The quantified self movement: some sociological perspectives

Today's Track Workout

Today’s Track Workout (Photo credit: nocklebeast)

The concepts of ‘self-tracking’ and the ‘quantified self’ have recently begun to emerge in discussions of how best to optimise one’s life. These concepts refer to the practice of gathering data about oneself on a regular basis and then recording and analysing the data to produce statistics and graphs relating to one’s bodily functions, diet, illness symptoms, appearance, social encounters, phone calls, work output, computer use, mood and many more aspects of everyday life.

The advent of digital technologies able to assist in the collecting, measuring, computation and display of these data has been vitally important in promoting the cause of the self-tracking movement. While people have been able to monitor and measure aspects of their bodies and selves using non-digital technologies for centuries, mobile digital devices connected to the internet have facilitated the ever more detailed measurement and monitoring of the body and everyday life in real time and the analysis, presentation and sharing of these data.

These technologies include not only digital cameras, smartphones and tablet computers, but also wearable wristbands, headbands or patches with digital technologies embedded in their fabric able to measure bodily functions or movement and upload data wirelessly. Tiny sensors can also be incorporated into everyday items such as toothbrushes, pyjamas or watering cans to measure such activities. Blood pressure cuffs and body weight scales can be purchased that connect wirelessly to apps. Global positioning devices and accelerometers in mobile devices provide spatial location and quantify movement. Apps that regularly ask users to document their mood can monitor affective states. There seems hardly a limit to the ways in which one’s daily activities can be monitored, measured and quantified. Some committed self-trackers even regularly send stool and blood samples for analysis and use commercially available genetic tests as part of their efforts to construct a detailed map of their bodily functions and wellbeing.

While the concept of self-tracking is not particularly new, the term the ‘quantified self’ (QS) to represent a social movement facilitated by digital technologies is novel. The QS movement was first developed by two Wired Magazine editors, who set up a website devoted to the movement in 2008, and thus began as a technologically-informed phenomenon. According to the Wikipedia definition ‘The Quantified Self is a movement to incorporate technology into data acquisition on aspects of a person’s daily life in terms of inputs (e.g. food consumed, quality of surrounding air), states (e.g. mood, arousal, blood oxygen levels), and performance (mental and physical)’ . This definition immediately begins to construct a view of the body/self as a machine-like entity, with ‘inputs’ and ‘outputs’ (glossed as ‘performance’ in the definition) that can readily be measured and quantified.

How might the QS movement be interpreted through a sociological lens? One way of analysing the phenomenon is via the theoretical perspectives offered by the ‘risk society’ thesis developed by Ulrich Beck (1992). In a world in which risks and threats appear to be ever-present, the certainties promised by the intense self-monitoring of the ‘self-tracker’ may be interpreted as a means of attempting to contain risk, to control the vagaries of fate to some extent. Beck describes the concept of self-reflexivity, or seeking information and making choices about one’s life in a context in which traditional patterns and frameworks that once structured the life course have largely dissolved. 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 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. As one self-tracker has noted, his tracking efforts have ‘made me believe I had more power over my health than I thought’.

Another perspective that may be adopted is that drawing on the philosophy of Michel Foucault. Foucault’s writings on the practices and technologies of the self in neoliberalism are pertinent to understanding the QS as a particular mode of governing the self. Self-tracking may viewed as one of many heterogeneous strategies and discourses that position the neoliberal self as a responsible citizen, willing and able to take care of her or his self-interest and welfare. As Foucault and others using his work have noted, neoliberalism promotes the concept of the citizen who needs no coercion to behave productively and in the interests of the state. Rather, the citizen voluntarily takes up modes of practice that both achieves self-interest and conforms to state objectives (see Lupton, 1995, for this perspective applied to public health).

The QS movement takes up and interprets a view of the body/self that positions it as amenable to improvement, an object of persona enterprise and work. Here an integral source of knowledge is that offered by metrics. The statistical aspect of the practice of self-tracking – the ability to produce ‘numbers’ measuring aspects of one’s life – is integral to the approach. It is 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: tellingly, the QS official website has as its motto ‘self knowledge through numbers’. The implication of this 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.

