An Introduction to Positive Computing

“Don't be evil,” wrote Larry Page and Sergey Brin on the eve of Google's IPO in 2004. Almost a decade later, Apple CEO Tim Cook opened the annual developer's conference with a tribute to emotional experience as part of a campaign in which Apple claimed to ask of their technologies: “Will it make life better? Does it deserve to exist?”

These messages, however aspirational, resonate as overarching goals for a growing number of technologists who want to ensure the work they love to do is actively improving people's lives. If a technology doesn't improve the wellbeing of individuals, society, or the planet, should it exist?

The desire to “do good with technology” has emerged from a shared experience that technology has a major impact on how we live, that it has the capacity not only to increase stress and suffering, but also to improve lives individually and en masse. Indeed, the potential influence of digital and ubiquitous technologies is unprecedented. As you read this book, there are more mobile devices than people on the planet,[(See globalenvision.org/2013/12/18/infographic-there-are-more-mobile-devices-people-world)] and over the past decade we have watched them play a starring role in the politics of nations, in the politics of human relationships, and in the day-to-day social and emotional dynamics of our lives.

As a result, a growing number of technology professionals are seeking a realignment of business goals away from profit and toward social good?a sentiment manifest in the advent of social enterprise that places profit making secondary to a social purpose.[(New ways of structuring a profitable organization around a social benefit come in various forms, including “for-benefit organizations” (e.g., Mozilla), low-profit, limited liability corporations (L3Cs), and “social businesses,” proposed by Nobel Peace Prize winner Muhammad Yunus (see yunussb.com or his book Building Social Business). These new organizational models are sometimes described as being part of an emerging “fourth sector” (see fourthsector.net).)] Within the technology industry, we have seen the emergence of initiatives such as Games for Change, UX for Good, Wisdom 2.0, and Design for Good, while human?computer interaction (HCI) conferences provide ongoing testament to the growth in HCI for wellbeing, social impact, and peace.

This growing interest in social good among technology professionals is part of a larger emerging public concern for how our digital experience is impacting our emotions, our quality of life, and our happiness. We are gradually leaving behind the stark mechanical push for productivity and efficiency that characterized the early age of computing and maturing into a new era in which people demand that technology contribute to their wellbeing as well as to some kind of net social gain.

This sentiment reflects a broader renaissance of focus on humanistic values such as happiness and human potential that has begun to flourish across many different disciplines. A shift in priorities is now loud and clear among economists, politicians, and policymakers as they turn to statistical measures of wellbeing and “gross national happiness” as new indicators of success (Helliwell, Layard, & Sachs, 2012).[(In 2011, the United Nations officially put happiness on the global agenda, guided by the king of Bhutan's suggestion that “gross national happiness” complement gross national product as an indicator of social progress (see Ryback 2012). Although the current leader of Bhutan has since set aside the idea of gross national happiness, other measures of happiness and life satisfaction have been adopted by policymakers in the United Kingdom, where the National Wellbeing Programme (which carries the slogan “Measuring what matters”) was created as part of the Office for National Statistics. The World Happiness Report (Helliwell, Layard, & Sachs, 2012) provides a summary of national and international policy initiatives, which we discuss in more detail in chapter 3.)]

Similarly, in the past decade psychologists and psychiatrists have achieved hard-won disciplinary support for research that goes beyond illness into aspects of healthy functioning such as resilience, happiness, and altruism.[(In the past decade, psychologists such as Ed Diener, Barbara Fredrickson, Martin Seligman, Sonja Lyubomirsky, and Mihaly Csikszentmihalyi have been part of an effort to extend the focus of psychology and psychiatry beyond a disease model to study the factors of wellbeing and optimal functioning. We discuss positive psychology in chapter 2.)] In concert, neuroscientists have been exploring the physiology of exceptionally healthy minds and studying constructs such as empathy, mindfulness, and meditation empirically. Their findings are fueling action by educators and business leaders who are applying work on emotional intelligence and positive psychology to improve wellbeing among their students and workers (Joinson, McKenna, Postmes, & Reips, 2007; Ong & van Dulmen, 2006). It's inevitable that technology should begin to play a more sophisticated part in these multidisciplinary efforts toward supporting wellbeing.

