Motivation and emotion/Book/2013/Self-tracking and motivation

Self-tracking and motivation:
How does self-tracking affect motivation?

Multimedia presentation (5 min)

Overview

Wondering about apply self-quantification/tracking to your life but don’t know where to start or really what it even is?

This book chapter answers the following questions:

Focus questions: What is self-quantification/tracking? What process motivates self-quantification? How has this movement come about? What are some of the more popular/ widely used self-quantification technologies and techniques? What is the ‘gamification’ aspect of these technologies? What types of motivation are used in self-quantification technologies? How do social needs motivate self-quantification? How do self-quantification technologies effect achievement? Which motivational themes are relevant to self-quantification? Am I a self-quantifier?

What is self-tracking?

Self-tracking refers to a modern phenomenon that has developed out of the human need to ‘self-regulate’. Self-regulation broadly refers to the process in which “people attempt to accomplish the goals they have for themselves, they mentally step back to monitor and evaluate how well things are going” (Zimmerman as cited in Reeve, 2009). As societal and technological advancements progress, people have developed new ways of monitoring and sharing their attempts at and success in, self-regulation and this is referred to as self-tracking. “Self-tracking has now become the inspiration for a whole movement called the quantified self” (Evans, 2012) and as such for the purposes of this book chapter self-tracking will be referred to as the quantified self or self-quantification. The quantified self refers to “a way of applying the social web, apps and consumer technology for personal health and productivity” (CIPR, 2013). “Members of the quantified-self movement have invented bio-digital devices to track their daily calorie intake, alcohol intake, heart-rate, blood-sugar levels, exercise regimes, social life, sex life, emotions (and) finances…”(Evans, 2012). This concept is best described as “self-knowledge through numbers” (Evans, 2012). The quantified-self movement incorporates psychological science principles in taking “a rational, scientific approach to self-improvement, which means keeping account of yourself, so that you can see what progress you’re making, which interventions are really working, and which are a waste of time” (Evans, 2012). This process of progress evaluation is in line with self-regulatory procedure.

Self-regulation as a process:

Self-regulation is often thought of as a cylindrical process. Reeve (2009) refers to the self-regulation process as “an ongoing, cylindrical process… it involves forethought, action and reflection”. Reeve (2009) describes forethought as involving ‘goal-setting’ and ‘implementation intentions’, Reeve describes the second stage in the self-regulation cycle as performance and the third stage as self-reflection which involves ‘self-monitoring’ and ‘self-evaluating’. Bandura also posited that self-regulation involves three processes; “self-observations, self-judgements and self-reactions” (Bandura as cited in Zimmerman & Schunk, 2011).

Self-observations

According to Bandura (as cited in Zimmerman & Schunk, 2011) self-observations “refer to tracking specific aspects of one’s functioning”.

Self-judgements

“Bandura describes self-judgements as comparisons of ones performances with a standard” (as cited in Zimmerman & Schunk, 2011).

Self-reactions

According to Bandura (as cited in Zimmerman & Schunk, 2011) “self-reactions refer to motivational and behavioural inferences that learners draw from their behavioural outcomes, such as beliefs about one’s efficacy”.

The theoretical self-regulatory process posited by Reeve (2009) shares many similarities with Bandura’s earlier model, both assert the process involves three distinct steps and that it is cylindrical in nature. Reeve’s (2009) first stage ‘forethought’ aligns closely with Bandura’s ‘self-observations’ in the same way that Reeve’s ‘self-reflection’ stage aligns closely with Bandura’s ‘self-judgements’ and ‘self-reactions’ stages. Zimmerman and Schunk (2011) assert that Bandura’s “self-reactions (stage) can produce adjustments in self-observations or self-judgements during the next cycle of learning”, this source further asserts; “shifts in self-regulation often indicate that a feedback cycle is completed and that a new cycle of self-regulation is about to commence”. Therefore, literature regarding self-regulation asserts that it is a cylindrical process involving three distinct steps and features include observing aspects of one’s functioning, goal-setting, implementation intentions, evaluating performance (with a standard) and self-monitoring as well as self-evaluation.

How has this movement come about?

The phrase ‘quantified-self’ was first used by Gary Wolf and Kevin Kelly, editors of wired magazine, in 2007 (CIPR, 2013). According to Morozov (2013) Wolf and Kelly cofounded the quantified-self movement. In 2010; “Wolf penned something of a manifesto for this nascent movement… which was published in… The New York Times Magazine, launching the Quantified-self movement not just nationally but globally” (Morozov, 2013). This article contained four factors that Wolf speculated led to the swift rise of this movement in recent years these included;

electronic sensors shrank in size and became more powerful… once they entered our smartphones, they became ubiquitous… social media :–from Facebook to Twitter- made sharing seem normal… the idea of cloud computing made it possible (and acceptable) to offload one’s :data onto distant servers, where merged with the data of other users, it can be expected to yield better results (Morozov, 2013).

