The Quantified Self (QS) movement was founded in 2007 by Gary Wolf and Kevin Kelly of Wired magazine. It is the practice of self-tracking. The underlying philosophy is that by using technology to monitor and track all facets of your daily life (monitoring everything from mood to food intake, to activity, to heart rate, etc. etc.) you will be spurred forward to become a better you.
I recently brought this up on the forums, and just yesterday Andrea LaMarre contacted me regarding the fact that iOS/8 (the operating system on iPhones) offers no feature for turning off the tracking of the steps you take.
The QS movement is just like every other dewy-eyed belief system in new technology’s transformative power for humankind. Their mantra? n=1. What does that mean? It means that pursuit of personal improvement is inherently personal.
Somewhat like proponents of net neutrality and free internet access for all, the QS founders and followers are not naïve or utterly clueless. They do understand the commercial realities of the technology they use. But they overestimate their ability to wade into the alligator pond confident they will negotiate safe passage.
“QSers generate data in the aggregate that makes large institutional data collectors salivate.” 1
“Self-tracking at first glance appears to be a highly specialised subculture, confined to the chronically ill, obsessives, narcissists or computer geeks...However the concept and practices of self-tracking are now dispersing rapidly into multiple social domains. There is evidence of ‘function creep’, or the move of self-tracking practices from private and participatory self-surveillance to collective and imposed surveillance.” 2
Dr. Lutton, quoted immediately above, has developed five modes for classifying types of self-tracking:
Private
Pushed
Communal
Imposed
Exploited
The private self-tracking realm is the core QS movement. These individuals believe in n=1 and not only do they track their personal data, but they also analyze and assess it in such a way that it is idiosyncratic and likely not easily transferable to others.
The pushed tracking world is incentivized self-tracking from another source. The fields of patient self-care, preventative medicine and health promotion are all super-keen to use these technologies to ‘nudge’ people into behaviour that will purportedly improve health outcomes. The workplace has become the central force in pushed self-tracking with financial incentives and “team spirit” as part of numerous wellness programs. Wearable technology companies such as Fitbit are busily signing up employers and insurance companies to buy their self-tracking devices and analytics software to be rolled out for employee wellness programs or applied for insurance discounts. 3
Communal self-tracking sounds like an oxymoron, but it is the process of sharing your self-tracking data on social media platforms. It makes self-tracking competitive at the same time as it is seeking acceptance from the group as well. Post-hoc rationalizations from communal self-trackers tend to be about how it enables them to learn from others, improve their data visualization methods, and be inspired to get more meaning out of their own personal data. 4 Communal self-tracking also has another distinct stream with more of a crowd sourcing, citizen responsibility approach. 5
Imposed self-tracking is as it sounds: the benefit of the data captured is not for the self. “Sociometric Solutions advises companies using sensor-rich ID badges worn by employees. These sociometric badges, equipped with two microphones, a location sensor and an accelerometer, monitor the communications behavior of individuals — tone of voice, posture and body language, as well as who spoke to whom for how long.” 6
Exploited self-tracking is when either private, pushed, communal or imposed self-tracking is repurposed for commercial benefit. Your data becomes a commodity.
My mantra is: if it’s tracked, it’s hacked. And I don’t simply mean the data may be stolen; I mean that it will be a commodity where its original intent is subsumed by commercial interest.
Why is a compulsory quantified self of any concern to those with eating disorders?
We assume that when something is quantified then it has a) a "right" and a "wrong" marker, and b) that measuring anything validates the measurement.
Systematic Review
So in what way does counting steps correlate with improved health outcomes?
Of 26 studies comprising 2767 participants, the authors concluded “the results suggest that the use of a pedometer is associated with significant increases in physical activity and significant decreases in body mass index and blood pressure. Whether these changes are durable over the long term is undetermined.” 7
And as usual we find that the actual data compiled do not quite support the conclusions made. The vast majority of participants were white females, BMI 30, normotensive and had “well controlled serum lipid levels”. Dropout rate was at 20%.
