, 2013). It offers technologies that include digitalised scales
for measuring body weight and bone density, blood pressure and heart rate monitors and
glucose measuring devices that wirelessly connect with apps on iPhones, iPods and iPads to
allow for measurement and monitoring of these body functions. The software incorporated
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with these devices provides a means for the user to keep a record of their measurements and
to easily observe any variation over time. The data collected can be emailed to one’s medical
professional or uploaded to social media platforms to share with family members and friends.
Other wearable digital self-tracking technologies on the market include the Nike+ Fuelband,
a wristband physical activity and calorie expenditure monitor, the Fitbit One, a small device
that can be clipped onto clothing, placed into a wristband during sleep or carried in a pocket,
which tracks physical activity, weight, calories used, water consumption, diet and sleep
patterns, the Zeo Personal Sleep Coach, a digitised headband to monitor sleep and the
Larklife wristband, which collects data on the user’s physical activity, sleep and diet and
incorporates reminders to users to move more, advice about how to improve their workout as
well as suggestions for improving work productivity (Ramirez, 2013).
The terms ‘self-tracking’ and ‘the quantified self’ are now often employed to describe the use
of these technologies (Smarr, 2012, Swan, 2012). There is a growing movement in self-
tracking as part of managing and improving one’s life (Lupton, 2013). The activities of
voluntary self-trackers in many ways coincide with the objectives of health promotion. While
other aspects of one’s everyday life (for example work outputs or social encounters) are often
recorded as part of producing the quantified self, bodily functions represent a major target of
self-tracking activities. Indeed medical and public health professionals have begun to show
awareness of the self-tracking movement and to advocate for building upon it in their work
(Swan, 2012, Wiederhold, 2012). According to Wiederhold, for example, ‘we are on the
leading edge of another revolution in health care, brought to you by the patient herself as she
uses her phone for self-tracking’ (2012, p. 235).
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Although thus far there are little published data in the academic literature on how and why
people are using self-tracking digital devices for health, research conducted by US-based Pew
Research Center (Fox and Duggan, 2013) found that 21 per cent of the US adults surveyed
reported monitoring a health indicator such as body weight, diet, exercise patterns, bodily
functions such as blood pressure or a medical symptom, either for themselves or a family
member, using a technological device such as a medical device (8 per cent), app or other tool
on their mobile device (7 per cent), computerised spread sheet (5 per cent) and website or
online tool (1 per cent). The survey further found that one in five respondents had
downloaded a health app to their digital device specifically to track or manage their health.
Exercise, body weight and diet apps were the most commonly downloaded apps.
A critical perspective on mHealth technologies
The use of mobile and wearable mHealth technologies affords the temporal, spatial and
interpersonal nature of health surveillance. Health-related data may easily and frequently be
collected from users’ mobile devices each time they log on to the relevant app. Such devices
thus offer an unprecedented opportunity to monitor and measure individuals’ health-related
habits on the part not only of the users themselves but also by health care and public health
workers. What are the social and cultural implications for how we might think about health
promotion practice and those individuals who are the target of mHealth campaigns or who are
voluntarily self-tracking their biometric data?
In a previously published article (Lupton, 2012) I noted that while there is a growing
literature on mHealth in the medical and public health literature very few critical analyses
have yet appeared. In that discussion I addressed such issues as how the concept of the
cyborg (the human-machine hybrid) is relevant to theorising mHealth and how mobile digital
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technologies may be used not only as body prostheses but also as interpreters of the body. I
also drew upon surveillance studies to argue that digital health technologies act to configure
and reconfigure surveillant assemblages (a term first introduced by Haggerty and Ericson,
2000), or bodies/subjects that are configured by and through surveillance technologies, and
that many individuals engage in voluntary self-surveillance as part of using mHealth
technologies. This previous article also discussed some privacy, intimacy and ethical issues
around the use of these technologies.