The lure of ‘numbers’ is that they appear scientifically neutral and exact. The body/self as it is produced through QS, therefore, is both subject and product of scientific measurement and interpretation. Using self-tracking facilitated by digital technologies encourages people to think about their bodies and their selves in different ways; through numbers and as the product of computerised technologies. Such a transformation extends further the move from the haptic (touch sensations) to the optic or visual understanding of the body/self within medicine, as well as the increasing focus on the metric as a valued source of knowledge in many other aspects of social life. 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.

As recent sociological analyses into questions of measure and value have argued, there has been a huge increase generally into the use of metrics in many aspects of social life, which has been greatly impelled by the development of technologies for achieving quantification (Adkins and Lury 2012). 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.

The surveillance society literature (for example, Lyon, 2007) might interpret the QS movement somewhat differently. According to this literature, in the surveillance society, digital technologies are increasingly monitoring and measuring individuals, whether this is achieved via the closed circuit television cameras that have become ubiquitous in public spaces, the loyalty cards offered by businesses or the mobile digital technologies one can now carry or wear upon one’s body. Much of the surveillance society literature has focused on the ways in which others use the data they collect on individuals using digital technologies for security or business reasons. What remains to be fully explored is how the data that are collected voluntarily by an individual using such approaches as self-tracking (in other words, self-surveillance or participatory surveillance) are used by that person for her or his own purposes (Lupton, 2012).

The latest self-tracking technologies allow people to broadcast their ‘numbers’ to many others via social media tools such as Facebook and Twitter. Self-surveillance here moves from an inner-directed preoccupation with the body/self to a performative mode, inviting further scrutiny from one’s friends and followers. Social media tools and other digital platforms also allow people to collate their self-gathered data with others interested in the same phenomenon, or compare their data against others’ data. Indeed at least one multinational workplace has already instituted a competition requiring participating employees to upload and display to all other workmates data they have collected on their bodily movements and weight loss using self-tracking devices as part of efforts to motivate them to achieve higher fitness levels.

Approaches from postphenomenology developed in science and technology studies and philosophy offer a theoretical approach to think about the ways in which humans interact with their technologies (see, for example, Ihde, 2009). These perspectives address such issues as the ontological nature of the human/technology interaction, the ways in which technologies are incorporated into concepts of embodiment and selfhood and how they extend or enhance these and how social relations are configured through, with and by technologies. For this theoretical position it is difficult, if not impossible, to separate technology from its user, as both are viewed as mutually constituted. Research questions focus on how the user/technology assemblage is configured, and how this assemblage views itself and interacts with other human and non-human actors or assemblages. There are complex ontological issues here in relation to the ways in which the human/technology assemblage is constructed and reconstructed.

Little specific academic research has been published that has specifically addressed the QS movement thus far, as it is such a new phenomenon (although for some interesting blog posts that have begun to explore some of these issues see my collection The Sociology of the Quantified Self). Yet from a sociological perspective a number of interesting questions about the quest to achieve ‘self-knowledge through numbers’ arise, including the following: What types of people are attracted to self-tracking? How do they use the data they produce? How are concepts of the body, self, social relationships, health and happiness both configured and negotiated via these data? How do members of their social networks respond to the sharing of data produced through this self-surveillance? How do self-trackers’ doctors or therapists make use of the data they produce? What the implications of shared data derived from self-tracking for patient empowerment? How does the digital device construct reality for its user, how it is incorporated into the routines of everyday life, how does it shape social encounters, how does it present users to others and to themselves? There is much more here to investigate in relation to the attempt to achieve ‘self-knowledge through numbers’.


Adkins, L. and Lury, C. (2012) Introduction: special measures. The Sociological Review, 59(s2), 5—23.

Beck, U. (1992) Risk Society: Towards a New Modernity. London: Sage.

Ihde, D. (2009) Postphenomenology and Technoscience. New York: State University of New York.

Lupton, D. (1995) The Imperative of Health: Public Health and the Regulated Body. London: Sage.

Lupton, D. (2012) M-health and health promotion: the digital cyborg and surveillance society. Social Theory & Health, 10, 229–44.

