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====== 8 Self-Awareness and Self-Compassion ======

It was late in his life, as he faced his executioners, that one of the world’s greatest thinkers would conclude that death was preferable to giving up philosophy. To those in his midst he declared simply: “The unexamined life is not worth living.” Socrates would go on to swallow hemlock for his crimes—crimes that would come to represent a pinnacle of human achievement.

A century earlier ancient India had yielded another of the world’s greatest philosophers, Gautama Buddha, who said “You are what you think. All that you are arises from your thoughts. With your thoughts you make your world.” The core Buddhist tenet summarized by the Four Noble Truths explains that in order to end our experience of suffering, we must first understand the workings of our mind. We must be able to recognize our thoughts, our emotions, our reactions, and their precursors, as they are the roots of our suffering.

Methods for self-examination, introspection, and self-awareness have since been refined by generations of philosophers, and more recently by modern Western psychologists from Sigmund Freud to Aaron Beck.

Now, in the second decade of the twenty-first century, cognitive behavioral therapy (CBT) has gone online: experience sampling solicits mood updates via smart phone, and the quantified-self movement inspires growing innovation in personal data analysis. But is it reasonable to expect any deeper understanding of our personal thoughts and emotions to arise from data? Can artificial intelligence, sophisticated machine-learning algorithms, and digital visualizations really help us to know ourselves better? If they did, would we be better for it?

In this chapter, we look at the state of the art in technology-mediated reflection, the varied approaches that have been applied to this endeavor, and the research emerging from its use. We also look at the foundations in psychology that underpin efforts toward greater self-awareness and how they are linked to increases in wellbeing. We look at both the potentials and the problems that may be associated with technological intervention into our inner lives, while deliberately evading the question, Would the Buddha have tweeted “feeling one with the universe” from under the Bodhi Tree?

Know Thyself
Why bother? Is self-knowledge merely philosophically virtuous or actually important to greater happiness and flourishing? Methods for CBT demonstrate that increased self-awareness can indeed improve wellbeing. In fact, a healthy chunk of the research and clinical work in modern psychology relies on promoting awareness of one’s thoughts, emotions, and behaviors in order to effectively treat mental illnesses such as anxiety and depression.

Neuroscientist Richard Davidson (e.g., Davidson & Begley, 2012) has identified recognizable neurophysiological patterns associated with self-awareness. He has found that greater self-awareness is associated with increased activity in the insula (involved in consciousness, emotion, and body regulation) and that long-time meditators have larger insulas.

If self-awareness is important to personal growth and wellbeing, what can we do to develop it, and how can technology play a part in that development? The answer is most frequently sought in various forms of reflection, introspection, and mindfulness training. There is an impressive wealth of evidence for the effectiveness of mindfulness practice on wellbeing, including the work of Jon Kabat-Zinn and researchers at the Oxford Mindfulness Centre. Davidson cites neurophysiological evidence for the effectiveness of mindfulness practice both for increasing self-awareness and for tempering potential negative side effects that might accompany this awareness (e.g., hypersensitivity and anxiety). We reserve mindfulness, however, for the next chapter and deal with it as a factor of wellbeing in its own right. In this chapter, we focus on reflection.

According to twentieth-century philosopher, psychologist, and educational reformer John Dewey (2013), it is essential for education to develop the skills of reflection: “while we cannot learn or be taught to think, we do have to learn to think well, especially acquire the general habit of reflection.” For Dewey, reflection is an act of reason that is often but not always directed to understanding the external world. He was also very willing to apply this objective rationality to more emotional concerns. “The meanings of honesty, sympathy, hatred, fear, must be grasped by having them presented in an individual’s first hand experience.” Applying Dewey’s imperative to modern technology design suggests that systems intended to help people reflect on emotions should do so from the context of the user’s own life experiences rather than from abstract concepts. Of course, emotions are just one category of things upon which one might introspect. There are at least three others.

Targets of Reflection
When we speak of self-awareness or reflection, there are various interpretations regarding what it is we are becoming aware of or upon which we are reflecting. Over time there have been proposals for various targets of reflective thought, which can roughly be synthesized into four main categories.

Cognitive awareness is what we believe we know about the world around us and our own lives. Understanding this aspect in ourselves is generally referred to as “metacognition,” a term introduced by John Flavell in the late 1970s (Flavell, 1979). A great deal of research on how to build computer systems to support metacognition is available in the learning technologies literature.

Affective awareness involves awareness of our states of mind, in particular moods and emotions. Strategies and computer tools that help us track and reflect on our moods and emotions have been developed in the areas of psychotherapy and affective computing and as commercial tools. Some of these tools are discussed later in this chapter.

Experiential awareness is our awareness of the integrated aspects of cognition, affect, and behavior (including their external and internal triggers). The combination of these three aspects of “experience” (cognition, affect, and behavior) is at the core of CBT, which we describe in more detail later in this chapter.

Character traits, or those aspects of personality that are dispositional qualities, are a fourth set of mental aspects upon which we can reflect. We won’t be focusing on this last category in this chapter because there is insufficient research to draw on at this stage. We delve more deeply into the cognitive, affective, and experiential in the next three sections.

Cognitive Awareness and Metacognition
Metacognitive skills, or the ability to “know what one knows,” are important to many aspects of life experience, from setting realistic personal targets to self-regulating learning activity. A number of researchers have explored metacognition in the context of designing intelligent tutoring systems. These systems can support learning by supporting metacognition—for example, encouraging self-explanation (as a way of scaffolding reflection) and setting personalized goals. In addition to using metacognition strategies as a feature, other systems have focused on developing metacognitive skills per se, based on the principles for metacognitive tutoring proposed by John R. Anderson and his colleagues (Anderson, Corbett, Koedinger, & Pelletier, 1995).

Outside of the learning context, researchers have considered the impact of metacognitive skills on mental health (particularly in the context of cognitive therapies), linking them to wellbeing. We come back to these examples later in the chapter.

Affective Awareness and Emotional Intelligence
The literature on emotional intelligence (EI) has focused on affective awareness—namely, the skills required to recognize and regulate our emotions in a way that is consistent with a model of emotional functioning (Mayer & Salovey, 1995). We discussed emotional intelligence in chapter 3, but it’s worth coming back to Daniel Goleman’s (1998) five EI skills because they provide a useful breakdown of affective awareness as it might contribute to wellbeing. The five EI skills are:

  * Self-awareness (the ability to recognize our own emotions)
  * Self-regulation (the ability to control them)
  * Motivation (passion for what we do)
  * Empathy (the ability to recognize others’ emotions, which is covered in depth in chapter 10)
  * Social skills, in particular the ability to manage relationships with others

Most of the research on EI links it to concrete measures of success, such as productivity in the workplace. Nevertheless, there is also some initial evidence for a link between EI and psychological wellbeing. For example, a number of studies have looked at how well EI predicts wellbeing as defined by standard SWB measures. Emma Gallagher and Dianne Vella-Brodrick (2008) analyzed the impact of EI on SWB, removing the effect of other factors such as personality and sociodemographic variables (e.g., wealth). They analyzed measures of life satisfaction, positive and negative affect, social support, EI, personality, and social desirability from the self-reports of 267 adults. Their analyses showed that EI and social support as well as their interaction effects significantly predicted SWB. Further research on these links would be helpful in demonstrating whether interventions to develop EI also increase wellbeing.

Experiential Awareness and Reflection
Perhaps the most promising strategies for reflection are those that target the holistic relationships between thoughts, feelings, and behaviors. The development of such understanding is at the core of some mindfulness practices and cognitive therapy, both of which have been empirically linked to wellbeing.

It’s worth pointing out the challenges of interdisciplinary research around a construct with as many varied interpretations as self-reflection. Each discipline looks at different aspects of reflection and takes a different focus. On the one hand, we might approach reflection, as Socrates, Dewey, and Peter Salovey have, as a retrospective dimension of thought. Even within this category approaches differ; Socrates’s point of departure was moral philosophy; Dewey’s interest was cognition and education; and other authors have studied reflection from the perspective of professional practice (e.g., Schön, 1983). In contrast, in mindfulness training and Buddhist psychology, reflection is generally rooted in the present. It is a present-moment self-awareness that observes thoughts, emotions, and behaviors as they arise, often in the context of deliberate contemplative practice.

The concept of reflection has been used in so many ways it risks becoming a bit of a catch-all. Therefore, in order for the concept to be useful to positive computing in a practical sense, it must first be contextualized. The adoption of any model of reflection for the development of technology will be shaped by (a) our motives for targeting reflection in the first place (What problem are we trying to solve? What activity are we trying to support?), (b) the development process we follow, and (c) the methods of evaluation we use.

By way of example, in the next section we discuss two contexts within which technologies can be (and have been) used to support reflection. The first is psychotherapy, in which reflecting on cognitive and behavioral patterns has been demonstrated to effect transformative experiences, especially for those with mental illness. In the second example, we discuss reflection at a more prosaic level and at a narrower granularity. We look at the practice of reflecting retrospectively on our daily behaviors, moods, and goals and at how new technologies, particularly in the area of personal informatics, can be used to collect behavioral data and scaffold the reflection process.

Reflection as a Strategy for Mental Health Treatment
Cognitive Behavioral Therapy

A number of psychotherapies focus on developing a self-understanding of the relationships between our thoughts, feelings, and behaviors. One of the most commonly used psychotherapies in the treatment of depression and anxiety is cognitive behavioral therapy. CBT was developed by Aaron T. Beck (Beck, Rush, Shaw, & Emery, 1987) and is closely related to rational emotive behavioral therapy developed by Albert Ellis (1973), both during the late 1950s. While Beck was treating patients using a psychoanalytic method, he began to notice how they, especially those with depression, often misinterpreted or had “cognitive distortions” relating to events in their lives. They would, for example, selectively obstruct certain thought processes or overgeneralize. For instance, a patient might interpret the fact that his spouse didn’t kiss him good-bye in the morning as evidence that he is no longer loved.

CBT is essentially based on the concept that the way we think influences the way we feel, which in turn influences the way we behave. This process, thinking–feeling–behaving, is part of an internal communication that people can access through reflection. The client can discover the meanings of such processes, in particular the triggers of irrational thinking and follow-up feelings, with the therapist’s help. The therapist often follows a Socratic questioning approach, scaffolding the client’s reflection so that he evaluates his assumptions and can modify his thinking. This systematic questioning (a.k.a. “talk therapy”) is combined with other activities such as role playing, writing in a diary, disputing irrational beliefs, and modifying language to be more positive, assertive, or playful.

Technology for CBT

Richard Layard, notable British economist and proponent of national wellbeing measures, has called on the UK government to invest both in increasing the provision of CBT and in teaching EI in schools in aid of improving national wellbeing. One strategy for increasing the reach of CBT programs in light of a shortage of trained therapists is through technology, and computers have already been successfully used to deliver such programs. In fact, computer-based CBT (CCBT) has been successful enough that in the United Kingdom the National Institute for Clinical Excellence considers Internet-delivered CBT a viable way of treating patients, in particular those with anxiety.

In a Health Technology Assessment for the UK National Health System, Eva Kaltenthaler and her colleagues (2006) compared the clinical and cost effectiveness of a number of online CBT products to traditional approaches. According to their analysis of 20 randomized controlled trial studies, there is evidence that CCBT is as effective as therapist CBT for the treatment of phobias and panic and is more cost effective for depression and anxiety. Moreover, using CCBT in conjunction with a therapist can reduce therapist time required.

It’s worth noting that we do not believe computers can reasonably replace human mental health professionals. Any such notion would reflect a lack of understanding regarding the complexity of mental illness and the mental health profession. We reject a people-replacement model of technology’s role in mental health, not only because of technology’s limited ability to be creative and empathic and to provide genuine human presence, but also because technology-based programs are largely generalized, incapable of making critical insights or adapting sufficiently to the nuance and variety in human personalities and circumstances. As such, technological systems are probably incapable of safely assisting with nontextbook, long-term, and life-threatening cases. Nevertheless, for certain types of mental health challenges, they could contribute significant help in, at least, the following four ways:

  * As complement to therapist treatment for a richer, more consistent, and possibly shorter treatment phase
  * As follow-up and maintenance after therapist sessions are complete
  * As triage where a shortage of qualified mental health professionals face far more people in need of help than can possibly be seen in one-on-one, hour-long sessions. Technology might be used to support more mild cases, while immediately directing those who may be in danger to professional help.
  * As a wider net for the many people who, although they are in need of professional help, do not seek it for many reasons such as stigma, fear, cost, and logistics. The anonymity and easy access provided by online programs can potentially foster flourishing in a much larger number of people. Some of these people may even proceed to seeking professional help once transitioned by such a process. Others may find the online program in itself successful in improving their lives.

To these ends, initial research is promising. In an Australian evaluation of a CCBT system (Mackinnon, Griffiths, & Christensen, 2008), three conditions were explored: the use of MoodGym, an Internet-based CBT intervention; the use of Bluepages, a website with information; and a control placebo group. Results showed that the Internet interventions reduced depression symptoms to a greater extent than the control group. This was true for a post-test, the 6-month follow-up, and a 12-month follow-up.

A UK randomized controlled trial of the efficacy of CCBT (Proudfoot, Ryden, Shapiro, Goldberg, & Gray, 2004) showed even stronger outcomes. The authors compared a commercial multimedia CCBT system (Beating the Blues1) with traditional treatment and found that “the computerised therapy improved depression, negative attributional style, work and social adjustment. … For anxiety and positive attributional style, treatment interacted with severity such that computerised therapy did better than usual treatment for more disturbed patients. Computerised therapy also led to greater satisfaction with treatment.”

These computer-based systems are exceptions in that they have been evaluated in peer-reviewed studies. Hundreds of other CCBT apps, many available for a few dollars at the app store, do not have the benefit of such evaluations. Most tend to be augmented diaries, providing users with a way to record events. Thoughts pertaining to these events can sometimes be labeled—for example, as “unhelpful” or “sad.” Other apps focus on specific activities (e.g., sleep, diet, and drinking).

For example, Drink Coach is an app developed by the Haringey Advisory Group on Alcohol, a UK group supporting those who suffer from alcohol misuse. The app focuses on scaffolding reflection on drinking habits. The user can record her alcohol consumption and the “risks” associated with it as well as set goals. The system tracks alcohol units and related calories consumed over time, and diary entries include fields for craving duration and intensity. The app also provides videos about mindfulness and breathing exercises that can help with cravings.

Panic Attacks is an app produced by myCBT Ltd. that focuses on anxiety disorders. It provides audio recordings designed to be calming, information on panic attacks, and a diary that helps challenge misinterpretations.

We hope to see more research and rigorous evaluation of these kinds of apps in the future so that we all can learn more about how best to design this kind of support.

Technology-Mediated Reflection for Wellbeing
The examples of CCBT in the previous section deal with mental health treatment. However, the focus of positive computing is mental health promotion. Of course, we have elected to spend significant time describing these e-therapy approaches in part because they are some of the most sophisticated and well-evaluated examples of technologies directed at psychological functioning that exist today, but also because you don’t have to be ill to benefit from them. For example, it is not only the clinically depressed that find themselves having irrational thoughts, making overgeneralizations, or “catastrophizing.” Most of us are prone to the kind of mental habits that in larger amounts and combined with other symptoms characterize clinical anxiety and depression. Even those of us who are mentally healthy can thus benefit from the exercises and practice of detecting cognitive distortions. Reducing these habits in the general population can be seen not only as a preventative measure that builds resilience to illness, but also as a promotional measure that improves the level of wellbeing in the population overall.

If we look at the taxonomy of Internet-based medical interventions (Barak, Klein, & Proudfoot, 2009), it’s interesting to imagine how many of these interventions might be reformulated as promotional (rather than therapeutic) strategies. Moreover, how many of them might be incorporated into the very tools we already use in our everyday activities? Although the notion of promotional strategies incorporated into everyday software remains somewhat forward thinking, there are a handful of examples of dedicated promotional tools. Among them is Echo.

Echo is a smartphone application for recording everyday experiences and reflecting on them afterward, created in collaboration by researchers in California (Isaacs, Konrad, Walendowski, & Lennig, 2013). They conducted three system deployments with 44 users who generated more than 12,000 recordings and reflections, and they found that the activity supported by the system (which they call “technology-mediated reflection”) successfully improved wellbeing. This study is instructive not only because it demonstrates an effective design for supporting reflection to promote wellbeing, but also because it serves as a model for rigorous evaluation of positive-computing technologies. The research team assessed results using four separate psychological metrics: the Subjective Happiness Scale, Satisfaction with Life Scale, Psychological General Well-Being Index, and the Mindfulness Attention Awareness Scale.

Echo is just one example of the ways in which many of the exercises that a therapist would use are translatable to online delivery. For example, role-playing (think videogames), writing reflections (as with Echo and writing tools that we analyze in the next section), disputing irrational beliefs (for example, by scaffolding the reasoning process online), and modifying language (Could we have a positive-computing spell checker for reflective practice?) are all therapeutic strategies amenable to technology support. Clearly, there is much room for innovation in this area, and we look forward to future examples of technologies for the treatment, prevention, and promotion of mental health.