As part of my continuing sociological study of the mHealth phenomenon, in what follows I
focus more specifically on the practice of monitoring biometric data using mobile digital
devices. I suggest a number of theoretical approaches (by no means exhaustive) that may be
adopted to theorise this practice. These include exploring concepts of technological bodily
enhancement and techno-utopian visions of the perfect(ible) body, healthism and personal
responsibility, visualisation and bodily display and the allure and power of metrics inherent in
the use of these devices.
My overarching theoretical perspective when analysing the mHealth phenomenon
conceptualises digital health technologies (like any other technologies) as actors (or in the
argot of science and technology studies ‘actants’) in a network of heterogeneous discourses,
bodies, practices, ideas and technologies. From this perspective technologies bestow meaning
and subjectivity upon their users, just as users shape the technologies and give them meaning
as they incorporate them into their everyday practices. Technologies assume certain kinds of
capacities, desires and embodiments; they also construct and configure them. Further,
technologies are never politically neutral, but rather are always implicated in complex power
relationships (Hadders, 2009, Mort et al., 2009, Mort and Smith, 2009, Rich and Miah, 2009,
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Casper and Morrison, 2010, Mansell, 2010). Changes in technologies addressed at
monitoring and regulating bodies and health states represent transformations in how bodies
are conceptualised, touched, managed and visually displayed, not only from the perspective
of professionals operating in the medical or public health field, but also for those who are
their subject.
Techno-utopia and the perfect(ible) body
Some writers have compared the use of technological devices implanted upon or used with
the body as part of the general desire to engage in ‘body projects’, practices of embodiment
that serve to assist people in defining their identities (Shilling, 1993, Featherstone, 1999,
Hogle, 2005, Pitts, 2005). Some of these practices are undertaken in the name of ‘good
health’; others are used to adhere to standards of physical beauty; yet others are a way of
demonstrating resistance of taken-for-granted norms of embodiment or to take control over
disempowering bodily experiences such as severe illness or surgery. Hogle (2005) uses the
term ‘enhancement technologies’ to refer to such technologies as cosmetic surgery,
pharmaceuticals such as Viagra, hormonal supplement, neurochemicals designed to improve
cognitive functioning and computerised prosthetics. The point of such technologies is to
‘correct’ apparent ‘deficits’ in body functioning or appearance.
Mobile digital devices could similarly be viewed as enhancement technologies when they are
used for health-related purposes. They extend the capacities of the body by supplying data
that can then be used to display the body’s limits and capabilities and allow users to employ
these data to work upon themselves and present themselves in certain ways. Writing before
the advent of mobile digital devices, Chrysanthou (2002) noted the move towards individuals
using information and computer technologies such as online health assessments, over-the-
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counter diagnostic tests and self-administered genetic tests, as part of what he describes as a
utopian vision of the perfect, imperishable body. These technologies participate in a kind of
‘techno-utopia’, in which technologies are positioned as harbingers of progress, keys to the
promotion of human happiness, wellbeing and health (Davis, 2012).
Techno-utopian discourses were particularly evident in discussions of the freedoms and
liberation from the confines of the body apparently offered by writers on cyberspace and the
posthuman body in the 1990s (Lupton, 1995a, Bell, 2001). Yet the kind of techno-utopian
discourses evident in discussions of biometric self-tracking do not suggest leaving the body
behind. To the contrary, they direct the gaze directly at the body. They privilege an intense
focus on and highly detailed knowledge of the body in which it is suggested that possession
of this knowledge of one’s body offers a means by which illness and disease may be
prevented.
The self-knowledge that is viewed as emerging from the minutiae of data recording a myriad
of aspects of the body is a psychological salve to the fear of bodily degeneration. The
‘Massive Health’ website (Massive Health, 2012), for example, notes that ‘Your body is the
ultimate interface problem. Sometimes, it just doesn’t give you the feedback you need … We
create the tight feedback loops your body is missing to keep you healthy’. This company
offers such apps as ‘The Eatery’, which allows users to photograph their meals. The app then
calculates not only the nutritional values of the food but provides what is described as ‘deep
insights’ into eating habits, such as whether the user eats more nutritious food in the morning
or evening and where their ‘weak points’ lie. According to the website: ‘Other apps tell you
about your food. We’re telling you about yourself.’