The authors define the participants as relatively inactive although the spread of pre-study step levels is large. The BMI decreased by 0.38 from baseline, or approximately a 3 lb. (1.4 kg) drop in weight (assuming average height of 5’4” for females). It’s simply assumed that weight loss is an improved health outcome. I’ll direct you to read the blog posts under the category “Obesity” if you feel such an assumption is scientifically proven.
High blood pressure is a risk factor for developing heart disease. It is not a disease in and of itself. In a study of 4089 patients with confirmed systolic heart failure, 550 deaths occurred within the year of study. However event-free survival for men was correlated with higher BMI and waist circumference. Event-free survival for women was correlated with higher BMI and women with a high waist circumference trended towards improved outcomes as well. The obesity paradox is at work yet again. 8
As the counting-steps study participants were predominantly normotensive then “significant decreases” in blood pressure is a non-event as a health outcome. The pre-intervention average blood pressure was 129/79. The post-intervention was 125.2/79.62.
To the authors’ credit they defined the pre-study readings as normotensive. They are indeed normative for this age group (average age: 49). But in our ever-lowering cut-off points to increase numbers needing treatment, many medical circles refer to a systolic reading over 120 as “pre-hypertensive”.
So the actual conclusions that could be drawn from the systematic review? White overweight older women lose next to no weight and remain normotensive after an intervention set to increase the number of steps they walk in a day.
Counting Steps
If there were one overarching observation I would make about anxiety disorders it would be that checking and monitoring (present in all anxiety disorders) are also the foundation of a severe reduction in quality of life.
Whether it is hyper-vigilance associated with self or surroundings, someone with an anxiety disorder cannot simply ignore stimulus that has been identified as a possible way to avoid a threat.
For reasons I go into in the blog post Insidious Activity, those with eating disorders (an anxiety disorder centered on food) appear to have aberrant responses to an increase in neuropeptide Y. NPY is an orexigenic neuropeptide that is released in our system when we are energy deficient. When its level increases, we are drawn to eat more and move less (to rectify the energy deficit). In those with eating disorders it appears to trigger an anorexigenic response: move more, eat less. 9
Not being able to turn off tracking the number of steps taken in a day is deadly for those with an eating disorder.
1. D Nafus, Dawn, J Sherman, Big Data, Big Questions| This One Does Not Go Up To 11: The Quantified Self Movement as an Alternative Big Data Practice International Journal of Communication, Vol.8, 2014).
2. D Lupton, Self-tracking modes: Reflexive self-monitoring and data practices, Available at SSRN 2483549, 2014.
3. P Olson, A Tilley, The quantified other: Nest and Fitbit chase a lucrative side business, Forbes, Vol.5 2014.
4. D Lupton, Self-tracking modes: Reflexive self-monitoring and data practices, Available at SSRN 2483549, 2014.
5. J Gabrys, Programming environments: environmentality and citizen sensing in the smart city, Environment and Planning D: Society and Space, Vol.32(1), pp.30-48, 2014.
6. S Lohr, Unblinking eyes track employees, The New York Times, 2014.
7. Dm Bravata, C Smith-Spangler, V Sundaram, AL Gienger, N Lin, R Lewis, CD Stave, I Olkin, JS Sirard, Using pedometers to increase physical activity and improve health: a systematic review, Jama, Vol.298(19), pp.2296-2304, 2007.
8. AL Clark, J Chyu, TB Horwich, The obesity paradox in men versus women with systolic heart failure." The American journal of cardiology, Vol.110(1), pp.77-82, 2012.
9. RA Nergårdh, AU Brodin, J Bergström, A Scheurink, P Södersten, Neuropeptide Y facilitates activity-based-anorexia, Psychoneuroendocrinology, Vol.32(5), pp. 493-502, 2007.