Reflection versus Direct Instruction
Reflective approaches to self-improvement are particularly appropriate for technology intervention in that they avoid the path of giving direct prescriptive instruction, which is a risky approach for any generalized tool to take. Moreover, reflective feedback has greater potential in situations where a client’s full story and context are not clear, which is almost always the case online.

In one of the sidebars in chapter 3, Harvard social media scholar danah boyd describes the digital street—a poignant reminder of how public our lives are and the difficult considerations that have arisen around this new reality. The lives we see in these digital streets are visible only in fragments. Even when we want to put these fragments to good use—for example, by identifying people at risk in order to point them in the right direction for help—our task is not trivial because we remain unaware of the full context of their situation. In these instances, reflective interventions, where a person is (a) encouraged to contextualize issues for themselves, (b) provided with information upon which to reflect, and (c) not given direct advice to take a specific action, may pose the best solution.

In a project with the Young and Well Cooperative Research Centre, we currently are exploring how a computer could automatically detect cognitive distortions in what young people write in blogs and on social networks. Using natural-language processing, we hope to detect expressions of all-or-nothing thinking, overgeneralization, discounting the positive, and jumping to conclusions. Technologies that can recognize cognitive distortions might form the foundation for tools that help people recognize these distortions for themselves. Needless to say, the careful design of these tools will be critical. No one, least of all teenagers, wants a virtual agent telling them what he should or shouldn’t post on his wall. But creatively and respectfully applied, with deference to autonomy, values, participation, and preferences, such technologies just might promote greater wellbeing on unprecedented scale.

Reflection for Wellness and Wellbeing—Quantifying the Self
Personal informatics, personal analytics, quantified self, self-tracking—these are all terms that refer to technologies used by individuals to collect and analyze data about their behaviors (and sometimes about their moods or emotions).

The area has grown on multiple fronts in both business and academia. Independent software developers and entrepreneurs can take credit for the impressive speed at which it has advanced. Take Buster Benson—a software developer in California and a pioneering example of a user/developer combo who has immersed himself with gusto into the world of quantified self. Benson has been quantifying himself since 2000.2 In one of his earliest forays, he tracked his state of mind using a “mood-o-meter,” a system he used to log and publish information about his morale, his health, and his sleep in concert with data on his alcohol and caffeine consumption. Using this application, he would rate these variables on a scale of 1 to 10, describe the day’s events in a short diary entry, and produce plots and visualizations for him and others to view.

He points out that others found the visualizations valuable because they could better judge when to approach him to ask for a favor, and he found himself paying attention to the way in which he was perceived by others. Over the years he has built and often commercialized many more personal informatics tools. His quest, he says, is “to find meaning,” and he carries out this quest by exploring data.

On another leg of the quest, after beginning a personal diary in order to track how his moods changed over time, he created the website 750words.com. The website is similar to a blog but differs in its constraints and purpose. It has a much simpler interface, limits posts to 750 words, and is designed to produce reports from these personal journal entries. A simple report might read, “Rafael Calvo started at 7:10 pm and finished 470 words at 7:57 pm, for a total of 47 minutes of typing at 10 words per minute. Rafael Calvo was distracted 4 times while writing.” Benson integrates the information from this tool with photo streams, geomapping, emotional state tracking, the number of unresponded emails he has sitting in his inbox, tweets received, and myriad other data streams to produce an unusually detailed public portrait of his personal life.3

In a recent seminar, Benson shared his conflicting opinions of self-tracking, sometimes viewing it simply as compulsive behavior, sometimes finding meaning in the data, and sometimes finding that although there is meaning in it, it’s “hundreds of years away.”4 He also found that after years of trying to find numbers that better match to his internal reality, more generic labels (or Boolean scores) seem best suited to the job. In one of his apps, he uses factors such as sleep, physical activity, meaningful work, time spent with his son, and so on to produce a single average measure.

Although Benson’s personal voyage isn’t scientific research, it is instructive. The experiences of people such as Benson who have been “quantifying themselves” for such long periods of time can provide useful insights in the way that diary and case study methods have been successfully used in HCI research. Sure, his concern for privacy is clearly lower than average, or perhaps he’s simply courageous in the name of computer science, but the result is an intriguing public experiment (performance artwork, even) that anyone can explore in order to reflect on the potential benefits, risks, limitations, inanity, or promise of the thoroughly quantified life.

Together with people like Benson, entrepreneurs and developers are putting together all kinds of apps that help people reflect on their behaviors in light of data collected about almost any aspect of their lives. At the website PersonalInformatics.org, you can find a catalog with hundreds of applications, from those for diet and exercise to those for tracking your sex life.

Some developers integrate GPS data into applications that calculate running or cycling itineraries, distance benchmarks, speed, and approximate calories burned. Some companies add a website or a custom gadget to the mix. The gadget-based business model pertains to some of the most commercially successful products, such as those offered by Fitbit (in March 2013 valued at more than $300 million).

Possibly the most significant personal tracking experiences are occurring online, where people view visualizations, interact with gamified motivational features, and share data and goals with others. In our lab, we are currently developing a set of tools that combine observational data (e.g., from health gadgets and traffic logs) with self-reported data (e.g., responses to a CES-D questionnaire or other psychological instruments), aiming for a more holistic view.

Reflection will continue to play a central role in our technology- supported efforts in supporting self-awareness. However, relentless in our determination not to neglect the caveats, we know this chapter would not be complete without the case against too much reflection as a method for self-awareness to improve wellbeing.

Staring at Our Own Reflection
Can self-awareness (or at least reflection) go too far? When does healthy reflection become unhealthy rumination or obsessive self-focus? Will encouraging reflection simply feed the apparent rising trend in narcissism that is also linked to depression? Should we encourage self-focus when self-focus is known to be a conspicuous characteristic of depression? In a linguistic analysis of student essays, Stephanie Rude, Eva-Maria Gortner, and James Pennebaker (2004) found that depressed individuals used the word I more frequently than did their nondepressed counterparts.

These issues highlight the challenges inherent in supporting the “right kind” and “right amount” of reflection. As a way forward, we summarize some of the elucidating research on self-compassion and gratitude, potential antidotes to the risks of overreflection.

Rumination and Self-Criticism

Sonja Lyubomirsky, among many other psychologists, has studied rumination and its impact on depression, problem-solving ability, and sociability. While comparing people who tend to be happier with those who tend to be unhappier to the average, positive-psychology researchers have found a link between unhappiness and too much self-reflection, including “dwelling” (or rumination) and self-criticism. According to Lyubomirsky’s (2001) research, happier people tend to self-reflect about moods and outcomes less than unhappier people.

Rumination, in which thinking is mostly about past events (rather than the worrisome future), tends to focus on issues of loss and bereavement, self-worth, and so on. Myriad studies have consistently shown that rumination is associated with depression and other mental health problems and that focusing attention on oneself can also increase and extend the length of depressive episodes. In the article “Rethinking Rumination” (Nolen-Hoeksema, Wisco, & Lyubomirsky, 2008), the authors explain how rumination is not just correlated with neuroticism, perfectionism, and other negative cognitive styles but also mediates “the relationship between depression, neuroticism, negative inferential styles, dysfunctional attitudes, self-criticism, dependency and neediness.”

However, according to this same article, it is also not clear which forms of self-reflection can be adaptive, positive, and instrumental in personal change or even just benign. Some researchers have tried to separate factors using the Ruminative Responses Scale and other scales in attempts to disentangle positive forms of reflection from otherwise negative rumination. Evidence suggests a difference between analytic and experiential self-focus (Watkins & Teasdale, 2004), the latter relating to the nonjudgmental present-focused observation found in mindfulness practice or what Susan Nolen-Hoeksema and her colleagues (2008) call “concrete rumination” or “mindful experiencing.” (We discuss mindfulness in the next chapter.)

This is perhaps why the generally present-focused and experiential process of self-reporting moods seems to increase emotional self-awareness, an important positive aspect of a number of psychotherapies. The positive impact of self-reports has been shown in studies where participants reported their moods via phone messages (Kaur et al., 2012) or as longer personal diary entries such as blogs (Ko & Kuo, 2009). Interestingly, the evidence suggests that mobile phone self-reports can help reduce the brooding component of rumination (which is the component with strongest correlation to depression) (Kaur et al., 2012).

Future research in positive computing can look at how technologies might be designed in such a way to detect signs of overthinking, brooding, or self-criticism and perhaps to shift focus to supporting antidotal practices such as mindfulness, connection to others, and change of perspective.

Self-Awareness versus Narcissism

Sometimes the barrage of inane status updates, blathering blogs, and twittering tweets conspire to create a cognitive and emotional cacophony that have driven many to one conclusion: the connected world is raising a Generation Me that believes everything they think and do is important and worthy of public display. These new tools begin to look less like they’re about connecting and more like they’re about performing.

To be fair, experimentation with any new tool will involve doing so clumsily at first. And certainly, we have already begun to adjust the way we use social media in light of these effects—for example, by filtering more, storing less, demanding finer privacy settings, and reporting spam. Western capitalist culture, especially in the United States, is frequently criticized for an overfocus on individualism, self-interest, and an overemphasis on self-esteem. A recent New York Times article reported that “Rutgers researchers classify 80 percent of Twitter users as ‘meformers’ who tweet mainly about themselves” (Tierney, 2013). Will tools for self-awareness and self-tracking simply reinforce this pattern, leading to a new wave of digital selfing?

Indeed, there’s compelling evidence that both narcissism and narcissistic personality disorder have increased among younger generations in the United States (Twenge & Foster, 2010; Twenge, Konrath, Foster, Campbell, & Bushman, 2008). This downside comes, perhaps predictably, on the tail of more positive increases of other individualistic traits such as self-esteem, agency, assertiveness, and extraversion. Of course, you could say that previous generations had personal experience with economic depression, world war, and civil rights battles, which probably did more to temper a sense of entitlement than microblogging and personal digital devices do. But the meta-analyses look at levels of narcissism among college students from the early 1980s to the present day, not among their grandparents. Although the causes are surely various (from changes in education to cultural attitudes, politics, and lifestyles—all potentially playing a part), if we speculate that our digital technologies (or perhaps, more accurately, the ways we have designed and used them thus far) are playing some role in increasing levels of narcissism (and even if they’re not to blame), it’s sensible to ask what we can do about it in the context of positive computing. Contemporary researchers such as Paul Gilbert and Kristin Neff are among those who have spent the past decade investigating the potential of self-compassion to provide a more balanced way forward. While self-compassion might at first blush sound like just another “selfism,” it critically incorporates a broader perspective and a sense of shared humanity that, combined with gratitude, may be a key strategy for keeping reflection in balance.

Self-Esteem versus Self-Compassion
If you grew up with Barney the purple dinosaur, you’ll remember the theme song: “Cause you are special, special, everyone is special, everyone in his or her own way. …” Dorian recalls her father scoffing cynically at the oxymoronic notion that everyone is special. Of course, growing up in a working-class family on the rural outskirts of Pittsburgh meant that if you wanted to feel special, you had to work for it. We now know young children benefit greatly from praise, encouragement, and affirmation of their competence and potential, which is why research on self-esteem has been incredibly important to the way educational institutions now prepare children for success in life. Still, according to some, there has been a downside to the approaches we’ve taken to boosting self-esteem. Described charmingly as the “Lake Woebegone Effect” (in reference to radio personality Garrison Keillor’s fictional hometown, where “all women are strong, all men are good-looking, and all children are above average”), researchers have found that self-esteem that is contingent on external achievement or dependent on proof of perpetual above-averageness can lead to depression or narcissism down the track.

Psychologist Kristin Neff (2011) at the University of Texas, Austin, draws attention to the American obsession with needing to be above average. “In our incredibly competitive society, being average is unacceptable. We have to be special and above average to feel we have any worth at all. The problem, of course, is that it is impossible for everyone to be above average at the same time.” She cites research that shows how we struggle to maintain the fragile sense of specialness required for our self-esteem by inflating our self-evaluations and putting others down to feel superior. It’s hard not to think of all the “reality” TV shows and gossip magazines that in their condescending parade of the sensational sell us the opportunity to feel superior to others.

Neff goes on to unravel the consequences of a societal love affair with self-esteem, referencing grade inflation and the problems with a construct that is frequently contingent on external measures such as appearance, academic achievement, work performance, and social approval. “Contingent self-esteem drives people to obsess about the implications of negative events for self-worth, making them more vulnerable to depression and reduced self-concept clarity.” Although she emphasizes that there are certainly healthy forms of self-esteem and there is much research linking self-esteem to wellbeing, she argues that these benefits can be found without the downsides in a notion of self-compassion.

Paul Gilbert (2009, 2010) introduced compassion-focused therapy in the past decade as a novel way to help people who suffer from high levels of shame and self-criticism. The concept of self-compassion may be new to Western psychology, but it is certainly not new to humanity. Gilbert credits Buddhist psychology as a source for compassion-focused therapy because it centers on compassion in its practice (Buddhist loving-kindness meditation begins with compassion for oneself).

According to Neff (2011), “self-compassion entails three main components which overlap and mutually interact: Self-kindness versus self- judgment, feelings of common humanity versus isolation, and mindfulness versus over-identification.” Self-compassion has been correlated to increased wellbeing in multiple ways. It has also been shown to be a highly effective predictor of quality of life (Van Dam, Sheppard, Forsyth, & Earleywine, 2011) and has been correlated to other aspects of interest to positive-computing work, such as increased self-improvement motivation and reduced risk of Internet addiction. Laura Bernard and John Curry (2011) provide a summary of wellbeing correlates and suggest intervention strategies that could begin to inspire work in positive computing.

Gratitude and Appreciation

For a final antidote to over-focus on the self, and one that also fosters wellbeing in its own right, we turn to gratitude. The practice of gratitude in various forms (from thank-you letters to gratitude journals) has consistently been shown to increase wellbeing (for reviews see: Emmons & McCullough, 2004; Watkins, Woodward, Stone, & Kolts, 2003; Wood, Froh, & Geraghty, 2010). Christine Carter (2011), Director of Berkeley’s Greater Good Science Center, recommends gratitude practice for curbing a sense of entitlement in our children as well as for fostering positive relationships: “Our culture glorifies independence and undervalues how much others help; we see our blessings as hard earned … appreciation is one of the most important ways that we teach our kids to form strong relationships with others … expressing gratitude is about expressing just how deep those connections run.”

Design for gratitude already makes a few appearances in the virtual world. There are apps available to support gratitude practices (such as gratitude journals), games occasionally include opportunities for gratitude (e.g., Hay Day allows players to send thank you cards when help is provided by other players in the game), and the Learning Solutions website transformed the ubiquitous “like” into the more gratitude-focused “I appreciate this.” Creative thinking around how we can support users in experiencing and extending acts of gratitude and appreciation will be a rewarding area of ongoing exploratory practice and one that can contribute positively to wellbeing.

A Way Forward

Tracking and sharing personal data can encourage us to compare ourselves to others, yet the research on happiness and self-compassion show that this can negatively impact our wellbeing. Reflecting on our thoughts, emotions, and behaviors is essential to personal growth, but obsessive rumination contributes to depression. How do we design technologies that support practices beneficial to wellbeing without reinforcing associated problems? We do not claim to have the answer, but we suggest the following design principles as safeguards in favor of healthy balance.

Design Implications
Principles for Supporting Self-Awareness and Reflection

  * Understand the pitfalls. Cultivating an awareness and understanding of the pitfalls that exist surrounding reflection and self-tracking will help us (designers) to avoid inadvertently supporting them.
  * Design for self-compassion, gratitude, and mindfulness. Research suggests that underscoring our efforts with principles of self-compassion, gratitude, and mindfulness will help prevent comparison, self-criticism, narcissism, and entitlement.
  * Acknowledge the limitations of technology and lean toward reflective support. Honoring the diversity and complexity of people while acknowledging the limitations of what can be provided by technology will often mean employing reflective feedback and avoiding highly prescriptive and constrained solutions. Outside of human-mediated medical intervention, what we don’t know about our users and their contexts will always outstrip what we do know, so providing them feedback for making better decisions will often be more widely effective than providing specific instruction.
  * Allow for nonabsolute categories. When we present the analysis of personal data to support inferences about states of mind or behavior, we should not be constrained to predefined categories. This idea is based on the work by Ellen Langer, who showed the negative impact of preconceptions on creativity. In her studies, Langer (e.g., Langer & Piper, 1987) provided evidence that when people come to a task with strong, absolute conceptions, for example when they are told, “This is a %___%,” in contrast to a conditional conception, as when they are told, “This could be a %___%,” they are much less likely to adapt or be creative with the concept.

Follow the Ongoing Research

Although better understanding of how we can design safeguards and adaptations to ensure that wellbeing interventions genuinely promote wellbeing will require ongoing research, understanding that these tensions exist and following research in antidotal concepts such as self-compassion, gratitude, altruism, and sympathetic joy are sure to be critical to approaching an optimal balance over time.