It was the wide publication of self-quantification principles that has allowed for the speedy development of this movement. Since its first mention in 2007 and further publicity in 2010, the self-quantification movement has invaded popular culture, the media and consumerism. “The (quantified-self) movement has really started gaining traction around 2010, with a number of prominent features in tech media and publications” (Sandhu, n.d.). Lipson and Kurman (2013) make some stark comparisons between self-regulatory practices of yesteryear and those that the average person is now able to conduct independently because of self-quantification;

For most of human history, monitoring one’s biometrics has been a fairly primitive process… people count their pulse, their breath :rate, examine the surface of their tongue… now new medical technologies allow people outside the medical establishment to track and :monitor, even predict what’s going on in their bodies… other fields have been transformed by growing amounts of available data, :computing power and the internet… people can predict and manage non-intuitive causalities (Lipson & Kurman, 2013. p. 142).

What are some of the more popular/ widely used self-quantification technologies and techniques?

Sandhu (n.d.) explains how many companies have developed hardware and software in order to meet the demands self-quantification’s popularity have created;

The initial following of QS was made up of the typical early adopter set, people who were technologically focused, data driven, and :open to the ideas of hacking and creating hardware to capture personal data. However, in recent years the movement has become more :mainstream, and a number of companies have entered the movement, offering hardware solutions to gather data.

It is beyond the scope of this book chapter to explore extensively all the facets of life in which self-quantification has developed technologies. However, this text will endeavour to explore the areas in which these technologies are most frequently applied. The following explores some of the most popular and most useful quantification technologies as applicable to the average person.

Health & Fitness

One self-quantification technology most frequently cited in literature on the subject is the Nike+ smartphone app. In this app “an accelerometer embedded in a shoe tracks the workouts of its wearer… runners and other athletes log on to nikeplus.com to access information-speed, mileage, elapsed time, calories burned-to see how they are going, to track their progress against goals” (Pine & Korn, 2011). Another frequently mentioned smartphone enabled self-quantification technology is ‘fitbit’ which “sells a clip on sensor that measures the number of steps you take each day, your total distance travelled, the calories burned and even your sleep quality, which you can then tack at fitbit.com” (Pine & Korn, 2011). Browsing the apple Iphone app store one can choose ‘categories’, ‘health and fitness’ and open a plethora of self-quantification technologies in the form of apps. Some of the more popular titles include:

• Calorie counter and diet tracker – by MyFitnessPal – this app allows the user to keep a track of their calorie intake via a database of foods and their corresponding calories. Users provide details about their current weight and fitness level as well as their goals.
• Sleep cycle alarm clock – this app analyses your sleep patterns waking you in early sleep stages instead of later sleep stages or REM sleep, working on the theory this means the user wakes feeling more rested.
• MapMyRun – This app uses GPS mapping to track the distance ran or walked by the user. The app also times the users workout and allows the user to share information about the workout including, time, distance and calories burned through popular social media.

In addition to these popular self-quantification techniques that signify some of the most downloaded apps worldwide there are apps that cater for every self-tracking need. There are apps available for tracking everything from diet, to exercise, to mood, to sleep patterns and cycles, to menstrual cycles and fertility for those endeavouring to fall pregnant (or not).

Finance

Another popular application for self-quantification technologies is tracking one’s financial activities. This includes one’s spending habits. There are a number of apps available to track spending of self-quantifiers.

• Spendee – This app boasts “the power of unique data analysis in an adaptable environment that automatically and thoroughly analyses your income and expenses, giving you intelligent advice on how to make the most of your money”.

There are many other apps in the finance section of the apple app store that offer similar abilities. If you can think of some aspect of your finances you want to track, there is an app for it! Technologies allowing for self-quantification, data collection and social sharing are everywhere. Cofounder of the quantified-self movement Gary Wolf very accurately summarises the effect this phenomenon is having while infiltrating the modern world; “almost imperceptibly numbers are infiltrating the last redoubts of the personal… sleep, exercise, sex, food, mood, location, alertness are all being tracked and measured, shared and displayed” (Wolf as cited in Pine & Korn, 2011).

What is the ‘gamification’ aspect of these technologies?