In this book, we refer to this area of work?the design and development of technology to support psychological wellbeing and human potential? as “positive computing.”[(Various terms such as positive technologies, positive computing, and interaction design for emotional wellbeing have been used to refer to the potential for technology to support positive psychology and related themes. To our knowledge, it was Tomas Sander who first proposed the term positive computing in an article for the edited book Positive Psychology as Social Change in 2011. Guiseppe Riva and colleagues use the term positive technology in the cyberpsychology context (we look at this work in greater detail in chapter 2).)] We believe we are seeing the beginning of an important shift in the focus of modern technologies in which multidisciplinary efforts to support human flourishing are helping to shape thinking around how we design for digital experience.

In the same way that economists are measuring wellbeing at the national level and psychologists have been measuring it at an individual level for decades, it's time to consciously and systematically consider wellbeing measures in the design and evaluation of technology.

That isn't to say it will be easy. Understanding the impact of technology on individuals and on society is fraught with the challenges common to understanding any highly complex system. Cultural, social, ethical, and psychological variables will inevitably conspire to create a complex, nuanced, and challenging space for investigation. This suggests that partnering with social scientists (old hands at dealing empirically with multifaceted human systems) will be absolutely vital to success.

A simple glance at modern media suggests that the public is eager for those of us working in technology to take on this challenge. Best-seller lists abound with books on happiness as well as with books on how technology is affecting it. Warnings that technology is degrading our intelligence and inducing stress sit alongside promises of how it will save the world.[(We would include here The Shallows by N. Carr, Alone Together by S. Turkle, Nudge by R. Thaler and C. Sunstein, and also Flourish and Authentic Happiness by M. Seligman among others.)]

What's clear is that many of us are interested in (and even nervous about) how these pervasive tools are affecting us, and we seek out ways of getting a handle on the situation. After all, it's arguably our fundamental goal in life as human beings to pursue happiness, and in the modern world we're either going to do so with the help of technology or in spite of it.

Of course, some might argue that technological progress in and of itself is enough to improve wellbeing across the population. Tempting as it is to go along with that assumption, the evidence persists in suggesting otherwise.

Technological Progress a Poor Proxy for Wellbeing

Remarkably, despite major advancements and an incredible proliferation of devices, there is no evidence our modern tools have made us psychologically healthier or happier today than we were 20 years ago.[(Longitudinal studies by economists show that although wealth has tripled in the United States over the past 30 years, increases in life satisfaction have been marginal. This increase in wealth has likewise come with a significant increase in digital technology use, yet with no significant increase in life satisfaction. Even if we don't expect wellbeing measures to follow Moore's law, a correlation with wellbeing and technology should show more than marginal increases. See Helliwell, Layard, & Sachs 2012 for details.)] In other words, just as wealth has proven to be an inadequate proxy for a nation's wellbeing (Kahneman, Krueger, Schkade, Schwarz, & Stone, 2006), technology use has proven similarly inadequate as a surrogate for increased wellbeing in an individual or across a population.

However, if digital technologies are not actively supporting our wellbeing, it is simply because we have yet to consider it in the design cycle of technology. This oversight has occurred for many reasons, including a historical position among engineers and computer scientists that makes us more comfortable staying clear of the difficult-to-quantify and value-laden aspects of psychological impact. In other words, wellbeing has been not only traditionally overlooked but even consciously excluded from consideration owing to a legacy of industry discomfort with certain aspects of humanness.

The Human-Machine Legacy

Although there are significant exceptions (including the critical work in values-sensitive design and other efforts in HCI), few technology professionals have begun adding user wellbeing to their brief. In fact, just try mentioning happiness or wellbeing at a seminar for software engineers, and you're guaranteed some eyebrow raising (or that special breed of academic heckling). In his book Texture, Richard H. R. Harper (2010) attributes the pragmatic and behaviorist mindset that dominates HCI to the early influence of Alan Turing and Norbert Wiener.

Turing believed he was inventing a new discipline, one that dealt with algorithms. But this vision also included a view of the human. As it happens, Wiener thought that the science he was inventing, cybernetics, was all about people, even though his science was enormously mathematical, and hence quite close to what Turing thought he was doing. But the world view that these individuals have produced is one in which people?the users?turn out to be not very human at all. They have humanlike capacities and humanlike behaviors to be sure, but they are so reduced in their sensibilities that the humanness has been taken out. … Those who adopt Turing's view assume that what goes on inside the [human] machine itself is not only invisible but also somehow tricky and best avoided.