And now, after alluding a number of times to the incredible promise of mindfulness for wellbeing, we turn to this unique state and practice in the next chapter—to its definition, its many positive correlates, and the strategies that have been proven to promote it.
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====== 8 Self-Awareness and Self-Compassion ======
It was late in his life, as he faced his executioners, that one of the world’s greatest thinkers would conclude that death was preferable to giving up philosophy. To those in his midst he declared simply: “The unexamined life is not worth living.” Socrates would go on to swallow hemlock for his crimes—crimes that would come to represent a pinnacle of human achievement.

A century earlier ancient India had yielded another of the world’s greatest philosophers, Gautama Buddha, who said “You are what you think. All that you are arises from your thoughts. With your thoughts you make your world.” The core Buddhist tenet summarized by the Four Noble Truths explains that in order to end our experience of suffering, we must first understand the workings of our mind. We must be able to recognize our thoughts, our emotions, our reactions, and their precursors, as they are the roots of our suffering.

Methods for self-examination, introspection, and self-awareness have since been refined by generations of philosophers, and more recently by modern Western psychologists from Sigmund Freud to Aaron Beck.

Now, in the second decade of the twenty-first century, cognitive behavioral therapy (CBT) has gone online: experience sampling solicits mood updates via smart phone, and the quantified-self movement inspires growing innovation in personal data analysis. But is it reasonable to expect any deeper understanding of our personal thoughts and emotions to arise from data? Can artificial intelligence, sophisticated machine-learning algorithms, and digital visualizations really help us to know ourselves better? If they did, would we be better for it?

In this chapter, we look at the state of the art in technology-mediated reflection, the varied approaches that have been applied to this endeavor, and the research emerging from its use. We also look at the foundations in psychology that underpin efforts toward greater self-awareness and how they are linked to increases in wellbeing. We look at both the potentials and the problems that may be associated with technological intervention into our inner lives, while deliberately evading the question, Would the Buddha have tweeted “feeling one with the universe” from under the Bodhi Tree?

Know Thyself
Why bother? Is self-knowledge merely philosophically virtuous or actually important to greater happiness and flourishing? Methods for CBT demonstrate that increased self-awareness can indeed improve wellbeing. In fact, a healthy chunk of the research and clinical work in modern psychology relies on promoting awareness of one’s thoughts, emotions, and behaviors in order to effectively treat mental illnesses such as anxiety and depression.

Neuroscientist Richard Davidson (e.g., Davidson & Begley, 2012) has identified recognizable neurophysiological patterns associated with self-awareness. He has found that greater self-awareness is associated with increased activity in the insula (involved in consciousness, emotion, and body regulation) and that long-time meditators have larger insulas.

If self-awareness is important to personal growth and wellbeing, what can we do to develop it, and how can technology play a part in that development? The answer is most frequently sought in various forms of reflection, introspection, and mindfulness training. There is an impressive wealth of evidence for the effectiveness of mindfulness practice on wellbeing, including the work of Jon Kabat-Zinn and researchers at the Oxford Mindfulness Centre. Davidson cites neurophysiological evidence for the effectiveness of mindfulness practice both for increasing self-awareness and for tempering potential negative side effects that might accompany this awareness (e.g., hypersensitivity and anxiety). We reserve mindfulness, however, for the next chapter and deal with it as a factor of wellbeing in its own right. In this chapter, we focus on reflection.

According to twentieth-century philosopher, psychologist, and educational reformer John Dewey (2013), it is essential for education to develop the skills of reflection: “while we cannot learn or be taught to think, we do have to learn to think well, especially acquire the general habit of reflection.” For Dewey, reflection is an act of reason that is often but not always directed to understanding the external world. He was also very willing to apply this objective rationality to more emotional concerns. “The meanings of honesty, sympathy, hatred, fear, must be grasped by having them presented in an individual’s first hand experience.” Applying Dewey’s imperative to modern technology design suggests that systems intended to help people reflect on emotions should do so from the context of the user’s own life experiences rather than from abstract concepts. Of course, emotions are just one category of things upon which one might introspect. There are at least three others.

Targets of Reflection
When we speak of self-awareness or reflection, there are various interpretations regarding what it is we are becoming aware of or upon which we are reflecting. Over time there have been proposals for various targets of reflective thought, which can roughly be synthesized into four main categories.

Cognitive awareness is what we believe we know about the world around us and our own lives. Understanding this aspect in ourselves is generally referred to as “metacognition,” a term introduced by John Flavell in the late 1970s (Flavell, 1979). A great deal of research on how to build computer systems to support metacognition is available in the learning technologies literature.

Affective awareness involves awareness of our states of mind, in particular moods and emotions. Strategies and computer tools that help us track and reflect on our moods and emotions have been developed in the areas of psychotherapy and affective computing and as commercial tools. Some of these tools are discussed later in this chapter.

Experiential awareness is our awareness of the integrated aspects of cognition, affect, and behavior (including their external and internal triggers). The combination of these three aspects of “experience” (cognition, affect, and behavior) is at the core of CBT, which we describe in more detail later in this chapter.

Character traits, or those aspects of personality that are dispositional qualities, are a fourth set of mental aspects upon which we can reflect. We won’t be focusing on this last category in this chapter because there is insufficient research to draw on at this stage. We delve more deeply into the cognitive, affective, and experiential in the next three sections.

Cognitive Awareness and Metacognition
Metacognitive skills, or the ability to “know what one knows,” are important to many aspects of life experience, from setting realistic personal targets to self-regulating learning activity. A number of researchers have explored metacognition in the context of designing intelligent tutoring systems. These systems can support learning by supporting metacognition—for example, encouraging self-explanation (as a way of scaffolding reflection) and setting personalized goals. In addition to using metacognition strategies as a feature, other systems have focused on developing metacognitive skills per se, based on the principles for metacognitive tutoring proposed by John R. Anderson and his colleagues (Anderson, Corbett, Koedinger, & Pelletier, 1995).

Outside of the learning context, researchers have considered the impact of metacognitive skills on mental health (particularly in the context of cognitive therapies), linking them to wellbeing. We come back to these examples later in the chapter.

Affective Awareness and Emotional Intelligence
The literature on emotional intelligence (EI) has focused on affective awareness—namely, the skills required to recognize and regulate our emotions in a way that is consistent with a model of emotional functioning (Mayer & Salovey, 1995). We discussed emotional intelligence in chapter 3, but it’s worth coming back to Daniel Goleman’s (1998) five EI skills because they provide a useful breakdown of affective awareness as it might contribute to wellbeing. The five EI skills are:

  * Self-awareness (the ability to recognize our own emotions)
  * Self-regulation (the ability to control them)
  * Motivation (passion for what we do)
  * Empathy (the ability to recognize others’ emotions, which is covered in depth in chapter 10)
  * Social skills, in particular the ability to manage relationships with others

Most of the research on EI links it to concrete measures of success, such as productivity in the workplace. Nevertheless, there is also some initial evidence for a link between EI and psychological wellbeing. For example, a number of studies have looked at how well EI predicts wellbeing as defined by standard SWB measures. Emma Gallagher and Dianne Vella-Brodrick (2008) analyzed the impact of EI on SWB, removing the effect of other factors such as personality and sociodemographic variables (e.g., wealth). They analyzed measures of life satisfaction, positive and negative affect, social support, EI, personality, and social desirability from the self-reports of 267 adults. Their analyses showed that EI and social support as well as their interaction effects significantly predicted SWB. Further research on these links would be helpful in demonstrating whether interventions to develop EI also increase wellbeing.

Experiential Awareness and Reflection
Perhaps the most promising strategies for reflection are those that target the holistic relationships between thoughts, feelings, and behaviors. The development of such understanding is at the core of some mindfulness practices and cognitive therapy, both of which have been empirically linked to wellbeing.

It’s worth pointing out the challenges of interdisciplinary research around a construct with as many varied interpretations as self-reflection. Each discipline looks at different aspects of reflection and takes a different focus. On the one hand, we might approach reflection, as Socrates, Dewey, and Peter Salovey have, as a retrospective dimension of thought. Even within this category approaches differ; Socrates’s point of departure was moral philosophy; Dewey’s interest was cognition and education; and other authors have studied reflection from the perspective of professional practice (e.g., Schön, 1983). In contrast, in mindfulness training and Buddhist psychology, reflection is generally rooted in the present. It is a present-moment self-awareness that observes thoughts, emotions, and behaviors as they arise, often in the context of deliberate contemplative practice.

The concept of reflection has been used in so many ways it risks becoming a bit of a catch-all. Therefore, in order for the concept to be useful to positive computing in a practical sense, it must first be contextualized. The adoption of any model of reflection for the development of technology will be shaped by (a) our motives for targeting reflection in the first place (What problem are we trying to solve? What activity are we trying to support?), (b) the development process we follow, and (c) the methods of evaluation we use.

By way of example, in the next section we discuss two contexts within which technologies can be (and have been) used to support reflection. The first is psychotherapy, in which reflecting on cognitive and behavioral patterns has been demonstrated to effect transformative experiences, especially for those with mental illness. In the second example, we discuss reflection at a more prosaic level and at a narrower granularity. We look at the practice of reflecting retrospectively on our daily behaviors, moods, and goals and at how new technologies, particularly in the area of personal informatics, can be used to collect behavioral data and scaffold the reflection process.

Reflection as a Strategy for Mental Health Treatment
Cognitive Behavioral Therapy

A number of psychotherapies focus on developing a self-understanding of the relationships between our thoughts, feelings, and behaviors. One of the most commonly used psychotherapies in the treatment of depression and anxiety is cognitive behavioral therapy. CBT was developed by Aaron T. Beck (Beck, Rush, Shaw, & Emery, 1987) and is closely related to rational emotive behavioral therapy developed by Albert Ellis (1973), both during the late 1950s. While Beck was treating patients using a psychoanalytic method, he began to notice how they, especially those with depression, often misinterpreted or had “cognitive distortions” relating to events in their lives. They would, for example, selectively obstruct certain thought processes or overgeneralize. For instance, a patient might interpret the fact that his spouse didn’t kiss him good-bye in the morning as evidence that he is no longer loved.

CBT is essentially based on the concept that the way we think influences the way we feel, which in turn influences the way we behave. This process, thinking–feeling–behaving, is part of an internal communication that people can access through reflection. The client can discover the meanings of such processes, in particular the triggers of irrational thinking and follow-up feelings, with the therapist’s help. The therapist often follows a Socratic questioning approach, scaffolding the client’s reflection so that he evaluates his assumptions and can modify his thinking. This systematic questioning (a.k.a. “talk therapy”) is combined with other activities such as role playing, writing in a diary, disputing irrational beliefs, and modifying language to be more positive, assertive, or playful.

Technology for CBT

Richard Layard, notable British economist and proponent of national wellbeing measures, has called on the UK government to invest both in increasing the provision of CBT and in teaching EI in schools in aid of improving national wellbeing. One strategy for increasing the reach of CBT programs in light of a shortage of trained therapists is through technology, and computers have already been successfully used to deliver such programs. In fact, computer-based CBT (CCBT) has been successful enough that in the United Kingdom the National Institute for Clinical Excellence considers Internet-delivered CBT a viable way of treating patients, in particular those with anxiety.

In a Health Technology Assessment for the UK National Health System, Eva Kaltenthaler and her colleagues (2006) compared the clinical and cost effectiveness of a number of online CBT products to traditional approaches. According to their analysis of 20 randomized controlled trial studies, there is evidence that CCBT is as effective as therapist CBT for the treatment of phobias and panic and is more cost effective for depression and anxiety. Moreover, using CCBT in conjunction with a therapist can reduce therapist time required.

It’s worth noting that we do not believe computers can reasonably replace human mental health professionals. Any such notion would reflect a lack of understanding regarding the complexity of mental illness and the mental health profession. We reject a people-replacement model of technology’s role in mental health, not only because of technology’s limited ability to be creative and empathic and to provide genuine human presence, but also because technology-based programs are largely generalized, incapable of making critical insights or adapting sufficiently to the nuance and variety in human personalities and circumstances. As such, technological systems are probably incapable of safely assisting with nontextbook, long-term, and life-threatening cases. Nevertheless, for certain types of mental health challenges, they could contribute significant help in, at least, the following four ways:

  * As complement to therapist treatment for a richer, more consistent, and possibly shorter treatment phase
  * As follow-up and maintenance after therapist sessions are complete
  * As triage where a shortage of qualified mental health professionals face far more people in need of help than can possibly be seen in one-on-one, hour-long sessions. Technology might be used to support more mild cases, while immediately directing those who may be in danger to professional help.
  * As a wider net for the many people who, although they are in need of professional help, do not seek it for many reasons such as stigma, fear, cost, and logistics. The anonymity and easy access provided by online programs can potentially foster flourishing in a much larger number of people. Some of these people may even proceed to seeking professional help once transitioned by such a process. Others may find the online program in itself successful in improving their lives.

To these ends, initial research is promising. In an Australian evaluation of a CCBT system (Mackinnon, Griffiths, & Christensen, 2008), three conditions were explored: the use of MoodGym, an Internet-based CBT intervention; the use of Bluepages, a website with information; and a control placebo group. Results showed that the Internet interventions reduced depression symptoms to a greater extent than the control group. This was true for a post-test, the 6-month follow-up, and a 12-month follow-up.

A UK randomized controlled trial of the efficacy of CCBT (Proudfoot, Ryden, Shapiro, Goldberg, & Gray, 2004) showed even stronger outcomes. The authors compared a commercial multimedia CCBT system (Beating the Blues1) with traditional treatment and found that “the computerised therapy improved depression, negative attributional style, work and social adjustment. … For anxiety and positive attributional style, treatment interacted with severity such that computerised therapy did better than usual treatment for more disturbed patients. Computerised therapy also led to greater satisfaction with treatment.”

These computer-based systems are exceptions in that they have been evaluated in peer-reviewed studies. Hundreds of other CCBT apps, many available for a few dollars at the app store, do not have the benefit of such evaluations. Most tend to be augmented diaries, providing users with a way to record events. Thoughts pertaining to these events can sometimes be labeled—for example, as “unhelpful” or “sad.” Other apps focus on specific activities (e.g., sleep, diet, and drinking).

For example, Drink Coach is an app developed by the Haringey Advisory Group on Alcohol, a UK group supporting those who suffer from alcohol misuse. The app focuses on scaffolding reflection on drinking habits. The user can record her alcohol consumption and the “risks” associated with it as well as set goals. The system tracks alcohol units and related calories consumed over time, and diary entries include fields for craving duration and intensity. The app also provides videos about mindfulness and breathing exercises that can help with cravings.

Panic Attacks is an app produced by myCBT Ltd. that focuses on anxiety disorders. It provides audio recordings designed to be calming, information on panic attacks, and a diary that helps challenge misinterpretations.

We hope to see more research and rigorous evaluation of these kinds of apps in the future so that we all can learn more about how best to design this kind of support.

Technology-Mediated Reflection for Wellbeing
The examples of CCBT in the previous section deal with mental health treatment. However, the focus of positive computing is mental health promotion. Of course, we have elected to spend significant time describing these e-therapy approaches in part because they are some of the most sophisticated and well-evaluated examples of technologies directed at psychological functioning that exist today, but also because you don’t have to be ill to benefit from them. For example, it is not only the clinically depressed that find themselves having irrational thoughts, making overgeneralizations, or “catastrophizing.” Most of us are prone to the kind of mental habits that in larger amounts and combined with other symptoms characterize clinical anxiety and depression. Even those of us who are mentally healthy can thus benefit from the exercises and practice of detecting cognitive distortions. Reducing these habits in the general population can be seen not only as a preventative measure that builds resilience to illness, but also as a promotional measure that improves the level of wellbeing in the population overall.

If we look at the taxonomy of Internet-based medical interventions (Barak, Klein, & Proudfoot, 2009), it’s interesting to imagine how many of these interventions might be reformulated as promotional (rather than therapeutic) strategies. Moreover, how many of them might be incorporated into the very tools we already use in our everyday activities? Although the notion of promotional strategies incorporated into everyday software remains somewhat forward thinking, there are a handful of examples of dedicated promotional tools. Among them is Echo.

Echo is a smartphone application for recording everyday experiences and reflecting on them afterward, created in collaboration by researchers in California (Isaacs, Konrad, Walendowski, & Lennig, 2013). They conducted three system deployments with 44 users who generated more than 12,000 recordings and reflections, and they found that the activity supported by the system (which they call “technology-mediated reflection”) successfully improved wellbeing. This study is instructive not only because it demonstrates an effective design for supporting reflection to promote wellbeing, but also because it serves as a model for rigorous evaluation of positive-computing technologies. The research team assessed results using four separate psychological metrics: the Subjective Happiness Scale, Satisfaction with Life Scale, Psychological General Well-Being Index, and the Mindfulness Attention Awareness Scale.

Echo is just one example of the ways in which many of the exercises that a therapist would use are translatable to online delivery. For example, role-playing (think videogames), writing reflections (as with Echo and writing tools that we analyze in the next section), disputing irrational beliefs (for example, by scaffolding the reasoning process online), and modifying language (Could we have a positive-computing spell checker for reflective practice?) are all therapeutic strategies amenable to technology support. Clearly, there is much room for innovation in this area, and we look forward to future examples of technologies for the treatment, prevention, and promotion of mental health.