Jones (2013) describes aspects of self-quantification apps (and their corresponding websites) that allow one to compete against oneself or others and provide virtual prizes and rewards for reaching goals; the Fitbit website awards me a badge every time I climb a certain amount of stairs and transmits that fact to my Facebook and the Nike+ website allows me to ‘race’ with my friends whether we are running at the same time or not (Jones, 2013). It is the competitive and social media sharing aspects and also the virtual prize-rewards of these self-quantifying apps and websites that led Dembosky to refer to such technologies as the ‘gamification’ of health practices (Dembosky as cited in Jones, 2013). In the book, What Video Games Have to Teach Us About Learning & Literacy, author James Gee cites “interactivity, the ability to customise and personalise the experience, the provision of ‘just in time’ information, and the presentation of information in multiple modes (audio, visual, textual and tactile)” as successful techniques for engaging players in rapid and effective learning (Gee as cited in Jones, 2013). Such characteristics are a part of many of the most popular self-quantifying apps.

What ‘types’ of motivation are used in self-quantification technologies?

There are two main categories into which human motivation falls. Intrinsic and Extrinsic motivation. Intrinsic motivation refers to “the inherent propensity to engage in one’s interests and to exercise one’s capacities and, in doing so, to seek out and master optimal challenges” (Deci & Ryan as cited in Reeve, 2009 p.111). Intrinsic motivation “emerges spontaneously from psychological needs and innate strivings… when people are motivated intrinsically, they act out of interest ‘for the fun of it’” (Reeve, 2009). Essentially intrinsic motivation stems from one’s capacity and desire to pursue an interest into stages of mastery for the sake of enjoyment. Extrinsic motivation “arises from environmental incentives and consequences… praise, attention… tokens, approval… public recognition… extrinsic motivation arises from some consequence that is separate from the activity itself” (Reeve, 2009). Thus, extrinsic motivation is driven by the possibility of reward whether it be in the form of a physical reward, some type of token reward, or social reward in the form of acclaim and attention. Self-quantification technologies rely on the presence of intrinsic motivation in their users while providing sources of extrinsic motivation. For example: Fitness apps that track and log data about one’s workout and allow one to share that information via social media afterwards (in the same way MapMyRun does) rely on a certain amount of intrinsic motivation from the user, to motivate them to download the app in the first place and to strive to use the app to meet their fitness goals. These apps rely heavily on extrinsic motivation as they are often promoted as a motivational tool to help those who are lacking in intrinsic motivation. These apps often award users with virtual awards such as ‘badges’ when they reach their goals (or the goals the app has set for them), this is an example of token reinforcement. The social media sharing aspect of these technologies is also quite extrinsic in nature as it potentially facilitates attention, praise and public recognition from friends and followers through various social media outlets.

How do social needs motivate self-quantification?

According to Plotnik and Kouyoumdjian (2011, p.332) “social needs are needs that are acquired through learning and experience”. Reeve (2009) asserts that “social needs arise and activate emotional and behavioural potential when need-satisfying incentives appear”. So, social needs facilitate emotional and behavioural actions when potentially socially satisfying inducements present themselves. This statement is further supported by Reeve (2009) “Social needs are mostly reactive in nature… they lie dormant within us until we encounter a potentially need-satisfying incentive that brings the social need to the front of our attention in terms of our thinking, feeling and behaving”. Therefore, social needs have the potential to motivate behaviour. Since self-quantification technologies often feature social aspects as a means of sharing users’ progress, social gratification serves as a means of motivating achievement. As such, human social needs are highly relevant to self-quantification in the 21st century.

It can be asserted that improvements and progress recorded by self-quantifying technologies are in part due to motivation resulting from social needs. Many of these technologies feature the option to upload progress and data collected to social media websites like Facebook, Twitter and Instagram. There is also often a feature allowing one to send an email or text message showing the details of their achievements. These features allow users to employ self-quantification technologies for the purpose of seeking social gratification, acceptance and praise from their peers via social media. For many self-quantifiers the motivation behind logging an extra kilometre on one’s fitness app may be the revere of one’s peers when one upload the data associated with this workout to social media.

How do self-quantification technologies effect achievement?

Spielberger (2004) refers to achievement motivation as “the desire to excel at effortful activities”. Research by McClelland “found that the goals that people with a high need for achievement set for themselves are challenging but realistic” (McClelland as cited in Nevid, 2009, p.289). Self-quantifying technologies may help users to be pulled toward achievement motivation or to engage in avoidance motivation. Achievement motivation refers to “the need to excel in one’s endeavours” (Nevid, 2009, p.289). Avoidance motivation refers to “the motive or desire to avoid failure” (Nevid, 2009, p.289). Self-quantifying technologies may have features that encompass both of these concepts in order to motivate users. Health and fitness application Nike+ allows you to choose a distance goal, this is a good example of applying the avoidance motivation concept in self-quantification technology as avoidance motivated users will be more likely to complete the distance nominated pre-workout. An achievement motivated user may choose the more open-ended format of health and fitness app MapMyRun as their inbuilt desire to excel means they will do so freely.