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Healthism and personal responsibility
Accounts of self-tracking technologies for health, in both the health promotional and the lay
self-tracking literatures, tend to place emphasis on the potential for the ‘empowerment’ of lay
people offered by these technologies and the importance of ‘taking responsibility’ for one’s
health. In their privileging of good health as the reason for using such devices, they are
engaging in and promoting the discourse of ‘healthism’.
Sociologists writing on healthism have identified the intense focus on health and the
prevention of illness that has emerged since the 1970s. Healthism positions the achievement
and maintenance of good health above many other aspects of life and features of one’s
identity, so that an individual’s everyday activities and thoughts are continually directed
towards this goal. A dominant belief underlying healthism is that fate can be controlled, at
least to some extent, by personal action and the taking of responsibility for one’s health
(Crawford, 1980, Crawford, 2006). Healthism tends to be a discourse embraced by the
socioeconomically privileged, who are able to position ‘health’ as a priority in their lives and
have the economic and educational resources to do so. This discourse therefore tends to gloss
over the social and economic determinants of health states for a focus on ‘empowerment’ and
‘taking charge’ of one’s own health. Healthist discourses therefore value those who take such
responsibility and represent them as ideal citizens, while people who are viewed as lacking
self-responsibility or who are ill are positioned as inferior and morally deficient (Lupton,
1995b, Crawford, 2006, Buse, 2010).
Medical advice and health promotion campaigns are predicated on and reproduce the values
of healthism (Lupton, 1995b, Petersen and Lupton, 1996). The advent of Web 2.0
technologies and mobile digital devices has allowed healthism to be promoted and
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promulgated in more detail and more intensely than ever before. While self-tracking is
directed at other aspects of life and not only health-related metrics, the idea that collecting
data on oneself is a primary means by which good health can be established and maintained is
dominant in discourses of self-tracking and the quantified self. Indeed self-tracking represents
the apotheosis of self-reflexivity in its intense focus on the self and using data about the self
to make choices about future behaviours. In relation to health matters, self-tracking offers
users of such technologies a strategy by which they feel as if they can gather data upon their
health indicators as a means of avoiding illness and disease.
The discourse of healthism in the mHealth literature configures users as ideal-type
responsible citizens who possess the economic and motivational capacity to engage in self-
surveillance via these technologies. As one advocate of self-tracking in preventive medicine
put it, using these technologies represents a paradigm shift from ‘My health is the
responsibility of my physician’ to ‘My health is my responsibility, and I have the tools to
manage it’ (Swan, 2012, p. 108). These individuals have readily adopted the subject of the
responsible, entrepreneurial citizen as it is privileged in neoliberal governmentality in seeking
to take action to achieve healthy and fit embodiment and engaging in self-governance
(Lupton, 1995b, Petersen and Lupton, 1996). Questions about the oft-cited problem of the
‘digital divide’, or the lack of access of many people to digital technologies because of their
socioeconomic status, geographical location, disability, lack of skills or sheer unwillingness
to learn about new digital technologies (Blanchard et al., 2008, Frederico et al., 2012) are
ignored in these discourses.
Visualisation technologies and bodily display
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The use of digital mobile technologies to record, measure and monitor bodily functions as
part of health promotion and voluntary self-tracking is a logical extension of the employment
of visualising technologies in medicine. Technologies for screening and diagnostic purposes
such as x-rays, computer tomography, ultrasound and magnetic resonance imaging have been
used for some decades to monitor, record and interpret the body, to gaze into and produce
images of its interior. In recent times digital technologies have become increasingly
important to the visualisation and display of the human body in medicine. Indeed it has been
argued that these technologies are participating in an important historical transformation of
bodies at which a key site is medicine (Duden, 1993, Waldby, 1997).