Reflection versus Direct Instruction
Reflective approaches to self-improvement are particularly appropriate for technology intervention in that they avoid the path of giving direct prescriptive instruction, which is a risky approach for any generalized tool to take. Moreover, reflective feedback has greater potential in situations where a client’s full story and context are not clear, which is almost always the case online.

In one of the sidebars in chapter 3, Harvard social media scholar danah boyd describes the digital street—a poignant reminder of how public our lives are and the difficult considerations that have arisen around this new reality. The lives we see in these digital streets are visible only in fragments. Even when we want to put these fragments to good use—for example, by identifying people at risk in order to point them in the right direction for help—our task is not trivial because we remain unaware of the full context of their situation. In these instances, reflective interventions, where a person is (a) encouraged to contextualize issues for themselves, (b) provided with information upon which to reflect, and (c) not given direct advice to take a specific action, may pose the best solution.

In a project with the Young and Well Cooperative Research Centre, we currently are exploring how a computer could automatically detect cognitive distortions in what young people write in blogs and on social networks. Using natural-language processing, we hope to detect expressions of all-or-nothing thinking, overgeneralization, discounting the positive, and jumping to conclusions. Technologies that can recognize cognitive distortions might form the foundation for tools that help people recognize these distortions for themselves. Needless to say, the careful design of these tools will be critical. No one, least of all teenagers, wants a virtual agent telling them what he should or shouldn’t post on his wall. But creatively and respectfully applied, with deference to autonomy, values, participation, and preferences, such technologies just might promote greater wellbeing on unprecedented scale.

Reflection for Wellness and Wellbeing—Quantifying the Self
Personal informatics, personal analytics, quantified self, self-tracking—these are all terms that refer to technologies used by individuals to collect and analyze data about their behaviors (and sometimes about their moods or emotions).

The area has grown on multiple fronts in both business and academia. Independent software developers and entrepreneurs can take credit for the impressive speed at which it has advanced. Take Buster Benson—a software developer in California and a pioneering example of a user/developer combo who has immersed himself with gusto into the world of quantified self. Benson has been quantifying himself since 2000.2 In one of his earliest forays, he tracked his state of mind using a “mood-o-meter,” a system he used to log and publish information about his morale, his health, and his sleep in concert with data on his alcohol and caffeine consumption. Using this application, he would rate these variables on a scale of 1 to 10, describe the day’s events in a short diary entry, and produce plots and visualizations for him and others to view.

He points out that others found the visualizations valuable because they could better judge when to approach him to ask for a favor, and he found himself paying attention to the way in which he was perceived by others. Over the years he has built and often commercialized many more personal informatics tools. His quest, he says, is “to find meaning,” and he carries out this quest by exploring data.

On another leg of the quest, after beginning a personal diary in order to track how his moods changed over time, he created the website 750words.com. The website is similar to a blog but differs in its constraints and purpose. It has a much simpler interface, limits posts to 750 words, and is designed to produce reports from these personal journal entries. A simple report might read, “Rafael Calvo started at 7:10 pm and finished 470 words at 7:57 pm, for a total of 47 minutes of typing at 10 words per minute. Rafael Calvo was distracted 4 times while writing.” Benson integrates the information from this tool with photo streams, geomapping, emotional state tracking, the number of unresponded emails he has sitting in his inbox, tweets received, and myriad other data streams to produce an unusually detailed public portrait of his personal life.3

In a recent seminar, Benson shared his conflicting opinions of self-tracking, sometimes viewing it simply as compulsive behavior, sometimes finding meaning in the data, and sometimes finding that although there is meaning in it, it’s “hundreds of years away.”4 He also found that after years of trying to find numbers that better match to his internal reality, more generic labels (or Boolean scores) seem best suited to the job. In one of his apps, he uses factors such as sleep, physical activity, meaningful work, time spent with his son, and so on to produce a single average measure.

Although Benson’s personal voyage isn’t scientific research, it is instructive. The experiences of people such as Benson who have been “quantifying themselves” for such long periods of time can provide useful insights in the way that diary and case study methods have been successfully used in HCI research. Sure, his concern for privacy is clearly lower than average, or perhaps he’s simply courageous in the name of computer science, but the result is an intriguing public experiment (performance artwork, even) that anyone can explore in order to reflect on the potential benefits, risks, limitations, inanity, or promise of the thoroughly quantified life.

Together with people like Benson, entrepreneurs and developers are putting together all kinds of apps that help people reflect on their behaviors in light of data collected about almost any aspect of their lives. At the website PersonalInformatics.org, you can find a catalog with hundreds of applications, from those for diet and exercise to those for tracking your sex life.

Some developers integrate GPS data into applications that calculate running or cycling itineraries, distance benchmarks, speed, and approximate calories burned. Some companies add a website or a custom gadget to the mix. The gadget-based business model pertains to some of the most commercially successful products, such as those offered by Fitbit (in March 2013 valued at more than $300 million).

Possibly the most significant personal tracking experiences are occurring online, where people view visualizations, interact with gamified motivational features, and share data and goals with others. In our lab, we are currently developing a set of tools that combine observational data (e.g., from health gadgets and traffic logs) with self-reported data (e.g., responses to a CES-D questionnaire or other psychological instruments), aiming for a more holistic view.

Reflection will continue to play a central role in our technology- supported efforts in supporting self-awareness. However, relentless in our determination not to neglect the caveats, we know this chapter would not be complete without the case against too much reflection as a method for self-awareness to improve wellbeing.

Staring at Our Own Reflection
Can self-awareness (or at least reflection) go too far? When does healthy reflection become unhealthy rumination or obsessive self-focus? Will encouraging reflection simply feed the apparent rising trend in narcissism that is also linked to depression? Should we encourage self-focus when self-focus is known to be a conspicuous characteristic of depression? In a linguistic analysis of student essays, Stephanie Rude, Eva-Maria Gortner, and James Pennebaker (2004) found that depressed individuals used the word I more frequently than did their nondepressed counterparts.

These issues highlight the challenges inherent in supporting the “right kind” and “right amount” of reflection. As a way forward, we summarize some of the elucidating research on self-compassion and gratitude, potential antidotes to the risks of overreflection.

Rumination and Self-Criticism

Sonja Lyubomirsky, among many other psychologists, has studied rumination and its impact on depression, problem-solving ability, and sociability. While comparing people who tend to be happier with those who tend to be unhappier to the average, positive-psychology researchers have found a link between unhappiness and too much self-reflection, including “dwelling” (or rumination) and self-criticism. According to Lyubomirsky’s (2001) research, happier people tend to self-reflect about moods and outcomes less than unhappier people.

Rumination, in which thinking is mostly about past events (rather than the worrisome future), tends to focus on issues of loss and bereavement, self-worth, and so on. Myriad studies have consistently shown that rumination is associated with depression and other mental health problems and that focusing attention on oneself can also increase and extend the length of depressive episodes. In the article “Rethinking Rumination” (Nolen-Hoeksema, Wisco, & Lyubomirsky, 2008), the authors explain how rumination is not just correlated with neuroticism, perfectionism, and other negative cognitive styles but also mediates “the relationship between depression, neuroticism, negative inferential styles, dysfunctional attitudes, self-criticism, dependency and neediness.”

However, according to this same article, it is also not clear which forms of self-reflection can be adaptive, positive, and instrumental in personal change or even just benign. Some researchers have tried to separate factors using the Ruminative Responses Scale and other scales in attempts to disentangle positive forms of reflection from otherwise negative rumination. Evidence suggests a difference between analytic and experiential self-focus (Watkins & Teasdale, 2004), the latter relating to the nonjudgmental present-focused observation found in mindfulness practice or what Susan Nolen-Hoeksema and her colleagues (2008) call “concrete rumination” or “mindful experiencing.” (We discuss mindfulness in the next chapter.)

This is perhaps why the generally present-focused and experiential process of self-reporting moods seems to increase emotional self-awareness, an important positive aspect of a number of psychotherapies. The positive impact of self-reports has been shown in studies where participants reported their moods via phone messages (Kaur et al., 2012) or as longer personal diary entries such as blogs (Ko & Kuo, 2009). Interestingly, the evidence suggests that mobile phone self-reports can help reduce the brooding component of rumination (which is the component with strongest correlation to depression) (Kaur et al., 2012).

Future research in positive computing can look at how technologies might be designed in such a way to detect signs of overthinking, brooding, or self-criticism and perhaps to shift focus to supporting antidotal practices such as mindfulness, connection to others, and change of perspective.

Self-Awareness versus Narcissism

Sometimes the barrage of inane status updates, blathering blogs, and twittering tweets conspire to create a cognitive and emotional cacophony that have driven many to one conclusion: the connected world is raising a Generation Me that believes everything they think and do is important and worthy of public display. These new tools begin to look less like they’re about connecting and more like they’re about performing.

To be fair, experimentation with any new tool will involve doing so clumsily at first. And certainly, we have already begun to adjust the way we use social media in light of these effects—for example, by filtering more, storing less, demanding finer privacy settings, and reporting spam. Western capitalist culture, especially in the United States, is frequently criticized for an overfocus on individualism, self-interest, and an overemphasis on self-esteem. A recent New York Times article reported that “Rutgers researchers classify 80 percent of Twitter users as ‘meformers’ who tweet mainly about themselves” (Tierney, 2013). Will tools for self-awareness and self-tracking simply reinforce this pattern, leading to a new wave of digital selfing?

Indeed, there’s compelling evidence that both narcissism and narcissistic personality disorder have increased among younger generations in the United States (Twenge & Foster, 2010; Twenge, Konrath, Foster, Campbell, & Bushman, 2008). This downside comes, perhaps predictably, on the tail of more positive increases of other individualistic traits such as self-esteem, agency, assertiveness, and extraversion. Of course, you could say that previous generations had personal experience with economic depression, world war, and civil rights battles, which probably did more to temper a sense of entitlement than microblogging and personal digital devices do. But the meta-analyses look at levels of narcissism among college students from the early 1980s to the present day, not among their grandparents. Although the causes are surely various (from changes in education to cultural attitudes, politics, and lifestyles—all potentially playing a part), if we speculate that our digital technologies (or perhaps, more accurately, the ways we have designed and used them thus far) are playing some role in increasing levels of narcissism (and even if they’re not to blame), it’s sensible to ask what we can do about it in the context of positive computing. Contemporary researchers such as Paul Gilbert and Kristin Neff are among those who have spent the past decade investigating the potential of self-compassion to provide a more balanced way forward. While self-compassion might at first blush sound like just another “selfism,” it critically incorporates a broader perspective and a sense of shared humanity that, combined with gratitude, may be a key strategy for keeping reflection in balance.

Self-Esteem versus Self-Compassion
If you grew up with Barney the purple dinosaur, you’ll remember the theme song: “Cause you are special, special, everyone is special, everyone in his or her own way. …” Dorian recalls her father scoffing cynically at the oxymoronic notion that everyone is special. Of course, growing up in a working-class family on the rural outskirts of Pittsburgh meant that if you wanted to feel special, you had to work for it. We now know young children benefit greatly from praise, encouragement, and affirmation of their competence and potential, which is why research on self-esteem has been incredibly important to the way educational institutions now prepare children for success in life. Still, according to some, there has been a downside to the approaches we’ve taken to boosting self-esteem. Described charmingly as the “Lake Woebegone Effect” (in reference to radio personality Garrison Keillor’s fictional hometown, where “all women are strong, all men are good-looking, and all children are above average”), researchers have found that self-esteem that is contingent on external achievement or dependent on proof of perpetual above-averageness can lead to depression or narcissism down the track.

Psychologist Kristin Neff (2011) at the University of Texas, Austin, draws attention to the American obsession with needing to be above average. “In our incredibly competitive society, being average is unacceptable. We have to be special and above average to feel we have any worth at all. The problem, of course, is that it is impossible for everyone to be above average at the same time.” She cites research that shows how we struggle to maintain the fragile sense of specialness required for our self-esteem by inflating our self-evaluations and putting others down to feel superior. It’s hard not to think of all the “reality” TV shows and gossip magazines that in their condescending parade of the sensational sell us the opportunity to feel superior to others.

Neff goes on to unravel the consequences of a societal love affair with self-esteem, referencing grade inflation and the problems with a construct that is frequently contingent on external measures such as appearance, academic achievement, work performance, and social approval. “Contingent self-esteem drives people to obsess about the implications of negative events for self-worth, making them more vulnerable to depression and reduced self-concept clarity.” Although she emphasizes that there are certainly healthy forms of self-esteem and there is much research linking self-esteem to wellbeing, she argues that these benefits can be found without the downsides in a notion of self-compassion.

Paul Gilbert (2009, 2010) introduced compassion-focused therapy in the past decade as a novel way to help people who suffer from high levels of shame and self-criticism. The concept of self-compassion may be new to Western psychology, but it is certainly not new to humanity. Gilbert credits Buddhist psychology as a source for compassion-focused therapy because it centers on compassion in its practice (Buddhist loving-kindness meditation begins with compassion for oneself).

According to Neff (2011), “self-compassion entails three main components which overlap and mutually interact: Self-kindness versus self- judgment, feelings of common humanity versus isolation, and mindfulness versus over-identification.” Self-compassion has been correlated to increased wellbeing in multiple ways. It has also been shown to be a highly effective predictor of quality of life (Van Dam, Sheppard, Forsyth, & Earleywine, 2011) and has been correlated to other aspects of interest to positive-computing work, such as increased self-improvement motivation and reduced risk of Internet addiction. Laura Bernard and John Curry (2011) provide a summary of wellbeing correlates and suggest intervention strategies that could begin to inspire work in positive computing.

Gratitude and Appreciation

For a final antidote to over-focus on the self, and one that also fosters wellbeing in its own right, we turn to gratitude. The practice of gratitude in various forms (from thank-you letters to gratitude journals) has consistently been shown to increase wellbeing (for reviews see: Emmons & McCullough, 2004; Watkins, Woodward, Stone, & Kolts, 2003; Wood, Froh, & Geraghty, 2010). Christine Carter (2011), Director of Berkeley’s Greater Good Science Center, recommends gratitude practice for curbing a sense of entitlement in our children as well as for fostering positive relationships: “Our culture glorifies independence and undervalues how much others help; we see our blessings as hard earned … appreciation is one of the most important ways that we teach our kids to form strong relationships with others … expressing gratitude is about expressing just how deep those connections run.”

Design for gratitude already makes a few appearances in the virtual world. There are apps available to support gratitude practices (such as gratitude journals), games occasionally include opportunities for gratitude (e.g., Hay Day allows players to send thank you cards when help is provided by other players in the game), and the Learning Solutions website transformed the ubiquitous “like” into the more gratitude-focused “I appreciate this.” Creative thinking around how we can support users in experiencing and extending acts of gratitude and appreciation will be a rewarding area of ongoing exploratory practice and one that can contribute positively to wellbeing.

A Way Forward

Tracking and sharing personal data can encourage us to compare ourselves to others, yet the research on happiness and self-compassion show that this can negatively impact our wellbeing. Reflecting on our thoughts, emotions, and behaviors is essential to personal growth, but obsessive rumination contributes to depression. How do we design technologies that support practices beneficial to wellbeing without reinforcing associated problems? We do not claim to have the answer, but we suggest the following design principles as safeguards in favor of healthy balance.

Design Implications
Principles for Supporting Self-Awareness and Reflection

  * Understand the pitfalls. Cultivating an awareness and understanding of the pitfalls that exist surrounding reflection and self-tracking will help us (designers) to avoid inadvertently supporting them.
  * Design for self-compassion, gratitude, and mindfulness. Research suggests that underscoring our efforts with principles of self-compassion, gratitude, and mindfulness will help prevent comparison, self-criticism, narcissism, and entitlement.
  * Acknowledge the limitations of technology and lean toward reflective support. Honoring the diversity and complexity of people while acknowledging the limitations of what can be provided by technology will often mean employing reflective feedback and avoiding highly prescriptive and constrained solutions. Outside of human-mediated medical intervention, what we don’t know about our users and their contexts will always outstrip what we do know, so providing them feedback for making better decisions will often be more widely effective than providing specific instruction.
  * Allow for nonabsolute categories. When we present the analysis of personal data to support inferences about states of mind or behavior, we should not be constrained to predefined categories. This idea is based on the work by Ellen Langer, who showed the negative impact of preconceptions on creativity. In her studies, Langer (e.g., Langer & Piper, 1987) provided evidence that when people come to a task with strong, absolute conceptions, for example when they are told, “This is a ___,” in contrast to a conditional conception, as when they are told, “This could be a ___,” they are much less likely to adapt or be creative with the concept.

Follow the Ongoing Research

Although better understanding of how we can design safeguards and adaptations to ensure that wellbeing interventions genuinely promote wellbeing will require ongoing research, understanding that these tensions exist and following research in antidotal concepts such as self-compassion, gratitude, altruism, and sympathetic joy are sure to be critical to approaching an optimal balance over time.

And now, after alluding a number of times to the incredible promise of mindfulness for wellbeing, we turn to this unique state and practice in the next chapter—to its definition, its many positive correlates, and the strategies that have been proven to promote it.
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====== 8 Self-Awareness and Self-Compassion ======

It was late in his life, as he faced his executioners, that one of the world’s greatest thinkers would conclude that death was preferable to giving up philosophy. To those in his midst he declared simply: “The unexamined life is not worth living.” Socrates would go on to swallow hemlock for his crimes—crimes that would come to represent a pinnacle of human achievement.