Harper makes no claim to being immune to this influence, and he shares insightful examples of technology development projects that failed to predict actual human use: “We recognized that issues of human action were relevant here, but our instincts were to avoid them; Turing's aversion to moral overtones encouraged us away.” He goes on to add that the public has likewise learned to think in the same way about themselves: “people think of themselves as machines … and worry about optimizing their performance.”

In attempting to unpack the Turing?Wiener legacy further, we have found that researchers in the previously mentioned eyebrow-raising category generally take one of four positions:

• The first (which we call the “positive dogmatic”) argues that technological progress itself is enough to make the world a better place; as countries become more technologically advanced, they become wealthier, more educated, and healthier, and when you're rich, educated, and healthy, you'll be happy. In this view, a technological singularity leads to utopia.
• A second group (which we call the “negative dogmatic” or “modern luddite”) believes that technology is inherently negative because it increases things such as unemployment, loneliness, stress, depression, and so on.
• The third group (agnostics) argue that it is impossible to say if products have positive or negative effects on wellbeing because, as a matter of principle, you can't measure that kind of thing.
• And finally, the fourth group is what Sextus Empiricus would call “skeptics” because they question the very existence of concepts such as wellbeing, happiness, and emotion in the first place.

Although we believe this is changing, we have found that our industry's traditional view of humans, useful as it has been to invention historically, creates barriers to progress as we get to a point where devices - far from being the mammoth expert-handled machines they once were - have become embedded into the daily experiences that shape all of us.

Nevertheless, some technologists remain reluctant to go beyond the apparent safety of a machine view of users. They are understandably wary of the empirical challenges that this change presents and skeptical of the feasibility of delving into psychological and subjective issues such as wellbeing within their field - and rightfully so, as it is entirely true that the technology field alone is not equipped for such a task. It has neither sufficient experience nor appropriate methodologies for dealing with the complexities of human psychological wellbeing, which is why multidisciplinary partnership is crucial. Partnerships with psychologists, anthropologists, sociologists, and educational researchers are already common within branches of HCI, so following in these footsteps should not require too drastic a leap.

Overall, in discussions with field leaders about positive computing, we find our colleagues are most likely to feel uncertain about the feasibility of measuring a concept as apparently nebulous and personal as wellbeing. Fortunately, on that point social science has spent decades refining instruments for precisely this purpose.

Measuring What Matters

Indeed, positive computing may appear out of reach at first glance, in the way that “user experience” felt fuzzy and impractical at the turn of the millennium. Although in technology fields we have little experience with measuring psychological impact, fields such as psychology and psychiatry proffer a wealth of empirically validated methodologies and best practice prerequisite to taking on this challenge.

For example, researchers have been measuring and assessing attributes such as happiness, quality of life, and subjective wellbeing since at least the 1970s (Fordyce, 1977). There are now more than 1,400 wellbeing and quality-of-life instruments for various specific subgroups (customized to age, culture, religion, context, etc.) and thousands of studies validating these instruments.[(The Australian Quality of Life Centre maintains a useful directory of research instruments. For example, the Personal Wellbeing Index has separate versions for adults, preschoolers, school children, and those with cognitive disabilities (see deakin.edu.au/research/acqol/instruments/instrument.php). You can figure out how you would score on the CESD-R (R = Revised) scale at cesd-r.com.)]

Two of the most widely used measures of wellbeing are the Center for Epidemiological Studies?Depression (CES-D) Scale, which has been used in more than 23,000 studies, and the Global Assessment of Functioning Scale used by psychiatrists and psychologists in clinical and research settings. Doctors, insurance companies, and government agencies rely on these measures to make decisions about treatment, benefits, and spending.

Recent technological advances in areas such as affective computing, computer vision, and data mining are also making inroads. Technology can now help us to better understand people's emotional experience through the analysis of text, facial expression, physiology, interaction, and behavioral analytics. We can also learn from research in cybertherapies and educational technologies, both of which seek to combine information about user behavior, cognition, and affect to inform their work.

Research and practice in medicine and the social sciences have shown us that measuring wellbeing and related factors not only is entirely feasible but has been well established for a number of decades. But is there any evidence that the technologies we build might actually be recruited to have a positive impact on wellbeing? Again, the work of psychologists has paved the way.

Studies in psychology have already combined the use of wellbeing measures with digital technologies for the delivery of Internet-based “interventions” (interventions are therapeutic or promotional efforts to improve mental or physical health). The Journal of Medical Internet Research and the Journal of Cyberpsychology, Behavior, and Social Networking are two of the most highly ranked journals publishing in this area. IEEE Transactions on Affective Computing also publishes research on the emotional impact of computers, but from an engineering perspective. Psychology research continues to uncover strategies empirically shown to lead to increases in long-term wellbeing, many of which are detailed later in this book.