Lyon, D. (2007) Surveillance Studies: An Overview. Cambridge: Polity Press.

41 thoughts on “The quantified self movement: some sociological perspectives

  1. A most interesting read. This bit caught my eye:
    “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.”

    Personally, my experience is exactly the opposite. Tracking weight and calorie intake and burn over the last 10 months has for the first time calibrated my capacity to interpret physical sensations—I am now much more closely attuned to the functioning of my body. Last night I guessed the calorie content of a meal I’d just eaten—a recipe we’d not had before—to within 20 calories (537 actual vs. 550 guessed). This was partly experience, but partly reading what are now well-calibrated internal physical sensations that tell me after a meal how much I’ve eaten, or rather how much more (if anything) I should still eat in a day. I have also seen dramatic benefits in terms of a 22% reduction in weight, moving to close to the middle of the medically-defined healthy range. I regard this as a major positive health outcome.

    The post comes across as balanced, but pretty skeptical of there being any possible value in such quantification activities. Have you tried them yourself?

    • Thank you for your comments, Duncan. It is very interesting to read your remarks about your experiences of how the data you derive from self-tracking and your felt physical sensations interact and contribute to each other.

      I am not at all sceptical about the value of self-tracking – I merely have an academic interest in it as a sociocultural phenomenon and neither advocate or condemn the practice. I can see why some people would find self-tracking very useful.

      As for your question – no, I haven’t tried self-tracking as I don’t have a personal interest in my own body metrics, but from a research perspective I am very interested in why others do it and what they gain from it. I aim to conduct some empirical research on this once I find some funding. This more theoretical piece is a precursor to moving ahead to conduct such empirical work.

      • ‘I merely have an academic interest in it as a sociocultural phenomenon and neither advocate or condemn the practice.’ You sound like Pontius Pilate. Firstly, you say that the QS movement suffers from the fallacy of believing numbers are somehow ‘fact’ and not value-laden – but then, your own analysis is also value-laden (‘neoliberal, surveillance society’) and therefore its not true to say you ‘neither advocate or condemn’. Secondly, I don’t see the point in standing back and simply theorising about the QS movement, without asking if it actually works – does self-tracking help people move towards the goals they set for themselves? And why don’t you try it for yourself?

      • Using the terms ‘neoliberal’ and ‘surveillance society’ is a matter of adopting well-known sociological phrases to describe aspects of contemporary society. There are some things that may be helpful about self-tracking for those who use it and others that we need to question. That is what my piece is doing, as well as attempting to site the practice in sociological theory as a starting point for further investigation. I agree that it is important to investigate how self-tracking is used by those who have adopted it and I am in the process of applying for funds to conduct empirical research on self-trackers. I haven’t tried it for myself because I simply don’t have an interest in doing so, but I am interested in why others choose to self-track and how it affects their lives.

  2. Hi Dr. Lupton. I’ve been drawing on your sociological literature for quite sometime but have only recently stumbled upon your new “digital intellectual” persona (love it). I feel compelled to comment on this piece on the “quantified self” and “self-tracking” as it hits many of the same themes of some of my own work in this area.

    It is my sense that quantification becomes an increasingly appealing practice not only because it is easier to trust the ‘truthiness’ of numbers but because, as you mentioned briefly, quantification connects with the affective regimes of progress, anticipation and temporality (see Adams, Murphy and Clarke 2009) inherent in the biomedical era. Charting progress in ever-increasing areas of life (from diet to sleep to bowel movements) becomes viewed as a necessary measure to optimize one’s health and secure the best possible future – a most ‘hopeful’ and desirable outcome for informed, responsible, neoliberal citizens.