A century earlier ancient India had yielded another of the world’s greatest philosophers, Gautama Buddha, who said “You are what you think. All that you are arises from your thoughts. With your thoughts you make your world.” The core Buddhist tenet summarized by the Four Noble Truths explains that in order to end our experience of suffering, we must first understand the workings of our mind. We must be able to recognize our thoughts, our emotions, our reactions, and their precursors, as they are the roots of our suffering.

Methods for self-examination, introspection, and self-awareness have since been refined by generations of philosophers, and more recently by modern Western psychologists from Sigmund Freud to Aaron Beck.

Now, in the second decade of the twenty-first century, cognitive behavioral therapy (CBT) has gone online: experience sampling solicits mood updates via smart phone, and the quantified-self movement inspires growing innovation in personal data analysis. But is it reasonable to expect any deeper understanding of our personal thoughts and emotions to arise from data? Can artificial intelligence, sophisticated machine-learning algorithms, and digital visualizations really help us to know ourselves better? If they did, would we be better for it?

In this chapter, we look at the state of the art in technology-mediated reflection, the varied approaches that have been applied to this endeavor, and the research emerging from its use. We also look at the foundations in psychology that underpin efforts toward greater self-awareness and how they are linked to increases in wellbeing. We look at both the potentials and the problems that may be associated with technological intervention into our inner lives, while deliberately evading the question, Would the Buddha have tweeted “feeling one with the universe” from under the Bodhi Tree?

Know Thyself
Why bother? Is self-knowledge merely philosophically virtuous or actually important to greater happiness and flourishing? Methods for CBT demonstrate that increased self-awareness can indeed improve wellbeing. In fact, a healthy chunk of the research and clinical work in modern psychology relies on promoting awareness of one’s thoughts, emotions, and behaviors in order to effectively treat mental illnesses such as anxiety and depression.

Neuroscientist Richard Davidson (e.g., Davidson & Begley, 2012) has identified recognizable neurophysiological patterns associated with self-awareness. He has found that greater self-awareness is associated with increased activity in the insula (involved in consciousness, emotion, and body regulation) and that long-time meditators have larger insulas.

If self-awareness is important to personal growth and wellbeing, what can we do to develop it, and how can technology play a part in that development? The answer is most frequently sought in various forms of reflection, introspection, and mindfulness training. There is an impressive wealth of evidence for the effectiveness of mindfulness practice on wellbeing, including the work of Jon Kabat-Zinn and researchers at the Oxford Mindfulness Centre. Davidson cites neurophysiological evidence for the effectiveness of mindfulness practice both for increasing self-awareness and for tempering potential negative side effects that might accompany this awareness (e.g., hypersensitivity and anxiety). We reserve mindfulness, however, for the next chapter and deal with it as a factor of wellbeing in its own right. In this chapter, we focus on reflection.

According to twentieth-century philosopher, psychologist, and educational reformer John Dewey (2013), it is essential for education to develop the skills of reflection: “while we cannot learn or be taught to think, we do have to learn to think well, especially acquire the general habit of reflection.” For Dewey, reflection is an act of reason that is often but not always directed to understanding the external world. He was also very willing to apply this objective rationality to more emotional concerns. “The meanings of honesty, sympathy, hatred, fear, must be grasped by having them presented in an individual’s first hand experience.” Applying Dewey’s imperative to modern technology design suggests that systems intended to help people reflect on emotions should do so from the context of the user’s own life experiences rather than from abstract concepts. Of course, emotions are just one category of things upon which one might introspect. There are at least three others.

Targets of Reflection
When we speak of self-awareness or reflection, there are various interpretations regarding what it is we are becoming aware of or upon which we are reflecting. Over time there have been proposals for various targets of reflective thought, which can roughly be synthesized into four main categories.

Cognitive awareness is what we believe we know about the world around us and our own lives. Understanding this aspect in ourselves is generally referred to as “metacognition,” a term introduced by John Flavell in the late 1970s (Flavell, 1979). A great deal of research on how to build computer systems to support metacognition is available in the learning technologies literature.

Affective awareness involves awareness of our states of mind, in particular moods and emotions. Strategies and computer tools that help us track and reflect on our moods and emotions have been developed in the areas of psychotherapy and affective computing and as commercial tools. Some of these tools are discussed later in this chapter.

Experiential awareness is our awareness of the integrated aspects of cognition, affect, and behavior (including their external and internal triggers). The combination of these three aspects of “experience” (cognition, affect, and behavior) is at the core of CBT, which we describe in more detail later in this chapter.

Character traits, or those aspects of personality that are dispositional qualities, are a fourth set of mental aspects upon which we can reflect. We won’t be focusing on this last category in this chapter because there is insufficient research to draw on at this stage. We delve more deeply into the cognitive, affective, and experiential in the next three sections.

Cognitive Awareness and Metacognition
Metacognitive skills, or the ability to “know what one knows,” are important to many aspects of life experience, from setting realistic personal targets to self-regulating learning activity. A number of researchers have explored metacognition in the context of designing intelligent tutoring systems. These systems can support learning by supporting metacognition—for example, encouraging self-explanation (as a way of scaffolding reflection) and setting personalized goals. In addition to using metacognition strategies as a feature, other systems have focused on developing metacognitive skills per se, based on the principles for metacognitive tutoring proposed by John R. Anderson and his colleagues (Anderson, Corbett, Koedinger, & Pelletier, 1995).

Outside of the learning context, researchers have considered the impact of metacognitive skills on mental health (particularly in the context of cognitive therapies), linking them to wellbeing. We come back to these examples later in the chapter.

Affective Awareness and Emotional Intelligence
The literature on emotional intelligence (EI) has focused on affective awareness—namely, the skills required to recognize and regulate our emotions in a way that is consistent with a model of emotional functioning (Mayer & Salovey, 1995). We discussed emotional intelligence in chapter 3, but it’s worth coming back to Daniel Goleman’s (1998) five EI skills because they provide a useful breakdown of affective awareness as it might contribute to wellbeing. The five EI skills are:

  * Self-awareness (the ability to recognize our own emotions)
  * Self-regulation (the ability to control them)
  * Motivation (passion for what we do)
  * Empathy (the ability to recognize others’ emotions, which is covered in depth in chapter 10)
  * Social skills, in particular the ability to manage relationships with others

Most of the research on EI links it to concrete measures of success, such as productivity in the workplace. Nevertheless, there is also some initial evidence for a link between EI and psychological wellbeing. For example, a number of studies have looked at how well EI predicts wellbeing as defined by standard SWB measures. Emma Gallagher and Dianne Vella-Brodrick (2008) analyzed the impact of EI on SWB, removing the effect of other factors such as personality and sociodemographic variables (e.g., wealth). They analyzed measures of life satisfaction, positive and negative affect, social support, EI, personality, and social desirability from the self-reports of 267 adults. Their analyses showed that EI and social support as well as their interaction effects significantly predicted SWB. Further research on these links would be helpful in demonstrating whether interventions to develop EI also increase wellbeing.

Experiential Awareness and Reflection
Perhaps the most promising strategies for reflection are those that target the holistic relationships between thoughts, feelings, and behaviors. The development of such understanding is at the core of some mindfulness practices and cognitive therapy, both of which have been empirically linked to wellbeing.

It’s worth pointing out the challenges of interdisciplinary research around a construct with as many varied interpretations as self-reflection. Each discipline looks at different aspects of reflection and takes a different focus. On the one hand, we might approach reflection, as Socrates, Dewey, and Peter Salovey have, as a retrospective dimension of thought. Even within this category approaches differ; Socrates’s point of departure was moral philosophy; Dewey’s interest was cognition and education; and other authors have studied reflection from the perspective of professional practice (e.g., Schön, 1983). In contrast, in mindfulness training and Buddhist psychology, reflection is generally rooted in the present. It is a present-moment self-awareness that observes thoughts, emotions, and behaviors as they arise, often in the context of deliberate contemplative practice.

The concept of reflection has been used in so many ways it risks becoming a bit of a catch-all. Therefore, in order for the concept to be useful to positive computing in a practical sense, it must first be contextualized. The adoption of any model of reflection for the development of technology will be shaped by (a) our motives for targeting reflection in the first place (What problem are we trying to solve? What activity are we trying to support?), (b) the development process we follow, and (c) the methods of evaluation we use.

By way of example, in the next section we discuss two contexts within which technologies can be (and have been) used to support reflection. The first is psychotherapy, in which reflecting on cognitive and behavioral patterns has been demonstrated to effect transformative experiences, especially for those with mental illness. In the second example, we discuss reflection at a more prosaic level and at a narrower granularity. We look at the practice of reflecting retrospectively on our daily behaviors, moods, and goals and at how new technologies, particularly in the area of personal informatics, can be used to collect behavioral data and scaffold the reflection process.

Reflection as a Strategy for Mental Health Treatment
Cognitive Behavioral Therapy

A number of psychotherapies focus on developing a self-understanding of the relationships between our thoughts, feelings, and behaviors. One of the most commonly used psychotherapies in the treatment of depression and anxiety is cognitive behavioral therapy. CBT was developed by Aaron T. Beck (Beck, Rush, Shaw, & Emery, 1987) and is closely related to rational emotive behavioral therapy developed by Albert Ellis (1973), both during the late 1950s. While Beck was treating patients using a psychoanalytic method, he began to notice how they, especially those with depression, often misinterpreted or had “cognitive distortions” relating to events in their lives. They would, for example, selectively obstruct certain thought processes or overgeneralize. For instance, a patient might interpret the fact that his spouse didn’t kiss him good-bye in the morning as evidence that he is no longer loved.

CBT is essentially based on the concept that the way we think influences the way we feel, which in turn influences the way we behave. This process, thinking–feeling–behaving, is part of an internal communication that people can access through reflection. The client can discover the meanings of such processes, in particular the triggers of irrational thinking and follow-up feelings, with the therapist’s help. The therapist often follows a Socratic questioning approach, scaffolding the client’s reflection so that he evaluates his assumptions and can modify his thinking. This systematic questioning (a.k.a. “talk therapy”) is combined with other activities such as role playing, writing in a diary, disputing irrational beliefs, and modifying language to be more positive, assertive, or playful.

Technology for CBT

Richard Layard, notable British economist and proponent of national wellbeing measures, has called on the UK government to invest both in increasing the provision of CBT and in teaching EI in schools in aid of improving national wellbeing. One strategy for increasing the reach of CBT programs in light of a shortage of trained therapists is through technology, and computers have already been successfully used to deliver such programs. In fact, computer-based CBT (CCBT) has been successful enough that in the United Kingdom the National Institute for Clinical Excellence considers Internet-delivered CBT a viable way of treating patients, in particular those with anxiety.

In a Health Technology Assessment for the UK National Health System, Eva Kaltenthaler and her colleagues (2006) compared the clinical and cost effectiveness of a number of online CBT products to traditional approaches. According to their analysis of 20 randomized controlled trial studies, there is evidence that CCBT is as effective as therapist CBT for the treatment of phobias and panic and is more cost effective for depression and anxiety. Moreover, using CCBT in conjunction with a therapist can reduce therapist time required.

It’s worth noting that we do not believe computers can reasonably replace human mental health professionals. Any such notion would reflect a lack of understanding regarding the complexity of mental illness and the mental health profession. We reject a people-replacement model of technology’s role in mental health, not only because of technology’s limited ability to be creative and empathic and to provide genuine human presence, but also because technology-based programs are largely generalized, incapable of making critical insights or adapting sufficiently to the nuance and variety in human personalities and circumstances. As such, technological systems are probably incapable of safely assisting with nontextbook, long-term, and life-threatening cases. Nevertheless, for certain types of mental health challenges, they could contribute significant help in, at least, the following four ways:

  * As complement to therapist treatment for a richer, more consistent, and possibly shorter treatment phase
  * As follow-up and maintenance after therapist sessions are complete
  * As triage where a shortage of qualified mental health professionals face far more people in need of help than can possibly be seen in one-on-one, hour-long sessions. Technology might be used to support more mild cases, while immediately directing those who may be in danger to professional help.
  * As a wider net for the many people who, although they are in need of professional help, do not seek it for many reasons such as stigma, fear, cost, and logistics. The anonymity and easy access provided by online programs can potentially foster flourishing in a much larger number of people. Some of these people may even proceed to seeking professional help once transitioned by such a process. Others may find the online program in itself successful in improving their lives.

To these ends, initial research is promising. In an Australian evaluation of a CCBT system (Mackinnon, Griffiths, & Christensen, 2008), three conditions were explored: the use of MoodGym, an Internet-based CBT intervention; the use of Bluepages, a website with information; and a control placebo group. Results showed that the Internet interventions reduced depression symptoms to a greater extent than the control group. This was true for a post-test, the 6-month follow-up, and a 12-month follow-up.

A UK randomized controlled trial of the efficacy of CCBT (Proudfoot, Ryden, Shapiro, Goldberg, & Gray, 2004) showed even stronger outcomes. The authors compared a commercial multimedia CCBT system (Beating the Blues1) with traditional treatment and found that “the computerised therapy improved depression, negative attributional style, work and social adjustment. … For anxiety and positive attributional style, treatment interacted with severity such that computerised therapy did better than usual treatment for more disturbed patients. Computerised therapy also led to greater satisfaction with treatment.”

These computer-based systems are exceptions in that they have been evaluated in peer-reviewed studies. Hundreds of other CCBT apps, many available for a few dollars at the app store, do not have the benefit of such evaluations. Most tend to be augmented diaries, providing users with a way to record events. Thoughts pertaining to these events can sometimes be labeled—for example, as “unhelpful” or “sad.” Other apps focus on specific activities (e.g., sleep, diet, and drinking).

For example, Drink Coach is an app developed by the Haringey Advisory Group on Alcohol, a UK group supporting those who suffer from alcohol misuse. The app focuses on scaffolding reflection on drinking habits. The user can record her alcohol consumption and the “risks” associated with it as well as set goals. The system tracks alcohol units and related calories consumed over time, and diary entries include fields for craving duration and intensity. The app also provides videos about mindfulness and breathing exercises that can help with cravings.

Panic Attacks is an app produced by myCBT Ltd. that focuses on anxiety disorders. It provides audio recordings designed to be calming, information on panic attacks, and a diary that helps challenge misinterpretations.

We hope to see more research and rigorous evaluation of these kinds of apps in the future so that we all can learn more about how best to design this kind of support.

Technology-Mediated Reflection for Wellbeing
The examples of CCBT in the previous section deal with mental health treatment. However, the focus of positive computing is mental health promotion. Of course, we have elected to spend significant time describing these e-therapy approaches in part because they are some of the most sophisticated and well-evaluated examples of technologies directed at psychological functioning that exist today, but also because you don’t have to be ill to benefit from them. For example, it is not only the clinically depressed that find themselves having irrational thoughts, making overgeneralizations, or “catastrophizing.” Most of us are prone to the kind of mental habits that in larger amounts and combined with other symptoms characterize clinical anxiety and depression. Even those of us who are mentally healthy can thus benefit from the exercises and practice of detecting cognitive distortions. Reducing these habits in the general population can be seen not only as a preventative measure that builds resilience to illness, but also as a promotional measure that improves the level of wellbeing in the population overall.

If we look at the taxonomy of Internet-based medical interventions (Barak, Klein, & Proudfoot, 2009), it’s interesting to imagine how many of these interventions might be reformulated as promotional (rather than therapeutic) strategies. Moreover, how many of them might be incorporated into the very tools we already use in our everyday activities? Although the notion of promotional strategies incorporated into everyday software remains somewhat forward thinking, there are a handful of examples of dedicated promotional tools. Among them is Echo.

Echo is a smartphone application for recording everyday experiences and reflecting on them afterward, created in collaboration by researchers in California (Isaacs, Konrad, Walendowski, & Lennig, 2013). They conducted three system deployments with 44 users who generated more than 12,000 recordings and reflections, and they found that the activity supported by the system (which they call “technology-mediated reflection”) successfully improved wellbeing. This study is instructive not only because it demonstrates an effective design for supporting reflection to promote wellbeing, but also because it serves as a model for rigorous evaluation of positive-computing technologies. The research team assessed results using four separate psychological metrics: the Subjective Happiness Scale, Satisfaction with Life Scale, Psychological General Well-Being Index, and the Mindfulness Attention Awareness Scale.

Echo is just one example of the ways in which many of the exercises that a therapist would use are translatable to online delivery. For example, role-playing (think videogames), writing reflections (as with Echo and writing tools that we analyze in the next section), disputing irrational beliefs (for example, by scaffolding the reasoning process online), and modifying language (Could we have a positive-computing spell checker for reflective practice?) are all therapeutic strategies amenable to technology support. Clearly, there is much room for innovation in this area, and we look forward to future examples of technologies for the treatment, prevention, and promotion of mental health.

Reflection versus Direct Instruction
Reflective approaches to self-improvement are particularly appropriate for technology intervention in that they avoid the path of giving direct prescriptive instruction, which is a risky approach for any generalized tool to take. Moreover, reflective feedback has greater potential in situations where a client’s full story and context are not clear, which is almost always the case online.