Which motivational themes are relevant to self-quantification?

There are several overarching themes that encompass the concepts discussed in this book chapter. These are general concepts established through research into motivation that serve to guide the way one thinks about motivation. In this section those which are most relevant to self-quantification will be discussed.

Motivation benefits adaptation:

“Motivations and emotions provide tremendous resources that allow people to adapt to environmental changes” (Reeve, 2009). If one wishes to adapt, motivation is key. This assertion is supported by Reeve (2009)

anyone who tries to lose weight, write a creative poem, or learn a foreign language without first recruiting motivation will quickly :realise that motivation benefits adaptation… take away the motivational states, and people would quickly lose a vital resource they :rely on to adapt and maintain well-being.

Citing this, personal adaptations one wishes to make whether using self-quantification technologies/strategies or not should take into account the importance of motivation.

Motivation includes both approach and avoidance tendencies:

As previously discussed, many self-quantification technologies provides options for both approach and avoidance achievers. When attempting to motivate oneself to achieve it is important to be aware of which category you fall into. As aforementioned, this knowledge will help you decide whether to use a distance goal or a more open-ended quantification technique. Are you motivated because you want to avoid failure or because you want approach and excel in achievement?

To flourish motivation needs supportive conditions:

“A person’s motivation cannot be separated from the social context in which it is embedded” (Reeve, 2009). When seeking motivation it is important to surround oneself with supportive environs as “those who are surrounded by social contexts that support and nurture their needs and strivings show greater vitality, experience personal growth, and thrive more than those who are surrounded by social neglect and frustration” (Keyes, Ryan & Deci as cited in Reeve, 2009). Self-quantifying technologies could be a part of these ‘supportive conditions’ that are vital to ongoing motivation.

Am I a self-quantifier?

If you answer ‘yes’ to a question add the number of points with which it corresponds, if no, do not add any points. The sum of scores at the end of the quiz reveals your self-quantification data!

1. Do you have access to one of the following; a smartphone, tablet, computer, the internet? (If yes add 1 point).
2. Do you use any of the following social media websites: Facebook, Twitter or Instagram? (If yes add 1 point).
3. Do you use any of the following apps/websites?: Nike+, MapMyRun, MyFitnessPal, Spendee or fitbit? (If yes add 3 points).
4. Have you ever used one of these apps to share your personal data through social media, email or text message? (If yes add 3 points)
5. Do you use more than one technology to record personal data in the pursuit of self-improvement? (If yes add 4 points).
6. Have you ever used any other application that records your personal data in the pursuit of self-improvement? (If yes add 1 point).
7. Is there a technology that you would attribute personal self-improvement to? (If yes add 2 points)

What does your score say about you?

• 0-5 points you're a non-quantified Nancy! You are yet to embrace the self-quantification movement!
• 5-10 points you're catching on! You are starting to embrace some self-quantifying technologies...
• 10-15 points you're a self-quantifying smarty! Not only are you embracing the self-quantifying technologies available you're sharing your data with the world - you're a part of the movement!

References

CIPR (Chartered Institute of Public Relations). (2013). Share this too: More social media solutions for PR professionals. Cornwall: UK. :John Wiley & Sons Inc.

Evans, J. (2012). Philosophy for life and other dangerous situations. Great Britain. Ebury Publishing.

Jones, R. (2013). Health and Risk Communication: An Applied Linguistic Perspective. NY: Routledge publishing.

Lipson, H. & Kurman, M. (2013). Fabricated: The new world of 3D printing. Ind: John Wiley & Sons.

Morozov, E. (2013). To save everything, click here: The folly of technological solutionism. PublicAffairs publishing.

Nevid, J. (2009) Psychology: Concepts and applications. Boston, MA: Houghton Mifflin Company.

Pine, B. J. & Korn, K. C. (2011). Infinite possibility. San Francisco, CA: Berrett-Koehler Publishers, Inc.

Plotnik, R. & Kouyoumdjian, H. (2011). Introduction to psychology. Belmont, CA: Wadsworth publishing.

Reeve, J. (2009). Understanding motivation and emotion (5th ed.). Hoboken, NJ: John Wiley & Sons Inc.

Spielberger, C. (2004). Encyclopaedia of applied psychology. Tampa, FL Academic Press.

Zimmerman, B. & Schunk, D. (2011). Handbook of self-regulation of learning and performance. NY: Taylor & Francis.

External links

• The quantified self movement: Unlocking your own personal data stream