    A graduate colleague of mine developed a paper which we presented at Society for the Social Studies of Science conference in Cleveland last year about quantification and body-tacking in the Wii Fit. It’s Foucauldian inspired title was “The Care of the Mii: Technoscience, Surveillance and the Biomedical Body in the Wii Fit”. If you are unfamiliar, the game is an exercise game the tracks the body’s weight and its movement, which is projected virtually through an avatar called the “Mii” (pronounced “me”). Our empirical analysis was limited but through the interviews we conducted, we found that users of the Wii Fit took an ambivalent stance about the game’s mandatory body-charting, simultaneously calling BMI an unreliable measure of health but finding the game’s built-in pressuring of users to comply to its recommended daily weigh-in as irresistible, indicating that they hated being “yelled at” by their Mii avatar and felt guilty missing a daily measure on their monthly weight log.
    I also ran into some self-quantifiers in my masters thesis, in which I interviewed a couple of “Primal Dieters.” This group seemed apt to take up self-quantification projects as a form of “experiment.” In this piece here you ask what types of people tend to be attracted to self-tracking. From my experience studying the Primal Diet community, they tend to be well-educated, entrepreneurial, “anti-authoritarian” types who prefer to take “data into their own hands” and draw their own conclusions, often rejecting the conclusions that medical experts draw from clinical data. They refer to their experiments as “n=1” experiments and one participant of mine believed that if each person in his community participated in body-tracking and they were able to aggregate their results, their experiments would provide more scientifically robust conclusions that that of traditional nutrition studies.

    I’d be happy to share with you some information from either project if you’d life. Coincidentally I’ll also be at the University of Sydney in February, pursuing a degree in international public health.

    • Hi Amanda. Thanks for those details of your research – very interesting stuff. I would love to have copies of any papers you have written from your research ( And do get in contact when you are Sydney!

  3. Great blog. I’d be interested to know, do you make a distinction between healthy people who collect data purely out of interest and people who collect data in order to track and manage diseases or illness symptoms? Diabetics have been using technology to self-monitor for many years. Is it the voluntary self-monitoring (as opposed to the imposed self-monitoring due to disease) aspect of QS that you find interesting?

    For me, knowledge is power and collecting data leads to greater patient empowerment . Being a patient places you in a vulnerable position but collecting my own data allows me to have more control over my conditions and treatment and therefore have less contact with the medical system. In the UK, there is still an attitude of paternalism towards patients. Many doctors prefer to keep patients in the dark about their data. Doctors often won’t give you your numbers, many will only give you their interpretation of the numbers, which I’ve found can often be wrong. As a data collecting patient, I want the empirical data – the numbers and the ranges so that I can conduct my own analysis.

    I’m the only person who knows the exact context in which the data was collected (time of day, food ingested, dosages of medicines taken, activity done, time of the month, stress levels, temperature etc.). These variables all influence my treatment needs, so the number along with its context has a more complex meaning and value to me than it does to a doctor who sees an decontextualised number and interprets that number solely in terms of where it appears in a population reference range (a population that will include people a lot older, younger, healthier or sicker than me).

    Also, the medical model of disease means that doctors are trained to give consideration to data at extreme points outside of a reference range and tend to take a binary (“normal”/”not normal”) view of numbers, whereas I might be interested in subtle shifts in the pattern of data over time that could occur both within a range and outside of it. These shifts can have real significance for me in terms of improving my day-to-day disease management but may be insignificant to a doctor trained in a reductionist medical model.

    On the subject of ontology, technology and the ‘truthiness’ of numbers, I find that having an empirical way to test the actual ‘numerical’ state of my body compared to my bodily sensations is extremely useful. For example, Diabetics can get ‘relative hypoglycaemia’ or ‘false hypos’ after running higher sugars for a while. This is where you feel like you are having a hypo (insulin overdose) and have all the symptoms of a hypo, but in fact you are not “empirically” hypo according to your number. In this instance your numbers are true and your bodily sensations are of no value as they are not functioning properly as the warning signs that they usually represent during normal hypos. Technology serves as a way to objectively test your hypothesis that you are hypo.

    However the numbers aren’t always “true” as technology can be faulty and sometimes your bodily sensations are more trustworthy than the numbers. The numbers always require some degree of interpretation.

    I think that if I weren’t ‘diseased’ then I would only be minimally interested in self-tracking, perhaps just at the gym for heart rate etc. I’d rather spend my time doing things other than self-monitoring.