In one of the sidebars in chapter 3, Harvard social media scholar danah boyd describes the digital street—a poignant reminder of how public our lives are and the difficult considerations that have arisen around this new reality. The lives we see in these digital streets are visible only in fragments. Even when we want to put these fragments to good use—for example, by identifying people at risk in order to point them in the right direction for help—our task is not trivial because we remain unaware of the full context of their situation. In these instances, reflective interventions, where a person is (a) encouraged to contextualize issues for themselves, (b) provided with information upon which to reflect, and (c) not given direct advice to take a specific action, may pose the best solution.

In a project with the Young and Well Cooperative Research Centre, we currently are exploring how a computer could automatically detect cognitive distortions in what young people write in blogs and on social networks. Using natural-language processing, we hope to detect expressions of all-or-nothing thinking, overgeneralization, discounting the positive, and jumping to conclusions. Technologies that can recognize cognitive distortions might form the foundation for tools that help people recognize these distortions for themselves. Needless to say, the careful design of these tools will be critical. No one, least of all teenagers, wants a virtual agent telling them what he should or shouldn’t post on his wall. But creatively and respectfully applied, with deference to autonomy, values, participation, and preferences, such technologies just might promote greater wellbeing on unprecedented scale.

Reflection for Wellness and Wellbeing—Quantifying the Self
Personal informatics, personal analytics, quantified self, self-tracking—these are all terms that refer to technologies used by individuals to collect and analyze data about their behaviors (and sometimes about their moods or emotions).

The area has grown on multiple fronts in both business and academia. Independent software developers and entrepreneurs can take credit for the impressive speed at which it has advanced. Take Buster Benson—a software developer in California and a pioneering example of a user/developer combo who has immersed himself with gusto into the world of quantified self. Benson has been quantifying himself since 2000.2 In one of his earliest forays, he tracked his state of mind using a “mood-o-meter,” a system he used to log and publish information about his morale, his health, and his sleep in concert with data on his alcohol and caffeine consumption. Using this application, he would rate these variables on a scale of 1 to 10, describe the day’s events in a short diary entry, and produce plots and visualizations for him and others to view.

He points out that others found the visualizations valuable because they could better judge when to approach him to ask for a favor, and he found himself paying attention to the way in which he was perceived by others. Over the years he has built and often commercialized many more personal informatics tools. His quest, he says, is “to find meaning,” and he carries out this quest by exploring data.

On another leg of the quest, after beginning a personal diary in order to track how his moods changed over time, he created the website 750words.com. The website is similar to a blog but differs in its constraints and purpose. It has a much simpler interface, limits posts to 750 words, and is designed to produce reports from these personal journal entries. A simple report might read, “Rafael Calvo started at 7:10 pm and finished 470 words at 7:57 pm, for a total of 47 minutes of typing at 10 words per minute. Rafael Calvo was distracted 4 times while writing.” Benson integrates the information from this tool with photo streams, geomapping, emotional state tracking, the number of unresponded emails he has sitting in his inbox, tweets received, and myriad other data streams to produce an unusually detailed public portrait of his personal life.3

In a recent seminar, Benson shared his conflicting opinions of self-tracking, sometimes viewing it simply as compulsive behavior, sometimes finding meaning in the data, and sometimes finding that although there is meaning in it, it’s “hundreds of years away.”4 He also found that after years of trying to find numbers that better match to his internal reality, more generic labels (or Boolean scores) seem best suited to the job. In one of his apps, he uses factors such as sleep, physical activity, meaningful work, time spent with his son, and so on to produce a single average measure.

Although Benson’s personal voyage isn’t scientific research, it is instructive. The experiences of people such as Benson who have been “quantifying themselves” for such long periods of time can provide useful insights in the way that diary and case study methods have been successfully used in HCI research. Sure, his concern for privacy is clearly lower than average, or perhaps he’s simply courageous in the name of computer science, but the result is an intriguing public experiment (performance artwork, even) that anyone can explore in order to reflect on the potential benefits, risks, limitations, inanity, or promise of the thoroughly quantified life.

Together with people like Benson, entrepreneurs and developers are putting together all kinds of apps that help people reflect on their behaviors in light of data collected about almost any aspect of their lives. At the website PersonalInformatics.org, you can find a catalog with hundreds of applications, from those for diet and exercise to those for tracking your sex life.

Some developers integrate GPS data into applications that calculate running or cycling itineraries, distance benchmarks, speed, and approximate calories burned. Some companies add a website or a custom gadget to the mix. The gadget-based business model pertains to some of the most commercially successful products, such as those offered by Fitbit (in March 2013 valued at more than $300 million).

Possibly the most significant personal tracking experiences are occurring online, where people view visualizations, interact with gamified motivational features, and share data and goals with others. In our lab, we are currently developing a set of tools that combine observational data (e.g., from health gadgets and traffic logs) with self-reported data (e.g., responses to a CES-D questionnaire or other psychological instruments), aiming for a more holistic view.

Reflection will continue to play a central role in our technology- supported efforts in supporting self-awareness. However, relentless in our determination not to neglect the caveats, we know this chapter would not be complete without the case against too much reflection as a method for self-awareness to improve wellbeing.

Staring at Our Own Reflection
Can self-awareness (or at least reflection) go too far? When does healthy reflection become unhealthy rumination or obsessive self-focus? Will encouraging reflection simply feed the apparent rising trend in narcissism that is also linked to depression? Should we encourage self-focus when self-focus is known to be a conspicuous characteristic of depression? In a linguistic analysis of student essays, Stephanie Rude, Eva-Maria Gortner, and James Pennebaker (2004) found that depressed individuals used the word I more frequently than did their nondepressed counterparts.

These issues highlight the challenges inherent in supporting the “right kind” and “right amount” of reflection. As a way forward, we summarize some of the elucidating research on self-compassion and gratitude, potential antidotes to the risks of overreflection.

Rumination and Self-Criticism

Sonja Lyubomirsky, among many other psychologists, has studied rumination and its impact on depression, problem-solving ability, and sociability. While comparing people who tend to be happier with those who tend to be unhappier to the average, positive-psychology researchers have found a link between unhappiness and too much self-reflection, including “dwelling” (or rumination) and self-criticism. According to Lyubomirsky’s (2001) research, happier people tend to self-reflect about moods and outcomes less than unhappier people.

Rumination, in which thinking is mostly about past events (rather than the worrisome future), tends to focus on issues of loss and bereavement, self-worth, and so on. Myriad studies have consistently shown that rumination is associated with depression and other mental health problems and that focusing attention on oneself can also increase and extend the length of depressive episodes. In the article “Rethinking Rumination” (Nolen-Hoeksema, Wisco, & Lyubomirsky, 2008), the authors explain how rumination is not just correlated with neuroticism, perfectionism, and other negative cognitive styles but also mediates “the relationship between depression, neuroticism, negative inferential styles, dysfunctional attitudes, self-criticism, dependency and neediness.”

However, according to this same article, it is also not clear which forms of self-reflection can be adaptive, positive, and instrumental in personal change or even just benign. Some researchers have tried to separate factors using the Ruminative Responses Scale and other scales in attempts to disentangle positive forms of reflection from otherwise negative rumination. Evidence suggests a difference between analytic and experiential self-focus (Watkins & Teasdale, 2004), the latter relating to the nonjudgmental present-focused observation found in mindfulness practice or what Susan Nolen-Hoeksema and her colleagues (2008) call “concrete rumination” or “mindful experiencing.” (We discuss mindfulness in the next chapter.)

This is perhaps why the generally present-focused and experiential process of self-reporting moods seems to increase emotional self-awareness, an important positive aspect of a number of psychotherapies. The positive impact of self-reports has been shown in studies where participants reported their moods via phone messages (Kaur et al., 2012) or as longer personal diary entries such as blogs (Ko & Kuo, 2009). Interestingly, the evidence suggests that mobile phone self-reports can help reduce the brooding component of rumination (which is the component with strongest correlation to depression) (Kaur et al., 2012).

Future research in positive computing can look at how technologies might be designed in such a way to detect signs of overthinking, brooding, or self-criticism and perhaps to shift focus to supporting antidotal practices such as mindfulness, connection to others, and change of perspective.

Self-Awareness versus Narcissism

Sometimes the barrage of inane status updates, blathering blogs, and twittering tweets conspire to create a cognitive and emotional cacophony that have driven many to one conclusion: the connected world is raising a Generation Me that believes everything they think and do is important and worthy of public display. These new tools begin to look less like they’re about connecting and more like they’re about performing.

To be fair, experimentation with any new tool will involve doing so clumsily at first. And certainly, we have already begun to adjust the way we use social media in light of these effects—for example, by filtering more, storing less, demanding finer privacy settings, and reporting spam. Western capitalist culture, especially in the United States, is frequently criticized for an overfocus on individualism, self-interest, and an overemphasis on self-esteem. A recent New York Times article reported that “Rutgers researchers classify 80 percent of Twitter users as ‘meformers’ who tweet mainly about themselves” (Tierney, 2013). Will tools for self-awareness and self-tracking simply reinforce this pattern, leading to a new wave of digital selfing?

Indeed, there’s compelling evidence that both narcissism and narcissistic personality disorder have increased among younger generations in the United States (Twenge & Foster, 2010; Twenge, Konrath, Foster, Campbell, & Bushman, 2008). This downside comes, perhaps predictably, on the tail of more positive increases of other individualistic traits such as self-esteem, agency, assertiveness, and extraversion. Of course, you could say that previous generations had personal experience with economic depression, world war, and civil rights battles, which probably did more to temper a sense of entitlement than microblogging and personal digital devices do. But the meta-analyses look at levels of narcissism among college students from the early 1980s to the present day, not among their grandparents. Although the causes are surely various (from changes in education to cultural attitudes, politics, and lifestyles—all potentially playing a part), if we speculate that our digital technologies (or perhaps, more accurately, the ways we have designed and used them thus far) are playing some role in increasing levels of narcissism (and even if they’re not to blame), it’s sensible to ask what we can do about it in the context of positive computing. Contemporary researchers such as Paul Gilbert and Kristin Neff are among those who have spent the past decade investigating the potential of self-compassion to provide a more balanced way forward. While self-compassion might at first blush sound like just another “selfism,” it critically incorporates a broader perspective and a sense of shared humanity that, combined with gratitude, may be a key strategy for keeping reflection in balance.

Self-Esteem versus Self-Compassion
If you grew up with Barney the purple dinosaur, you’ll remember the theme song: “Cause you are special, special, everyone is special, everyone in his or her own way. …” Dorian recalls her father scoffing cynically at the oxymoronic notion that everyone is special. Of course, growing up in a working-class family on the rural outskirts of Pittsburgh meant that if you wanted to feel special, you had to work for it. We now know young children benefit greatly from praise, encouragement, and affirmation of their competence and potential, which is why research on self-esteem has been incredibly important to the way educational institutions now prepare children for success in life. Still, according to some, there has been a downside to the approaches we’ve taken to boosting self-esteem. Described charmingly as the “Lake Woebegone Effect” (in reference to radio personality Garrison Keillor’s fictional hometown, where “all women are strong, all men are good-looking, and all children are above average”), researchers have found that self-esteem that is contingent on external achievement or dependent on proof of perpetual above-averageness can lead to depression or narcissism down the track.

Psychologist Kristin Neff (2011) at the University of Texas, Austin, draws attention to the American obsession with needing to be above average. “In our incredibly competitive society, being average is unacceptable. We have to be special and above average to feel we have any worth at all. The problem, of course, is that it is impossible for everyone to be above average at the same time.” She cites research that shows how we struggle to maintain the fragile sense of specialness required for our self-esteem by inflating our self-evaluations and putting others down to feel superior. It’s hard not to think of all the “reality” TV shows and gossip magazines that in their condescending parade of the sensational sell us the opportunity to feel superior to others.

Neff goes on to unravel the consequences of a societal love affair with self-esteem, referencing grade inflation and the problems with a construct that is frequently contingent on external measures such as appearance, academic achievement, work performance, and social approval. “Contingent self-esteem drives people to obsess about the implications of negative events for self-worth, making them more vulnerable to depression and reduced self-concept clarity.” Although she emphasizes that there are certainly healthy forms of self-esteem and there is much research linking self-esteem to wellbeing, she argues that these benefits can be found without the downsides in a notion of self-compassion.

Paul Gilbert (2009, 2010) introduced compassion-focused therapy in the past decade as a novel way to help people who suffer from high levels of shame and self-criticism. The concept of self-compassion may be new to Western psychology, but it is certainly not new to humanity. Gilbert credits Buddhist psychology as a source for compassion-focused therapy because it centers on compassion in its practice (Buddhist loving-kindness meditation begins with compassion for oneself).

According to Neff (2011), “self-compassion entails three main components which overlap and mutually interact: Self-kindness versus self- judgment, feelings of common humanity versus isolation, and mindfulness versus over-identification.” Self-compassion has been correlated to increased wellbeing in multiple ways. It has also been shown to be a highly effective predictor of quality of life (Van Dam, Sheppard, Forsyth, & Earleywine, 2011) and has been correlated to other aspects of interest to positive-computing work, such as increased self-improvement motivation and reduced risk of Internet addiction. Laura Bernard and John Curry (2011) provide a summary of wellbeing correlates and suggest intervention strategies that could begin to inspire work in positive computing.

Gratitude and Appreciation

For a final antidote to over-focus on the self, and one that also fosters wellbeing in its own right, we turn to gratitude. The practice of gratitude in various forms (from thank-you letters to gratitude journals) has consistently been shown to increase wellbeing (for reviews see: Emmons & McCullough, 2004; Watkins, Woodward, Stone, & Kolts, 2003; Wood, Froh, & Geraghty, 2010). Christine Carter (2011), Director of Berkeley’s Greater Good Science Center, recommends gratitude practice for curbing a sense of entitlement in our children as well as for fostering positive relationships: “Our culture glorifies independence and undervalues how much others help; we see our blessings as hard earned … appreciation is one of the most important ways that we teach our kids to form strong relationships with others … expressing gratitude is about expressing just how deep those connections run.”

Design for gratitude already makes a few appearances in the virtual world. There are apps available to support gratitude practices (such as gratitude journals), games occasionally include opportunities for gratitude (e.g., Hay Day allows players to send thank you cards when help is provided by other players in the game), and the Learning Solutions website transformed the ubiquitous “like” into the more gratitude-focused “I appreciate this.” Creative thinking around how we can support users in experiencing and extending acts of gratitude and appreciation will be a rewarding area of ongoing exploratory practice and one that can contribute positively to wellbeing.

A Way Forward

Tracking and sharing personal data can encourage us to compare ourselves to others, yet the research on happiness and self-compassion show that this can negatively impact our wellbeing. Reflecting on our thoughts, emotions, and behaviors is essential to personal growth, but obsessive rumination contributes to depression. How do we design technologies that support practices beneficial to wellbeing without reinforcing associated problems? We do not claim to have the answer, but we suggest the following design principles as safeguards in favor of healthy balance.

Design Implications
Principles for Supporting Self-Awareness and Reflection

  * Understand the pitfalls. Cultivating an awareness and understanding of the pitfalls that exist surrounding reflection and self-tracking will help us (designers) to avoid inadvertently supporting them.
  * Design for self-compassion, gratitude, and mindfulness. Research suggests that underscoring our efforts with principles of self-compassion, gratitude, and mindfulness will help prevent comparison, self-criticism, narcissism, and entitlement.
  * Acknowledge the limitations of technology and lean toward reflective support. Honoring the diversity and complexity of people while acknowledging the limitations of what can be provided by technology will often mean employing reflective feedback and avoiding highly prescriptive and constrained solutions. Outside of human-mediated medical intervention, what we don’t know about our users and their contexts will always outstrip what we do know, so providing them feedback for making better decisions will often be more widely effective than providing specific instruction.
  * Allow for nonabsolute categories. When we present the analysis of personal data to support inferences about states of mind or behavior, we should not be constrained to predefined categories. This idea is based on the work by Ellen Langer, who showed the negative impact of preconceptions on creativity. In her studies, Langer (e.g., Langer & Piper, 1987) provided evidence that when people come to a task with strong, absolute conceptions, for example when they are told, “This is a %___%,” in contrast to a conditional conception, as when they are told, “This could be a %___%,” they are much less likely to adapt or be creative with the concept.

Follow the Ongoing Research

Although better understanding of how we can design safeguards and adaptations to ensure that wellbeing interventions genuinely promote wellbeing will require ongoing research, understanding that these tensions exist and following research in antidotal concepts such as self-compassion, gratitude, altruism, and sympathetic joy are sure to be critical to approaching an optimal balance over time.

And now, after alluding a number of times to the incredible promise of mindfulness for wellbeing, we turn to this unique state and practice in the next chapter—to its definition, its many positive correlates, and the strategies that have been proven to promote it.
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====== 8 Self-Awareness and Self-Compassion ======
It was late in his life, as he faced his executioners, that one of the world’s greatest thinkers would conclude that death was preferable to giving up philosophy. To those in his midst he declared simply: “The unexamined life is not worth living.” Socrates would go on to swallow hemlock for his crimes—crimes that would come to represent a pinnacle of human achievement.