Part of this increasing use of visualising technologies is a significant shift in how the body
and health states are conceptualised, articulated and portrayed. Where once people relied
upon the haptic sensations they felt in their bodies and reported to their physicians, medical
technologies devoted to producing images of the body have altered the experience and
treatment of bodies. The optic has come to take pre-eminence over the haptic in revealing the
‘truth’ of the body (Duden, 1993). Such technologies produce a virtual patient, a ‘screen
body’. The visual image or data they generate are often privileged as more ‘objective’ than
the signs offered by the ‘real’, fleshly body and patients’ own accounts of their bodies
(Chrysanthou, 2002, Blaxter, 2009).
Like these medical imaging technologies, mobile digital technologies that measure bodily
movement and body functioning, and report these data to the device user and those with
whom they choose to share these data, produce a spectacular body, one in which the internal
workings are similarly displayed and made visible. As part of the project of seeking security
and stability, of ‘taming uncertainty’ (Lupton, 1995b) the ‘transparent body’ is created using
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such technologies in the effort to penetrate the dark interior of the body, render it visible,
knowable and thereby (it is assumed) manageable. By generating biometric data, these
devices are producing ‘bodies that are simultaneously hyper text and flesh’ (Rich and Miah,
2009, p. 172, emphasis in the original).
Because they constantly collect data on bodies that are constantly moving and engaging in a
wide variety of activities, the ‘digital archive’ (Waldby, 1997) of the body these technologies
are able to construct is subject to constant change and revision. When users employ devices
which allow them to measure their bodily functioning, movement and consumption habits
and then to display the collected data via social media platforms, they are, in effect, sharing
personal body displays, using them for their own purposes of ‘performing health’.
Sometimes this display of one’s biometric data may take an overtly competitive form, as in
websites such as strava.com, where people can upload data from digital devices which have
GPS and heart monitor functions from a run, hike or cycle which show how many kilometres
they have covered and at what speeds, power and heart-rates, and then compare these data
with others engaging in similar activities on the same route. Exercisers can also strive for
their personal best by comparing data from previous outings with their latest and again
broadcast the resultant data to their social networks. These functions, therefore, are able to
contribute to the configuration of identity and the presentation of the self online that have
been identified as important elements in analyses of social media platforms such as Facebook
(Zhao et al., 2008, Ellis, 2010, Davis, 2012).
The allure and power of metrics
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Self-tracking mHealth devices not only configure the body and health states into visual
displays, they are also based on quantification, often using complex algorithms to process and
display the data collected. The visual data on the body produced by mobile digital devices
the ‘numbers’ that allow users to compare their biometrics with those generated on previous
days or against others’ data – contribute to a new way of conceptualising one’s body and
one’s health status. These ‘numbers’ has been vitally important in promoting the cause of the
self-tracking movement. Indeed for some the achievement of ‘self knowledge through
numbers’ as the official Quantified Self movement website (Quantified Self, 2013) has it, is
the primary objective of self-tracking.
As recent sociological analyses into questions of measure and value have argued, there has
been a huge increase generally in the use of metrics in many aspects of social life, which has
been greatly impelled by the development of technologies for achieving, interpreting and
displaying quantification. Yet there is a politics of measurement: numbers are not neutral,
despite the accepted concept of them as devoid of value judgements, assumptions and
meanings. The ways in which phenomena are quantified and interpreted and the purposes to
which these measurements are put are always implicated in social relationships, power
dynamics and ways of seeing (Savage and Burrows, 2007, Adkins and Lury, 2011, Ruppert,
2012).