    • Thank you for your comments and insights Jo. You make an important distinction between people who have a condition or illness that they are tracking and those who are tracking for other reasons. I am aware that patients are using self-tracking to test therapies and to bring their data together with others as a way of conducting their own trials of what works and doesn’t work, and also to produce data for themselves that they can use without requiring medical authority, as you do, as a means of gaining control over your illness. You are right, these uses of self-tracking can potentially challenge medical authority and give patients a sense of empowerment and self-knowledge that can be very beneficial. This is a phenomenon that I would also like to pursue in further research as it does raise interesting questions about medical dominance and control over knowledge and the potential for patient empowerment. On the other hand, some patients may be ‘prescribed’ mHealth technologies by their doctors as a means of attempting to lessen time with doctors and to promote self-responsibility, and not all patients might be willing to do this – some would rather the doctor take control and want more rather than less interaction with their doctors. These are complex issues worth investigating.

  4. Pingback: The quantified self movement: some sociological perspectives | This ... | Sousveillance |

  5. Pingback: The quantified self movement: some sociological perspectives | Sociologie des réseaux sociaux |

  6. Pingback: The quantified self movement: some sociological perspectives | information analyst |

  7. Pingback: Homepage

  8. This post made me think of a new product from Weight Watchers called the ActiveLink. Philips makes something like it called the DirectLife. There’s also the FitBit. From what I understand, a person wears the monitor all day long – some people even wear them in the shower and while sleeping (the FitBit, for instance, can monitor how many times per night one wakes up). They monitor movement/activity. They then sync to a computer or “smart” device. Can connect to apps. Produce all sorts of charts and graphs. Set activity challenges based on weight loss goals …

    An area ripe for an empirical study! Very interesting.

    • Yes, Rachael, there are more and more devices available that you can wear on your body all day (and night) long to monitor your body functions. There are even pharmaceutical pills that once swallowed can send signals to a patch worn on the body and thence to a computer to monitor what the drug is doing inside.

  9. Pingback: The quantified self movement: some sociological perspectives | Web of Things |

  10. Pingback: Shame | Abetternhs's Blog

  11. Pingback: The quantified self movement: some sociological perspectives | DDRRNT

  12. Pingback: The quantified self movement: some sociological perspectives | The Sociology of the Quantified Self |

  13. Pingback: The quantified self movement: some sociological perspectives | Health stats and digital health cornerstones |

  14. Pingback: The quantified self movement: some sociological perspectives | PHARMA GEEK |

  15. Pingback: The quantified self movement: some sociological perspectives | Quantified Self, Lifestyle Design, mHealth, Personal Analytics, Big Data |

  16. Pingback: The quantified self movement: some sociological perspectives | Mobile Health: How Mobile Phones Support Health Care |

  17. Pingback: The quantified self movement: some sociological perspectives | DbtMobile, le blogDbtMobile, le blog

  18. Pingback: The quantified self movement: some sociological perspectives | Quantified-Self & Gamification |

  19. Pingback: Living the quantified self: the realities of self-tracking for health | This Sociological Life

  20. Pingback: The quantified self movement: some sociological perspectives | e-Xploration |

  21. Pingback: Moving attachments: our emotional relationship with mobile digital media technologies | This Sociological Life

  22. Pingback: The quantified self movement: some sociological...

  23. Pingback: The quantified self movement: some sociological...

  24. Thanks so much for this post!
    I’m currently writing my masters dissertation about digital self-tracking of menstrual cycles and it has proven to be a challenge to find literature. But you blog post have given me some ideas. Your collection is also a good starting point.

  25. Pingback: The quantified self movement: some sociological...

  26. Pingback: Top 30 Sociology Blogs of 2013

  27. Pingback: The quantified self movement: some sociological perspectives ← Msante & Quantified Self

  28. Pingback: An Introduction to the Quantified Self Research Network’s Inaugural Meeting | This Is Not a Sociology Blog

  29. Pingback: Best Fascinated Sociology Blogs | siadjnu

  30. Pingback: The quantified self movement: some sociological...

  31. Pingback: Self Knowledge // #BCM310 | TJL

  32. Pingback: Introducing Quantified Information Governance: A New Path to Return on Data - Information Governance Initiative

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s