A century earlier ancient India had yielded another of the world’s greatest philosophers, Gautama Buddha, who said “You are what you think. All that you are arises from your thoughts. With your thoughts you make your world.” The core Buddhist tenet summarized by the Four Noble Truths explains that in order to end our experience of suffering, we must first understand the workings of our mind. We must be able to recognize our thoughts, our emotions, our reactions, and their precursors, as they are the roots of our suffering.

Methods for self-examination, introspection, and self-awareness have since been refined by generations of philosophers, and more recently by modern Western psychologists from Sigmund Freud to Aaron Beck.

Now, in the second decade of the twenty-first century, cognitive behavioral therapy (CBT) has gone online: experience sampling solicits mood updates via smart phone, and the quantified-self movement inspires growing innovation in personal data analysis. But is it reasonable to expect any deeper understanding of our personal thoughts and emotions to arise from data? Can artificial intelligence, sophisticated machine-learning algorithms, and digital visualizations really help us to know ourselves better? If they did, would we be better for it?

In this chapter, we look at the state of the art in technology-mediated reflection, the varied approaches that have been applied to this endeavor, and the research emerging from its use. We also look at the foundations in psychology that underpin efforts toward greater self-awareness and how they are linked to increases in wellbeing. We look at both the potentials and the problems that may be associated with technological intervention into our inner lives, while deliberately evading the question, Would the Buddha have tweeted “feeling one with the universe” from under the Bodhi Tree?

Know Thyself
Why bother? Is self-knowledge merely philosophically virtuous or actually important to greater happiness and flourishing? Methods for CBT demonstrate that increased self-awareness can indeed improve wellbeing. In fact, a healthy chunk of the research and clinical work in modern psychology relies on promoting awareness of one’s thoughts, emotions, and behaviors in order to effectively treat mental illnesses such as anxiety and depression.

Neuroscientist Richard Davidson (e.g., Davidson & Begley, 2012) has identified recognizable neurophysiological patterns associated with self-awareness. He has found that greater self-awareness is associated with increased activity in the insula (involved in consciousness, emotion, and body regulation) and that long-time meditators have larger insulas.

If self-awareness is important to personal growth and wellbeing, what can we do to develop it, and how can technology play a part in that development? The answer is most frequently sought in various forms of reflection, introspection, and mindfulness training. There is an impressive wealth of evidence for the effectiveness of mindfulness practice on wellbeing, including the work of Jon Kabat-Zinn and researchers at the Oxford Mindfulness Centre. Davidson cites neurophysiological evidence for the effectiveness of mindfulness practice both for increasing self-awareness and for tempering potential negative side effects that might accompany this awareness (e.g., hypersensitivity and anxiety). We reserve mindfulness, however, for the next chapter and deal with it as a factor of wellbeing in its own right. In this chapter, we focus on reflection.

According to twentieth-century philosopher, psychologist, and educational reformer John Dewey (2013), it is essential for education to develop the skills of reflection: “while we cannot learn or be taught to think, we do have to learn to think well, especially acquire the general habit of reflection.” For Dewey, reflection is an act of reason that is often but not always directed to understanding the external world. He was also very willing to apply this objective rationality to more emotional concerns. “The meanings of honesty, sympathy, hatred, fear, must be grasped by having them presented in an individual’s first hand experience.” Applying Dewey’s imperative to modern technology design suggests that systems intended to help people reflect on emotions should do so from the context of the user’s own life experiences rather than from abstract concepts. Of course, emotions are just one category of things upon which one might introspect. There are at least three others.

Targets of Reflection
When we speak of self-awareness or reflection, there are various interpretations regarding what it is we are becoming aware of or upon which we are reflecting. Over time there have been proposals for various targets of reflective thought, which can roughly be synthesized into four main categories.

Cognitive awareness is what we believe we know about the world around us and our own lives. Understanding this aspect in ourselves is generally referred to as “metacognition,” a term introduced by John Flavell in the late 1970s (Flavell, 1979). A great deal of research on how to build computer systems to support metacognition is available in the learning technologies literature.

Affective awareness involves awareness of our states of mind, in particular moods and emotions. Strategies and computer tools that help us track and reflect on our moods and emotions have been developed in the areas of psychotherapy and affective computing and as commercial tools. Some of these tools are discussed later in this chapter.

Experiential awareness is our awareness of the integrated aspects of cognition, affect, and behavior (including their external and internal triggers). The combination of these three aspects of “experience” (cognition, affect, and behavior) is at the core of CBT, which we describe in more detail later in this chapter.

Character traits, or those aspects of personality that are dispositional qualities, are a fourth set of mental aspects upon which we can reflect. We won’t be focusing on this last category in this chapter because there is insufficient research to draw on at this stage. We delve more deeply into the cognitive, affective, and experiential in the next three sections.

Cognitive Awareness and Metacognition
Metacognitive skills, or the ability to “know what one knows,” are important to many aspects of life experience, from setting realistic personal targets to self-regulating learning activity. A number of researchers have explored metacognition in the context of designing intelligent tutoring systems. These systems can support learning by supporting metacognition—for example, encouraging self-explanation (as a way of scaffolding reflection) and setting personalized goals. In addition to using metacognition strategies as a feature, other systems have focused on developing metacognitive skills per se, based on the principles for metacognitive tutoring proposed by John R. Anderson and his colleagues (Anderson, Corbett, Koedinger, & Pelletier, 1995).

Outside of the learning context, researchers have considered the impact of metacognitive skills on mental health (particularly in the context of cognitive therapies), linking them to wellbeing. We come back to these examples later in the chapter.

Affective Awareness and Emotional Intelligence
The literature on emotional intelligence (EI) has focused on affective awareness—namely, the skills required to recognize and regulate our emotions in a way that is consistent with a model of emotional functioning (Mayer & Salovey, 1995). We discussed emotional intelligence in chapter 3, but it’s worth coming back to Daniel Goleman’s (1998) five EI skills because they provide a useful breakdown of affective awareness as it might contribute to wellbeing. The five EI skills are:

  * Self-awareness (the ability to recognize our own emotions)
  * Self-regulation (the ability to control them)
  * Motivation (passion for what we do)
  * Empathy (the ability to recognize others’ emotions, which is covered in depth in chapter 10)
  * Social skills, in particular the ability to manage relationships with others

Most of the research on EI links it to concrete measures of success, such as productivity in the workplace. Nevertheless, there is also some initial evidence for a link between EI and psychological wellbeing. For example, a number of studies have looked at how well EI predicts wellbeing as defined by standard SWB measures. Emma Gallagher and Dianne Vella-Brodrick (2008) analyzed the impact of EI on SWB, removing the effect of other factors such as personality and sociodemographic variables (e.g., wealth). They analyzed measures of life satisfaction, positive and negative affect, social support, EI, personality, and social desirability from the self-reports of 267 adults. Their analyses showed that EI and social support as well as their interaction effects significantly predicted SWB. Further research on these links would be helpful in demonstrating whether interventions to develop EI also increase wellbeing.

Experiential Awareness and Reflection
Perhaps the most promising strategies for reflection are those that target the holistic relationships between thoughts, feelings, and behaviors. The development of such understanding is at the core of some mindfulness practices and cognitive therapy, both of which have been empirically linked to wellbeing.

It’s worth pointing out the challenges of interdisciplinary research around a construct with as many varied interpretations as self-reflection. Each discipline looks at different aspects of reflection and takes a different focus. On the one hand, we might approach reflection, as Socrates, Dewey, and Peter Salovey have, as a retrospective dimension of thought. Even within this category approaches differ; Socrates’s point of departure was moral philosophy; Dewey’s interest was cognition and education; and other authors have studied reflection from the perspective of professional practice (e.g., Schön, 1983). In contrast, in mindfulness training and Buddhist psychology, reflection is generally rooted in the present. It is a present-moment self-awareness that observes thoughts, emotions, and behaviors as they arise, often in the context of deliberate contemplative practice.

The concept of reflection has been used in so many ways it risks becoming a bit of a catch-all. Therefore, in order for the concept to be useful to positive computing in a practical sense, it must first be contextualized. The adoption of any model of reflection for the development of technology will be shaped by (a) our motives for targeting reflection in the first place (What problem are we trying to solve? What activity are we trying to support?), (b) the development process we follow, and (c) the methods of evaluation we use.

By way of example, in the next section we discuss two contexts within which technologies can be (and have been) used to support reflection. The first is psychotherapy, in which reflecting on cognitive and behavioral patterns has been demonstrated to effect transformative experiences, especially for those with mental illness. In the second example, we discuss reflection at a more prosaic level and at a narrower granularity. We look at the practice of reflecting retrospectively on our daily behaviors, moods, and goals and at how new technologies, particularly in the area of personal informatics, can be used to collect behavioral data and scaffold the reflection process.

Reflection as a Strategy for Mental Health Treatment
Cognitive Behavioral Therapy

A number of psychotherapies focus on developing a self-understanding of the relationships between our thoughts, feelings, and behaviors. One of the most commonly used psychotherapies in the treatment of depression and anxiety is cognitive behavioral therapy. CBT was developed by Aaron T. Beck (Beck, Rush, Shaw, & Emery, 1987) and is closely related to rational emotive behavioral therapy developed by Albert Ellis (1973), both during the late 1950s. While Beck was treating patients using a psychoanalytic method, he began to notice how they, especially those with depression, often misinterpreted or had “cognitive distortions” relating to events in their lives. They would, for example, selectively obstruct certain thought processes or overgeneralize. For instance, a patient might interpret the fact that his spouse didn’t kiss him good-bye in the morning as evidence that he is no longer loved.

CBT is essentially based on the concept that the way we think influences the way we feel, which in turn influences the way we behave. This process, thinking–feeling–behaving, is part of an internal communication that people can access through reflection. The client can discover the meanings of such processes, in particular the triggers of irrational thinking and follow-up feelings, with the therapist’s help. The therapist often follows a Socratic questioning approach, scaffolding the client’s reflection so that he evaluates his assumptions and can modify his thinking. This systematic questioning (a.k.a. “talk therapy”) is combined with other activities such as role playing, writing in a diary, disputing irrational beliefs, and modifying language to be more positive, assertive, or playful.

Technology for CBT

Richard Layard, notable British economist and proponent of national wellbeing measures, has called on the UK government to invest both in increasing the provision of CBT and in teaching EI in schools in aid of improving national wellbeing. One strategy for increasing the reach of CBT programs in light of a shortage of trained therapists is through technology, and computers have already been successfully used to deliver such programs. In fact, computer-based CBT (CCBT) has been successful enough that in the United Kingdom the National Institute for Clinical Excellence considers Internet-delivered CBT a viable way of treating patients, in particular those with anxiety.

In a Health Technology Assessment for the UK National Health System, Eva Kaltenthaler and her colleagues (2006) compared the clinical and cost effectiveness of a number of online CBT products to traditional approaches. According to their analysis of 20 randomized controlled trial studies, there is evidence that CCBT is as effective as therapist CBT for the treatment of phobias and panic and is more cost effective for depression and anxiety. Moreover, using CCBT in conjunction with a therapist can reduce therapist time required.

It’s worth noting that we do not believe computers can reasonably replace human mental health professionals. Any such notion would reflect a lack of understanding regarding the complexity of mental illness and the mental health profession. We reject a people-replacement model of technology’s role in mental health, not only because of technology’s limited ability to be creative and empathic and to provide genuine human presence, but also because technology-based programs are largely generalized, incapable of making critical insights or adapting sufficiently to the nuance and variety in human personalities and circumstances. As such, technological systems are probably incapable of safely assisting with nontextbook, long-term, and life-threatening cases. Nevertheless, for certain types of mental health challenges, they could contribute significant help in, at least, the following four ways:

  * As complement to therapist treatment for a richer, more consistent, and possibly shorter treatment phase
  * As follow-up and maintenance after therapist sessions are complete
  * As triage where a shortage of qualified mental health professionals face far more people in need of help than can possibly be seen in one-on-one, hour-long sessions. Technology might be used to support more mild cases, while immediately directing those who may be in danger to professional help.
  * As a wider net for the many people who, although they are in need of professional help, do not seek it for many reasons such as stigma, fear, cost, and logistics. The anonymity and easy access provided by online programs can potentially foster flourishing in a much larger number of people. Some of these people may even proceed to seeking professional help once transitioned by such a process. Others may find the online program in itself successful in improving their lives.

To these ends, initial research is promising. In an Australian evaluation of a CCBT system (Mackinnon, Griffiths, & Christensen, 2008), three conditions were explored: the use of MoodGym, an Internet-based CBT intervention; the use of Bluepages, a website with information; and a control placebo group. Results showed that the Internet interventions reduced depression symptoms to a greater extent than the control group. This was true for a post-test, the 6-month follow-up, and a 12-month follow-up.

A UK randomized controlled trial of the efficacy of CCBT (Proudfoot, Ryden, Shapiro, Goldberg, & Gray, 2004) showed even stronger outcomes. The authors compared a commercial multimedia CCBT system (Beating the Blues1) with traditional treatment and found that “the computerised therapy improved depression, negative attributional style, work and social adjustment. … For anxiety and positive attributional style, treatment interacted with severity such that computerised therapy did better than usual treatment for more disturbed patients. Computerised therapy also led to greater satisfaction with treatment.”

These computer-based systems are exceptions in that they have been evaluated in peer-reviewed studies. Hundreds of other CCBT apps, many available for a few dollars at the app store, do not have the benefit of such evaluations. Most tend to be augmented diaries, providing users with a way to record events. Thoughts pertaining to these events can sometimes be labeled—for example, as “unhelpful” or “sad.” Other apps focus on specific activities (e.g., sleep, diet, and drinking).

For example, Drink Coach is an app developed by the Haringey Advisory Group on Alcohol, a UK group supporting those who suffer from alcohol misuse. The app focuses on scaffolding reflection on drinking habits. The user can record her alcohol consumption and the “risks” associated with it as well as set goals. The system tracks alcohol units and related calories consumed over time, and diary entries include fields for craving duration and intensity. The app also provides videos about mindfulness and breathing exercises that can help with cravings.

Panic Attacks is an app produced by myCBT Ltd. that focuses on anxiety disorders. It provides audio recordings designed to be calming, information on panic attacks, and a diary that helps challenge misinterpretations.

We hope to see more research and rigorous evaluation of these kinds of apps in the future so that we all can learn more about how best to design this kind of support.

Technology-Mediated Reflection for Wellbeing
The examples of CCBT in the previous section deal with mental health treatment. However, the focus of positive computing is mental health promotion. Of course, we have elected to spend significant time describing these e-therapy approaches in part because they are some of the most sophisticated and well-evaluated examples of technologies directed at psychological functioning that exist today, but also because you don’t have to be ill to benefit from them. For example, it is not only the clinically depressed that find themselves having irrational thoughts, making overgeneralizations, or “catastrophizing.” Most of us are prone to the kind of mental habits that in larger amounts and combined with other symptoms characterize clinical anxiety and depression. Even those of us who are mentally healthy can thus benefit from the exercises and practice of detecting cognitive distortions. Reducing these habits in the general population can be seen not only as a preventative measure that builds resilience to illness, but also as a promotional measure that improves the level of wellbeing in the population overall.

If we look at the taxonomy of Internet-based medical interventions (Barak, Klein, & Proudfoot, 2009), it’s interesting to imagine how many of these interventions might be reformulated as promotional (rather than therapeutic) strategies. Moreover, how many of them might be incorporated into the very tools we already use in our everyday activities? Although the notion of promotional strategies incorporated into everyday software remains somewhat forward thinking, there are a handful of examples of dedicated promotional tools. Among them is Echo.

Echo is a smartphone application for recording everyday experiences and reflecting on them afterward, created in collaboration by researchers in California (Isaacs, Konrad, Walendowski, & Lennig, 2013). They conducted three system deployments with 44 users who generated more than 12,000 recordings and reflections, and they found that the activity supported by the system (which they call “technology-mediated reflection”) successfully improved wellbeing. This study is instructive not only because it demonstrates an effective design for supporting reflection to promote wellbeing, but also because it serves as a model for rigorous evaluation of positive-computing technologies. The research team assessed results using four separate psychological metrics: the Subjective Happiness Scale, Satisfaction with Life Scale, Psychological General Well-Being Index, and the Mindfulness Attention Awareness Scale.

Echo is just one example of the ways in which many of the exercises that a therapist would use are translatable to online delivery. For example, role-playing (think videogames), writing reflections (as with Echo and writing tools that we analyze in the next section), disputing irrational beliefs (for example, by scaffolding the reasoning process online), and modifying language (Could we have a positive-computing spell checker for reflective practice?) are all therapeutic strategies amenable to technology support. Clearly, there is much room for innovation in this area, and we look forward to future examples of technologies for the treatment, prevention, and promotion of mental health.

Reflection versus Direct Instruction
Reflective approaches to self-improvement are particularly appropriate for technology intervention in that they avoid the path of giving direct prescriptive instruction, which is a risky approach for any generalized tool to take. Moreover, reflective feedback has greater potential in situations where a client’s full story and context are not clear, which is almost always the case online.