Although psychologists have developed many proven ways to strengthen our mental resources, we spend much more time with digital technologies than we do with psychologists; digital technologies have unparalleled demographic reach. As psychology researchers Stephen Schueller and Acacia Parks (2012) have said, “The science of internet [sic] interventions can be advanced through expanding options and strategies to promote worldwide wellbeing.”

As an example of sheer numbers, in 2012 researchers at Facebook published a study in Nature that measured the impact of three interface-design variations on social participation behavior (Bond et al., 2012). This randomized control trial had a whopping 61 million participants and succeeded in showing how a small design change can have impressive consequences on user thinking and behavior.

We currently go about designing new technologies without any sense of how our design decisions will impact our users' psychological health and flourishing. Imagine the effects of taking that aspect into account, even just a little bit. Wellbeing-driven improvements to digital experiences have the unique potential to effect population-wide positive change.

Developments in the field of positive computing will have the side effect of giving us a way to critically measure aspirational missions and grandiose claims. Promises such as “do no evil” and “make the world a better place” are currently little more than marketing vagaries. We ought to be better equipped to bring rigor to these kinds of aspirations, to challenge them effectively, and to encourage integrity. For example, when a company such as Google makes the claim that its technology will make a better world,9 we should be able to assess this claim in a meaningful way from multiple perspectives, including wellbeing, sustainability and social impact. Positive computing will get us part of the way by allowing us to do so from the perspective of human psychological wellbeing. This approach will provide one piece to the puzzle of proof with regard to whether a technology does indeed deserve to exist.

The Walk-Through

In this book, we hope to support the work of current trailblazers and to facilitate future research and practice by synthesizing multidisciplinary theory, knowledge, and methodologies into a consolidated foundation for a rigorous and prosperous field. In part I, we look at fields outside of computing, such as psychology, economics, and education, as well as at pioneering work within computing that can support or already has begun to address the improvement of wellbeing.

We are privileged to be able to include perspectives from various experts from disciplines such as psychology, neuroscience, and HCI as sidebars throughout the book. Jeremy Bailenson, Timothy Bickmore, danah boyd, Jane Burns, David Caruso, Mihaly Csikszentmihalyi, Felicia Huppert, Mary-Helen Immordino-Yang, Adele Krusche, Jane McGonigal, Jonathan Nicholas, Don Norman, Yvonne Rogers, and J. Mark G. Williams have generously shared aspects of their vision for how future technology might take part in supporting wellbeing.

After a review of the foundational literature, in chapter 5 we propose a theoretical framework and consider appropriate methods for the research and evaluation of positive-computing technologies. We also make efforts to sketch out a scope for the field, looking not only at technologies specially built to support wellbeing, but also at the potential for wellbeing research to enhance the experience of all technology.

In part II, we zoom in on a number of specific wellbeing factors as identified in the literature, specifically positive emotions, motivation, engagement, self-awareness, mindfulness, empathy, compassion, and altruism. We look at the literature that correlates these factors to wellbeing, what kinds of strategies exist for fostering them, how technology has already been used to support their development, and possibilities for future work.

Before coming to a close, we take a critical look at issues such as privacy, paternalism, psychological complexity, and autonomy?all of which need to be judiciously explored as part of future work.

Finally, we envision a way forward, including a pragmatic exploration of how current and future work in positive computing might be funded and sustained.

One of the goals of this book is to make a convincing case that considering wellbeing in the design of technology is not only entirely achievable, but also valuable, if not imperative, to building a digital environment that can make a happier and healthier (not just more productive) world. We also hope to show that to enter an age of ubiquitous computing while turning a blind eye to the influence of technology on wellbeing is to accept a kind of convenient ignorance of the real impact of our work and thus to limit our success as designers and developers.

The potential for technology to become a vehicle for worldwide flourishing is huge, and the intentions of enthusiastic professionals are genuine, but in order for our efforts to be effective they must be grounded in evidence and open to evaluation, and, in the end, they must prove themselves. This book attempts to take a first step in what we hope will be an ongoing rigorous and dynamic interdisciplinary journey toward digital experience that is very deeply human centered.