Using self-tracking technologies encourages people to think about their bodies and their
selves through numbers. The implication of the ‘self knowledge through numbers’ motto is
that ‘self-knowledge’ as it accomplished via self-tracking and the production of ‘numbers’ is
a worthy goal for individuals to aspire to. The more we know about ourselves and our bodies,
the more productive, wealthier, wiser, healthier, emotionally-stable and so on we can be. It is
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assumed that the production of such hard/objective data is the best way of assessing and
representing the value of one’s life and that better ‘self-knowledge’ will result.
The lure of the ‘numbers’ produced from self-tracking is that they appear scientifically
neutral. The body/self as it is produced through self-tracking, therefore, is both subject and
product of ‘scientific’ measurement and interpretation. Such a transformation extends further
the move from the haptic to the optic in the configuring of the body/self. As one’s bodily
states and functions become ever more recordable and visualised via data displays, it
becomes easier to trust the ‘numbers’ over physical sensations.
Concluding comments
In this article I have raised some possibilities for thinking about mHealth technologies as they
are used or promoted for monitoring and displaying health states and bodily functions. There
is much yet to explore concerning the incorporation of these technologies into everyday life.
Like any other material object, mobile digital devices have their own social lives and
histories (Appadurai, 1988) as they are taken up and used as part of embodied practices.
Some cultural theorists use the term ‘domesticate’ to describe the ways in which technologies
are incorporated into everyday use and how they are transformed or ‘tamed’ to fit into
routines. Technologies may retain some of their unpredictable ‘wildness’, however, as
technologies are not simply configured by their users but in turn shape their users in various
ways by creating new ways of thinking, feeling and being (Pols and Willems, 2011). This is a
dimension of mobile digital devices that is not always recognised or acknowledged.
Given that mobile digital technologies are so novel, research directed at how people actually
use them for health purposes how they ‘domesticate’ them and incorporate them into their
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everyday lives -- has yet to be published. What types of people self-track? How do the
devices they use come to acquire meaning in the context of everyday use? What are the social
lives of these commodities? Aspects of how and to what extent these devices are incorporated
in concepts of selfhood and embodiment also remain to be fully explored.
Related to these questions are those concerning how concepts of ‘health’ are configured and
understood via these technologies and what types of resistance users may offer to
incorporating them into their everyday worlds? Given the simulated nature of the ‘data
doubles’ (Haggerty and Ericson, 2000) produced via digital technologies, ‘health’ at least
partly potentially becomes a simulacrum. If the statistics recorded by one’s digital device
show that one’s BMI is ‘normal’, that one is not imbibing too much alcohol, engaging in
enough exercise, has a normal resting pulse or blood pressure, these data comprise a
simulated ‘healthy body’, regardless of how well an individual may actually feel. Such
questions as how users respond to the data produced by self-tracking on a day-to-day basis,
how they react to others’ responses when these data are shared and what credence users
ascribe to the data derived from these devices compared with other sources of bodily
experience and information deserve indepth research and analysis.
Freund (2004, p. 273) uses the term ‘technological habitus’ to describe the ‘internalised
control’ and kinds of consciousness required of individuals to function in technological
environments such as those currently offered in contemporary western societies. The
human/machine entity, he argues, is not seamless: rather there are disjunctions or, as he
puts it, ‘seams in the cyborg’ -- where fleshly body and machine do not intermesh smoothly,
and discomfort, stress or disempowerment may result. Sleep patterns, increasing work and
commuting time and a decrease in leisure time, for example, can be disrupted by the use of
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technologies, causing illness, stress and fatigue. People may feel overwhelmed by the sheer
mass of data conveyed by their digital devices and the need to keep up with social network
updates. They may begin to resent the imperative to self-track their body’s functions and
performances, even if the decision to do so was their own rather than urged upon them by a
medical or public health professional. There is also the possibility that the intense focus on
one’s body produced through self-tracking -- making the body ever more ‘visible’, rendering
it open to ever-more detailed monitoring -- may eventuate not only in greater certainty, but
also create greater anxiety.