In one of the sidebars in chapter 3, Harvard social media scholar danah boyd describes the digital street—a poignant reminder of how public our lives are and the difficult considerations that have arisen around this new reality. The lives we see in these digital streets are visible only in fragments. Even when we want to put these fragments to good use—for example, by identifying people at risk in order to point them in the right direction for help—our task is not trivial because we remain unaware of the full context of their situation. In these instances, reflective interventions, where a person is (a) encouraged to contextualize issues for themselves, (b) provided with information upon which to reflect, and (c) not given direct advice to take a specific action, may pose the best solution.

In a project with the Young and Well Cooperative Research Centre, we currently are exploring how a computer could automatically detect cognitive distortions in what young people write in blogs and on social networks. Using natural-language processing, we hope to detect expressions of all-or-nothing thinking, overgeneralization, discounting the positive, and jumping to conclusions. Technologies that can recognize cognitive distortions might form the foundation for tools that help people recognize these distortions for themselves. Needless to say, the careful design of these tools will be critical. No one, least of all teenagers, wants a virtual agent telling them what he should or shouldn’t post on his wall. But creatively and respectfully applied, with deference to autonomy, values, participation, and preferences, such technologies just might promote greater wellbeing on unprecedented scale.

Reflection for Wellness and Wellbeing—Quantifying the Self
Personal informatics, personal analytics, quantified self, self-tracking—these are all terms that refer to technologies used by individuals to collect and analyze data about their behaviors (and sometimes about their moods or emotions).

The area has grown on multiple fronts in both business and academia. Independent software developers and entrepreneurs can take credit for the impressive speed at which it has advanced. Take Buster Benson—a software developer in California and a pioneering example of a user/developer combo who has immersed himself with gusto into the world of quantified self. Benson has been quantifying himself since 2000.2 In one of his earliest forays, he tracked his state of mind using a “mood-o-meter,” a system he used to log and publish information about his morale, his health, and his sleep in concert with data on his alcohol and caffeine consumption. Using this application, he would rate these variables on a scale of 1 to 10, describe the day’s events in a short diary entry, and produce plots and visualizations for him and others to view.

He points out that others found the visualizations valuable because they could better judge when to approach him to ask for a favor, and he found himself paying attention to the way in which he was perceived by others. Over the years he has built and often commercialized many more personal informatics tools. His quest, he says, is “to find meaning,” and he carries out this quest by exploring data.

On another leg of the quest, after beginning a personal diary in order to track how his moods changed over time, he created the website 750words.com. The website is similar to a blog but differs in its constraints and purpose. It has a much simpler interface, limits posts to 750 words, and is designed to produce reports from these personal journal entries. A simple report might read, “Rafael Calvo started at 7:10 pm and finished 470 words at 7:57 pm, for a total of 47 minutes of typing at 10 words per minute. Rafael Calvo was distracted 4 times while writing.” Benson integrates the information from this tool with photo streams, geomapping, emotional state tracking, the number of unresponded emails he has sitting in his inbox, tweets received, and myriad other data streams to produce an unusually detailed public portrait of his personal life.3

In a recent seminar, Benson shared his conflicting opinions of self-tracking, sometimes viewing it simply as compulsive behavior, sometimes finding meaning in the data, and sometimes finding that although there is meaning in it, it’s “hundreds of years away.”4 He also found that after years of trying to find numbers that better match to his internal reality, more generic labels (or Boolean scores) seem best suited to the job. In one of his apps, he uses factors such as sleep, physical activity, meaningful work, time spent with his son, and so on to produce a single average measure.

Although Benson’s personal voyage isn’t scientific research, it is instructive. The experiences of people such as Benson who have been “quantifying themselves” for such long periods of time can provide useful insights in the way that diary and case study methods have been successfully used in HCI research. Sure, his concern for privacy is clearly lower than average, or perhaps he’s simply courageous in the name of computer science, but the result is an intriguing public experiment (performance artwork, even) that anyone can explore in order to reflect on the potential benefits, risks, limitations, inanity, or promise of the thoroughly quantified life.

Together with people like Benson, entrepreneurs and developers are putting together all kinds of apps that help people reflect on their behaviors in light of data collected about almost any aspect of their lives. At the website PersonalInformatics.org, you can find a catalog with hundreds of applications, from those for diet and exercise to those for tracking your sex life.

Some developers integrate GPS data into applications that calculate running or cycling itineraries, distance benchmarks, speed, and approximate calories burned. Some companies add a website or a custom gadget to the mix. The gadget-based business model pertains to some of the most commercially successful products, such as those offered by Fitbit (in March 2013 valued at more than $300 million).

Possibly the most significant personal tracking experiences are occurring online, where people view visualizations, interact with gamified motivational features, and share data and goals with others. In our lab, we are currently developing a set of tools that combine observational data (e.g., from health gadgets and traffic logs) with self-reported data (e.g., responses to a CES-D questionnaire or other psychological instruments), aiming for a more holistic view.

Reflection will continue to play a central role in our technology- supported efforts in supporting self-awareness. However, relentless in our determination not to neglect the caveats, we know this chapter would not be complete without the case against too much reflection as a method for self-awareness to improve wellbeing.

Staring at Our Own Reflection
Can self-awareness (or at least reflection) go too far? When does healthy reflection become unhealthy rumination or obsessive self-focus? Will encouraging reflection simply feed the apparent rising trend in narcissism that is also linked to depression? Should we encourage self-focus when self-focus is known to be a conspicuous characteristic of depression? In a linguistic analysis of student essays, Stephanie Rude, Eva-Maria Gortner, and James Pennebaker (2004) found that depressed individuals used the word I more frequently than did their nondepressed counterparts.

These issues highlight the challenges inherent in supporting the “right kind” and “right amount” of reflection. As a way forward, we summarize some of the elucidating research on self-compassion and gratitude, potential antidotes to the risks of overreflection.

Rumination and Self-Criticism

Sonja Lyubomirsky, among many other psychologists, has studied rumination and its impact on depression, problem-solving ability, and sociability. While comparing people who tend to be happier with those who tend to be unhappier to the average, positive-psychology researchers have found a link between unhappiness and too much self-reflection, including “dwelling” (or rumination) and self-criticism. According to Lyubomirsky’s (2001) research, happier people tend to self-reflect about moods and outcomes less than unhappier people.

Rumination, in which thinking is mostly about past events (rather than the worrisome future), tends to focus on issues of loss and bereavement, self-worth, and so on. Myriad studies have consistently shown that rumination is associated with depression and other mental health problems and that focusing attention on oneself can also increase and extend the length of depressive episodes. In the article “Rethinking Rumination” (Nolen-Hoeksema, Wisco, & Lyubomirsky, 2008), the authors explain how rumination is not just correlated with neuroticism, perfectionism, and other negative cognitive styles but also mediates “the relationship between depression, neuroticism, negative inferential styles, dysfunctional attitudes, self-criticism, dependency and neediness.”

However, according to this same article, it is also not clear which forms of self-reflection can be adaptive, positive, and instrumental in personal change or even just benign. Some researchers have tried to separate factors using the Ruminative Responses Scale and other scales in attempts to disentangle positive forms of reflection from otherwise negative rumination. Evidence suggests a difference between analytic and experiential self-focus (Watkins & Teasdale, 2004), the latter relating to the nonjudgmental present-focused observation found in mindfulness practice or what Susan Nolen-Hoeksema and her colleagues (2008) call “concrete rumination” or “mindful experiencing.” (We discuss mindfulness in the next chapter.)

This is perhaps why the generally present-focused and experiential process of self-reporting moods seems to increase emotional self-awareness, an important positive aspect of a number of psychotherapies. The positive impact of self-reports has been shown in studies where participants reported their moods via phone messages (Kaur et al., 2012) or as longer personal diary entries such as blogs (Ko & Kuo, 2009). Interestingly, the evidence suggests that mobile phone self-reports can help reduce the brooding component of rumination (which is the component with strongest correlation to depression) (Kaur et al., 2012).

Future research in positive computing can look at how technologies might be designed in such a way to detect signs of overthinking, brooding, or self-criticism and perhaps to shift focus to supporting antidotal practices such as mindfulness, connection to others, and change of perspective.

Self-Awareness versus Narcissism

Sometimes the barrage of inane status updates, blathering blogs, and twittering tweets conspire to create a cognitive and emotional cacophony that have driven many to one conclusion: the connected world is raising a Generation Me that believes everything they think and do is important and worthy of public display. These new tools begin to look less like they’re about connecting and more like they’re about performing.

To be fair, experimentation with any new tool will involve doing so clumsily at first. And certainly, we have already begun to adjust the way we use social media in light of these effects—for example, by filtering more, storing less, demanding finer privacy settings, and reporting spam. Western capitalist culture, especially in the United States, is frequently criticized for an overfocus on individualism, self-interest, and an overemphasis on self-esteem. A recent New York Times article reported that “Rutgers researchers classify 80 percent of Twitter users as ‘meformers’ who tweet mainly about themselves” (Tierney, 2013). Will tools for self-awareness and self-tracking simply reinforce this pattern, leading to a new wave of digital selfing?

Indeed, there’s compelling evidence that both narcissism and narcissistic personality disorder have increased among younger generations in the United States (Twenge & Foster, 2010; Twenge, Konrath, Foster, Campbell, & Bushman, 2008). This downside comes, perhaps predictably, on the tail of more positive increases of other individualistic traits such as self-esteem, agency, assertiveness, and extraversion. Of course, you could say that previous generations had personal experience with economic depression, world war, and civil rights battles, which probably did more to temper a sense of entitlement than microblogging and personal digital devices do. But the meta-analyses look at levels of narcissism among college students from the early 1980s to the present day, not among their grandparents. Although the causes are surely various (from changes in education to cultural attitudes, politics, and lifestyles—all potentially playing a part), if we speculate that our digital technologies (or perhaps, more accurately, the ways we have designed and used them thus far) are playing some role in increasing levels of narcissism (and even if they’re not to blame), it’s sensible to ask what we can do about it in the context of positive computing. Contemporary researchers such as Paul Gilbert and Kristin Neff are among those who have spent the past decade investigating the potential of self-compassion to provide a more balanced way forward. While self-compassion might at first blush sound like just another “selfism,” it critically incorporates a broader perspective and a sense of shared humanity that, combined with gratitude, may be a key strategy for keeping reflection in balance.

Self-Esteem versus Self-Compassion
If you grew up with Barney the purple dinosaur, you’ll remember the theme song: “Cause you are special, special, everyone is special, everyone in his or her own way. …” Dorian recalls her father scoffing cynically at the oxymoronic notion that everyone is special. Of course, growing up in a working-class family on the rural outskirts of Pittsburgh meant that if you wanted to feel special, you had to work for it. We now know young children benefit greatly from praise, encouragement, and affirmation of their competence and potential, which is why research on self-esteem has been incredibly important to the way educational institutions now prepare children for success in life. Still, according to some, there has been a downside to the approaches we’ve taken to boosting self-esteem. Described charmingly as the “Lake Woebegone Effect” (in reference to radio personality Garrison Keillor’s fictional hometown, where “all women are strong, all men are good-looking, and all children are above average”), researchers have found that self-esteem that is contingent on external achievement or dependent on proof of perpetual above-averageness can lead to depression or narcissism down the track.

Psychologist Kristin Neff (2011) at the University of Texas, Austin, draws attention to the American obsession with needing to be above average. “In our incredibly competitive society, being average is unacceptable. We have to be special and above average to feel we have any worth at all. The problem, of course, is that it is impossible for everyone to be above average at the same time.” She cites research that shows how we struggle to maintain the fragile sense of specialness required for our self-esteem by inflating our self-evaluations and putting others down to feel superior. It’s hard not to think of all the “reality” TV shows and gossip magazines that in their condescending parade of the sensational sell us the opportunity to feel superior to others.

Neff goes on to unravel the consequences of a societal love affair with self-esteem, referencing grade inflation and the problems with a construct that is frequently contingent on external measures such as appearance, academic achievement, work performance, and social approval. “Contingent self-esteem drives people to obsess about the implications of negative events for self-worth, making them more vulnerable to depression and reduced self-concept clarity.” Although she emphasizes that there are certainly healthy forms of self-esteem and there is much research linking self-esteem to wellbeing, she argues that these benefits can be found without the downsides in a notion of self-compassion.

Paul Gilbert (2009, 2010) introduced compassion-focused therapy in the past decade as a novel way to help people who suffer from high levels of shame and self-criticism. The concept of self-compassion may be new to Western psychology, but it is certainly not new to humanity. Gilbert credits Buddhist psychology as a source for compassion-focused therapy because it centers on compassion in its practice (Buddhist loving-kindness meditation begins with compassion for oneself).

According to Neff (2011), “self-compassion entails three main components which overlap and mutually interact: Self-kindness versus self- judgment, feelings of common humanity versus isolation, and mindfulness versus over-identification.” Self-compassion has been correlated to increased wellbeing in multiple ways. It has also been shown to be a highly effective predictor of quality of life (Van Dam, Sheppard, Forsyth, & Earleywine, 2011) and has been correlated to other aspects of interest to positive-computing work, such as increased self-improvement motivation and reduced risk of Internet addiction. Laura Bernard and John Curry (2011) provide a summary of wellbeing correlates and suggest intervention strategies that could begin to inspire work in positive computing.

Gratitude and Appreciation

For a final antidote to over-focus on the self, and one that also fosters wellbeing in its own right, we turn to gratitude. The practice of gratitude in various forms (from thank-you letters to gratitude journals) has consistently been shown to increase wellbeing (for reviews see: Emmons & McCullough, 2004; Watkins, Woodward, Stone, & Kolts, 2003; Wood, Froh, & Geraghty, 2010). Christine Carter (2011), Director of Berkeley’s Greater Good Science Center, recommends gratitude practice for curbing a sense of entitlement in our children as well as for fostering positive relationships: “Our culture glorifies independence and undervalues how much others help; we see our blessings as hard earned … appreciation is one of the most important ways that we teach our kids to form strong relationships with others … expressing gratitude is about expressing just how deep those connections run.”

Design for gratitude already makes a few appearances in the virtual world. There are apps available to support gratitude practices (such as gratitude journals), games occasionally include opportunities for gratitude (e.g., Hay Day allows players to send thank you cards when help is provided by other players in the game), and the Learning Solutions website transformed the ubiquitous “like” into the more gratitude-focused “I appreciate this.” Creative thinking around how we can support users in experiencing and extending acts of gratitude and appreciation will be a rewarding area of ongoing exploratory practice and one that can contribute positively to wellbeing.

A Way Forward

Tracking and sharing personal data can encourage us to compare ourselves to others, yet the research on happiness and self-compassion show that this can negatively impact our wellbeing. Reflecting on our thoughts, emotions, and behaviors is essential to personal growth, but obsessive rumination contributes to depression. How do we design technologies that support practices beneficial to wellbeing without reinforcing associated problems? We do not claim to have the answer, but we suggest the following design principles as safeguards in favor of healthy balance.

Design Implications
Principles for Supporting Self-Awareness and Reflection

  * Understand the pitfalls. Cultivating an awareness and understanding of the pitfalls that exist surrounding reflection and self-tracking will help us (designers) to avoid inadvertently supporting them.
  * Design for self-compassion, gratitude, and mindfulness. Research suggests that underscoring our efforts with principles of self-compassion, gratitude, and mindfulness will help prevent comparison, self-criticism, narcissism, and entitlement.
  * Acknowledge the limitations of technology and lean toward reflective support. Honoring the diversity and complexity of people while acknowledging the limitations of what can be provided by technology will often mean employing reflective feedback and avoiding highly prescriptive and constrained solutions. Outside of human-mediated medical intervention, what we don’t know about our users and their contexts will always outstrip what we do know, so providing them feedback for making better decisions will often be more widely effective than providing specific instruction.
  * Allow for nonabsolute categories. When we present the analysis of personal data to support inferences about states of mind or behavior, we should not be constrained to predefined categories. This idea is based on the work by Ellen Langer, who showed the negative impact of preconceptions on creativity. In her studies, Langer (e.g., Langer & Piper, 1987) provided evidence that when people come to a task with strong, absolute conceptions, for example when they are told, “This is a ___,” in contrast to a conditional conception, as when they are told, “This could be a ___,” they are much less likely to adapt or be creative with the concept.

Follow the Ongoing Research

Although better understanding of how we can design safeguards and adaptations to ensure that wellbeing interventions genuinely promote wellbeing will require ongoing research, understanding that these tensions exist and following research in antidotal concepts such as self-compassion, gratitude, altruism, and sympathetic joy are sure to be critical to approaching an optimal balance over time.

And now, after alluding a number of times to the incredible promise of mindfulness for wellbeing, we turn to this unique state and practice in the next chapter—to its definition, its many positive correlates, and the strategies that have been proven to promote it.
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Notes
1. Beating the Blues can be found at ultrasis.com.
2. Buster Benson discusses why he self-tracks in the video at goo.gl/Ds1kY.
3. See Benson’s website at busterbenson.com.
4. See http://quantifiedself.com/2012/12/buster-benson-why-i-track/.
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