References

• Bond, R. M., Fariss, C. J., Jones, J. J., Kramer, A. D. I., Marlow, C., Settle, J. E., … Fowler, J. H. (2012). A 61-million-person experiment in social influence and political mobilization. Nature, 489(7415), 295-298.
• Fordyce, M. W. (1977). Development of a program to increase happiness. Journal of Counseling Psychology, 24(6), 511-521.
• Harper, R. H. R. (2010). Texture: Human expression in the age of communications overload. Cambridge, MA: MIT Press.
• Helliwell, J., Layard, R., & Sachs, J. (2012). World happiness report. New York: Earth Institute.
• Joinson, A., McKenna, K., Postmes, T., & Reips, U.-D. (Eds.). (2007). The Oxford handbook of Internet psychology (p. 520). Oxford, UK: Oxford University Press.
• Kahneman, D., Krueger, A. B., Schkade, D. A., Schwarz, N. S., & Stone, A. A. (2006). Would you be happier if you were richer? A focusing illusion. Science, 312(5782), 1908-1910.
• Ong, A. D., & van Dulmen, M. H. M. (Eds.). (2006). Oxford handbook of methods in positive psychology. New York: Oxford University Press.
• Ryback, T.?W. (2012). The U.N. happiness project. New York Times, March 28. At http://nytimes.com/2012/03/29/opinion/the-un-happiness-project.html?pagewanted=all&_r=0
• Schueller, S. M., & Parks, A. C. (2012). Disseminating self-help: Positive psychology exercises in an online trial. Journal of Medical Internet Research, 14(3), e63.

~~REFNOTES~~

“괴물이 되지는 말자.” 래리 페이지(Larry Page)와 세르게이 브린(Sergey Brin)이 2004년 구글의 기업공개 안내서에 썼던 말이다. 거의 10년 후, 애플의 CEO 팀 쿡(Tim Cook)은 연례 개발자회의를 애플은 “우리의 기술이 삶을 더 낫게 하는 것인가? 그런 존재가 있는가?”를 묻겠다는 캠페인에서 겪은 정서적 경험에 대한 헌사로 시작했다.

이런 메시지는 다소 야심적인 것이기는 하지만, 자신이 사랑하는 일이 분명히 사람들의 삶을 더 낫게 하는 것이기를 바라는 많은 기술자들의 중요한 목표로 자리잡았다. 기술이 개인과 사회 나아가 전 지구적인 웰빙을 개선하지 않는 것이라면, 존재해야 할 가??있는가?

“기술로 좋은 일을 한다”는 소망은 기술이 우리의 삶에 중요한 영향을 미친다는 공통의 경험 즉, 기술은 스트레스와 괴로움을 배가하는 것인 동시에 개인이나 집단의 삶을 향상시키기도 한다는 경험을 공유하면서 나타나게 되었다. 실제로 디지털과 유비퀴터스 기술의 잠재적 영향력은 전례가 없는 것이다. 당신이 이 책을 읽고 있는 지금, 모바일 장비(device)는 지구상의 인간의 수보다도 많으며,미주

지난 10년 간 그것이 국가의 정치나 인간관계의 정치 그리고 일상적 삶에서 매일 경험하는 사회적 역동과 감정 등에 빼어난 역할을 하고 있음을 목격하고 있다.
이에 따라 사업의 목적을 이윤에서 사회적 선으로 재정립하는 기술전문가들이 점차 늘고 있는데, 이런 분위기는 사회적 목적을 우선시하고 이윤창출을 부차적인 것으로 간주하는 사회적기업의 출현에서 두드러지는 정서이다.
우리는 기술산업 분야에서 Games for Change, UX for Good, Wisdom 2.0, Design for Good과 같은 새로운 개념의 출현을 겪었고 인간-컴퓨터 상호작용(HCI)에 관한 국제회의들에서는 HCI의 성장이 웰빙과 사회적 영향력, 평화를 위한 방향으로 이루어지고 있다는 증거들이 꾸준히 발표되고 있다.
기술전문가들 사이에서 보이는 사회적 선에 대한 관심증대는 우리의 디지털 경험이 우리의 정서와 삶의 질, 행복에 어떤 영향을 미치는가에 대한 대중적 관심의 출현이라는 더 커다란 경향의 일부이다. 우리는 삭막하고 기계적으로 생산성과 효율성을 추종하던 컴퓨팅 초기의 특징을 뒤로하고 점차 기술이 개인의 웰빙뿐아니라 일종의 총체적 사회적 이득에 기여해야 한다는 사람들의 요구에 부응해야 하는 새로운 시대로 성장해??있다.
이런 분위기는 다양한 분야에서 꽃피우기 시작한 행복과 인간 잠재력과 같은 인본적 가치에 초점을 두는 광범한 르네상스를 반영하는 것이다. 이제 성공의 새로운 지표로 웰빙과 “국민총행복”같은 통계치를 강조하는 경제학자들과 정치학자들, 정책가들 사이에서는 우선순위의 변동이 분명하게 드러나고 있다(Helliwell, Layard, & Sachs, 2012).