The capacity of the mobile digital device to develop an intimate relationship with their users -
- to be viewed as a friend, helpmeet, and, in the context of mHealth even as one’s proxy
doctor, health coach or mental health professional -- requires greater examination. So too the
ambivalence that users may feel about continuing the use of mHealth technologies or sharing
the data they derive from this use is a feature that should be acknowledged. The greater
reliance one may have upon a particular technology, the more it is incorporated into everyday
life, subjectivity and embodiment, the more one feels an emotional connection to it, the
greater the potential for ambivalence (Lupton, 1995a). Analyses of social media platforms
such as Facebook are beginning to appear that suggest that users may express feelings of
ambivalence towards these technologies. Users may simultaneously recognise their
dependence upon social media to maintain their social network but may also resent this
dependence and the time that is taken up in engaging with them, even fearing that they may
be ‘addicted’ to their use (Davis, 2012).
It is possible that the practice of self-tracking may also come to be experienced as a burden
rather than a vital source of self-knowledge and empowerment. Anecdotal accounts of self-
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tracking from sites such as the Quantified Self suggest that some regular self-trackers do
experience significant health benefits from doing so, claiming that they feel more in control
of their health and bodies and have successfully lost weight, engaged in regular exercise,
dealt with sleep problems, reduced the consumption of cigarettes and alcohol or managed a
chronic medical condition using these devices. However other users find self-tracking too
onerous, find the devices inconvenient, unfashionable or uncomfortable to wear or that the
apps are not compatible with their smartphones. Some have commented that engaging in self-
tracking led them to become overly focused on their health and to experience feelings of
failure, anxiety or self-hatred (Lupton, 2013).
The implications of mHealth technologies for health promotion work also remain under-
explored and under-theorised. Some survey research has suggested that many medical and
health professionals are not themselves using social or other digital media in their
professional practice to any great extent as yet because of lack of knowledge about how best
to do so or concern about having to learn about using new technologies (Giordano and
Giordano, 2011, Hanson et al., 2011, Usher, 2011, 2012). Here again more extensive and
indepth research is required to explore the attitudes and experiences of health promoters in
relation to these technologies and how they are being domesticated and incorporated into
their everyday working practices and knowledges.
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... The term became popular in 2008 after a series of events in Silicon Valley promoting and endorsing self-tracking. Lupton (2012Lupton ( , 2013aLupton ( , 2013bLupton ( , 2013cLupton ( , 2014Lupton ( , 2016aLupton ( , 2016b and Moore (2017Moore ( , 2018 have established a body of research on self-tracking as a "profoundly social practice" (Lupton, 2014: 77). ...
... The quantified self Lupton (2012Lupton ( , 2013aLupton ( , 2013bLupton ( , 2013cLupton ( , 2014Lupton ( , 2016aLupton ( , 2016b Moore (2017, The quantified self Lupton (2012Lupton ( , 2013aLupton ( , 2013bLupton ( , 2013cLupton ( , 2014Lupton ( , 2016aLupton ( , 2016b Moore (2017, 2018) Moore and Robinson, 2016;Nafus, 2016Surveillance Ball (2005) Ball et al., 2016;Sewell, 1998;Sewell et al., 2012;-Sewell and Barker, 2006Biopolitics Foucault (1991, 2003 Lemke ( The analytic capabilities of these devices continue to grow more sophisticated as they become a type of 'digital therapist' that 'diagnoses moods, alerts users to mood changes before they're consciously aware of them and transforms how people monitor and manage their moods and mental health'. (Schrage 2017, HBR) These extracts elicited from an academic magazine, a business source, and a science publication, indicate the broad reach of discourses of self-monitoring. ...
