Month: October 2016

Social media and the Quantified Self.

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Maybe it’s the company I keep online, but every day there seems to be more and more posts appearing on my timelines about health, fitness and wellbeing. On any given day, when I look at my timelines and newsfeeds, I note that many of my friends are sharing the fact that they are running (from jogging to marathons), doing crossfit, attending the gym or a personal trainer and eating healthily. It is true that some people in my social media echo chamber are “of a certain age” and because we are being constantly reminded of our mortality, have begun to take better care of ourselves. There is also the “algorithm” debate/conspiracy; that searches which I make influence the information which appears when I am on social media. But, let’s assume, for a minute, that my “Friends” list is a quasi representative sample; are people turning to tech and social media to help them with their health and wellbeing goals and, if they are, is there evidence to support this approach.

There are countless apps available (there are over 13,000 health-related apps in the Apple App Store, here are 39 of them! And yes, I know I said “countless”) which allow users to connect and track performance. There are applications which, along with providing health and medical information, present objective anatomical information. Even the most basic applications for mobile devices allow users to measure sleep, diet, exercise, weight, mood, medication and numerous bodily functions. Additionally, realising the importance of a motivational and support component to the process, quite a few of these applications have reward systems (badges, points or counters) and functionality where collected data can be shared on social media. These apps can be helpful for those trying to get into shape, with even simple smartphone apps helping to significantly increase physical activity (Glynn et al, 2014; Walsh et al, 2016). With the data the applications collect, workouts can be tracked, goals can be set and progress can be monitored. Health psychologists tell us that monitoring, planning and goal setting are all important factors in changing behaviours. Further, if users engage on the social level, interactions with friends can trigger action and the support received from others can help motivation (Ba & Wang, 2013).

Monitoring our health and maintaining healthy behaviour electronically is not new; we have been doing it since the 70’s. Developments and advancements in technology and the rise in popularity of social media, in the last decade, has created a new paradigm, though – the intersection between the Quantified Self and social media. It’s all well and good using apps and mobile devices to monitor and maintain behaviour, but when we go online, or when we interact with others, or click “Share” and our new, changing behaviour is proclaimed to our social circle, something different is happening. From my own limited experiences, participating in Twitter chats and “Liking” the Facebook page of my local Parkrun has already linked me to like-minded people; novice, amateur fun-runners. Getting updates on times, event information, and other runners has inspired and motivated me. Checking my timings, aiming to set a new “PB” and achieving that, has given me a sense of achievement and I feel good!

So far, research into the reasons why people use self-tracking digital devices for health is limited. Research into why people share their health, fitness and wellbeing information on social media, even more so. In the U.S. The Pew Research Center have found that 21% of the adults surveyed report monitoring their health (weight, diet, exercise, blood pressure or medical symptoms) using technology; a medical device (8%), app or tool on a mobile device (7%), computerised spread sheet (5%) and website or online tool (1%). Further, 20% of respondents had downloaded an app to a mobile device to manage and monitor their health behaviour (weight, diet and exercise). Eventhough a recent study  has found that wearing a device which monitors and provides feedback on physical activity may not offer an advantage over standard behavioral weight loss approaches and may result in less weight loss over two years (Jakicic et al, 2016), benefits to wearing these devices  have been uncovered. It has been shown, for instance, that aside from the perceived usefulness of the equipment, self-regulation, social motives and enjoyment explain why some people use these trackers (Straiger et al, 2016).

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It is likely that those who use this technology will, in some cases, share their information of social media; you are encouraged to do so. So far, social media is loaded with inspirational images. Pictures of fit, healthy, active, thin, attractive people running and training effortlessly, eating picture perfect meals abound. Motivational “before and after” stories appear regularly and, while much of this content is intended to inspire, it can have a negative effect. One can’t help but compare oneself to these “fitstagrammers” and, while it has been shown that “fitspiration” images have a positive effect on motivation to pursue healthy goals, these images can have a negative effect on body image (Tiggemann & Zaccardo, 2015) and they can decrease body satisfaction (Benton & Karazsia, 2015). Moreover, Facebook social comparison has been negatively associated with subjective wellbeing (Gerson et al, 2016).

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Like with most things to do with social media, it is early days, research is in its infancy, care needs to be taken and we need balance in our discussion around the subject. Care needs to be taken when taking inspiration from people online. As we discovered last year, with the Essena O’Neill saga, it is very easy to set up a blog or an Instagram account; near perfect pictures are easy to produce; it’s very easy to dispense advice; it’s very easy to make recommendations. It’s not so easy to qualify as a dietician, sports psychologist or for that matter, a mental health professional. And that Insta-Life may not be what it seems.

The intersection between technology, the quantified self and social media is exciting, though;  not just for users, but for research. Extant theories around reward, punishment, motivation, comparison, etc are going to be able to explain a lot, but research on this truly modern paradigm could also shed new light on human behavior.

 

References

Ba, S., & Wang, L. (2013). Digital health communities: The effect of their motivation mechanisms. Decision Support Systems, 55(4), 941-947.

Benton, C. & Karazsia, B. (2015). The effect of thin and muscular images on women’s body satisfaction. Body Image, 13(3), 22-27.

Gerson, J,. Plagnol, A., & Corr, P. Subjective well-being and social media use: Do personality traits moderate the impact of social comparison on Facebook? Computers in human behaviour, 63(10), 813-822.

Glynn, L., Hayes, P., Casey, M., Glynn, F., Alvarez-Iglesias, A., Newell, J., O’Laighin, G., Heaney, D., O’Donnell, M., Murphy, A. (2014). Effectiveness of a smartphone application to promote physical activity in primary care: the SMART MOVE randomised controlled trial. British Journal of General Practice, 64(624), 384-391.

Jakicic, J., Davis, K., Rogers, R., King, W., Marcus, M., Helsel, D., Rickman, A., Wahed, A., & Belle, S. (2016). Effect of Wearable Technology Combined With a Lifestyle Intervention on Long-term Weight Loss. The IDEA Randomized Clinical Trial. JAMA, 316(11), 1161-1171.

Stragier, J., Vanden Abeele, M., Mechant, P., & De Marez, L. (2016). Understanding persistence in the use of Online Fitness Communities: Comparing novice and experienced users. Computers in Human Behavior, 64(11), 34-42.

Tiggemann, M. & Zaccardo, M. )2015). “Exercise to be fit, not skinny”: The effect of fitspiration imagery on women’s body image. Body Image, 15(9), 61-67.

Walsh, J., Corbett, T., Hogan, M., Duggan, J., & McNamara, A. (2016). An mHealth Intervention Using a Smartphone App to Increase Walking Behavior in Young Adults: A Pilot Study. JMIR Mhealth Uhealth, 4(3), 109.