... The quantified self Lupton (2012Lupton ( , 2013aLupton ( , 2013bLupton ( , 2013cLupton ( , 2014Lupton ( , 2016aLupton ( , 2016b Moore (2017, The quantified self Lupton (2012Lupton ( , 2013aLupton ( , 2013bLupton ( , 2013cLupton ( , 2014Lupton ( , 2016aLupton ( , 2016b Moore (2017, 2018) Moore and Robinson, 2016;Nafus, 2016Surveillance Ball (2005) Ball et al., 2016;Sewell, 1998;Sewell et al., 2012;-Sewell and Barker, 2006Biopolitics Foucault (1991, 2003 Lemke ( The analytic capabilities of these devices continue to grow more sophisticated as they become a type of 'digital therapist' that 'diagnoses moods, alerts users to mood changes before they're consciously aware of them and transforms how people monitor and manage their moods and mental health'. (Schrage 2017, HBR) These extracts elicited from an academic magazine, a business source, and a science publication, indicate the broad reach of discourses of self-monitoring. ...
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Wearable technology (WT) use in organizations is accelerating despite ethical concerns about personal privacy, data security, and stress from increased surveillance. Technology media, a key producer of meanings about WT, gives some attention to these issues but they also routinely promote WT as if they are a panacea for employee wellness. We critically analyze 150 media articles to understand how they justify the adoption of WT into organizational life. We contribute by extending previous work on surveillance technology to show how and why WT media discourses use neo-liberal justifications to justify WT implementation. We explore implications including competing health and wellness discourses and make suggestions for further research.
... These in turn have led to the explosion of health data repositories, containing troves of clinical and genomic data, 1 as well as swaths of self-tracking data from wearables, biosensors and/or environmental data. 3,4 Meanwhile, social media and other data are being mined for health research, 5 and machine learning techniques are being used to help predict health conditions. 6 The storage and processing of health-related data are set to become the fastest growing sector in the datasphere. ...
... All documents highlighted the importance of reducing energy use and/or carbon emissions to address the environmental impact of digital technologies in the health sector. 4 Nearly all documents (n = 14) also stressed the need to attend to the environmental impacts associated with the technology's component materials in terms of used mineral resources and e-waste. Scott and colleagues (2012) categorised these environmental impacts collectively into 'upstream impacts' (extraction, processing, or synthesis of raw materials, the manufacture of components and the packaging and distribution of these components), 'mid-stream impacts' (design, implementation and use) and 'downstream impacts' ('end-of-life' aspects of disposal or recycling). ...
... Underlying the 'more data is better' culture is the underlying assumption that individuals can be completely knowable if enough data is collected and analysed. 39 In the health research field, this is seen to lie with more accurate and detailed information that can help improve the health of patients and/or individuals (c.f.. 4,35,40 ) At the same time, many of these assumptions are tied to economic and political interests: data collection is driven by a cycle of capital accumulation that comes from the expected economic value attributed to the data. 39 One notable example is genomics, in which the value of health-related data goes beyond health benefits in that genomic technologies attract investments as a way to stimulate the economy towards economic growth. ...
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... Yet, digital self-tracking applications are accessible for none to marginal costs, and portable fitness hardware such as pedometers are relatively affordable (Rooksby et al. 2014). Moreover, scholars have collectively recognized the growing popularity of smartphone applications, wearable sensing technology, and other digital self-tracking platforms (Lupton 2013;Rooksby et al. 2014;Sanders 2017). And movements such as Quantified Self (2015) have developed a variety of digital technologies that facilitate the tracking of diverse behaviors (e.g., mobility patterns from GPS data; Parecki 2018). ...
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... Self-tracking is represented as the opposite of covert surveillance or as imposed, a practice that offers people control and inspection of their data and analysis for and among themselves. However, there is evidence of "function creep" and of self-tracking data shifting from private tracking and self-participatory tracking to collective and enforced tracking (Lupton, 2013). Self-surveillance may thus be transformed into mass surveillance that produces data assemblies for the use by interested players, agencies, and organizations beyond the personal and private spheres (Lupton, 2014). ...
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