마찬가지로, 지난 10년 간 심리학자들과 정신의학자들은 질병을 넘어서 회복탄력성과 행복, 이타성 같은 건강한 측면의 기능에 대한 연구들에 대해 탄탄한 학문적 지지를 획득하였다.
또한 신경과학자들은 예외적인 건강한 마음의 생리학을 탐구하고 공감과 마음챙김, 명상과 같은 개념들을 실증적으로 연구해왔다. 이들의 연구결과는 교육과 기업분야의 지도자들이 자신의 학생이나 근로자의 웰빙증진을 위한 작업에 정서지능과 긍정심리학을 적용하도록 불을 붙였다( ). 기술이 이러한 웰빙을 지원하는 학제적인 노력에서 좀 더 세련된 역할을 시작해야 한다는 것은 불가피한 것이다.
이 책에서 말하는 “긍정컴퓨팅”이란 심리적 웰빙과 인간잠재력 계발을 지원하는 기술의 디자인과 개발 작업 분야를 뜻한다.
우리는 인간성의 만개를 지원하는 학제적인 노력들 덕분에 디지털 경험을 어떻게 설계해야할 것인가에 관한 우리의 생각이 바뀌고 있는, 현대기술의 초점에 중요한 변화가 일어나기 시작하는 시기에 있다고 본다.
경제학자들이 웰빙을 국가수준에서 측정하고 심리학자들이 수 십년 간 개인수준에서 웰빙을 측정해온 것과 같은 방식으로 기술의 디자인과 평가에 웰빙측정치를 의식적이고 체계적으로 고려해야 할 시기가 되었다.
그렇다고 그 작업이 쉬울 것이라는 말은 아니다. 기술이 개인과 사회에 미치는 영향을 이해하려면 모든 복잡한 시스템을 이해하려 할 때와 마찬가지로 넘어야 할 장애들이 많다. 문화와 사회적, 인종적, 심리적 변수들이 연구장면을 복잡미묘하고 극복하기 쉽지 않은 공간으로 만들게 될 것이다. 이는 성공을 위해서는 (인간이라는 체계의 다양한 측면을 경험적으로 다루는 데에 능숙한)사회과학자들과 연계하는 것이 분명히 필수적임을 시사한다.
현대의 매체를 둘러보면 기술분야에서 일하는 우리들이 이런 도전을 받아들이기를 대중사회가 갈망하고 있음을 쉽게 알 수 있다. 베스트셀러 목록에는 행복에 관한 책들은 물론이고 기술이 어떻게 행복을 좌우하는가에 관한 책들이 매우 많이 들어있다. 기술이 우리의 지능을 쇠퇴시키고 스트레스를 유발하는지에 관한 경고와 기술이 세상을 구할 것이라는 약속들이 함께 놓여있다.

명백한 것은 우리 중 많은 사람들이 이미 대중화된 기술들이 우리??어떤 영향을 미치는지에 흥미를 (그리고 우려를) 가지고 있고, 이런 상황을 다룰 수 있는 방법을 모색하고 잇다는 것이다. 결국 인간으로서 우리 삶의 근본적 목표는 행복을 추구하는 것이며, 현대세상에서 그런 목표추구에 기술의 도움을 받거나 아니면 그런 도움 없이 ?킬?하는 것일 터이다.
물론, 어떤 이들은 기술적 진보는 그 자체로 전인류의 웰빙 향상에 충분한 것이라 주장할 지도 모른다. 이런 가정을 받아들이고 가는 것은 유혹적이긴 하지만, 증거들은 계속해서 그렇지 않다는 것을 보여준다.

기술적 진보는 웰빙의 허접한 유사품에 불과하다(technological progress as a poor proxy for wellbeing)

디바이스의 성능이 엄청 향상되고 믿을 수 없을 정도로 널리 확산되어 있지만, 이런 우리의 현대적 기기들이 지난 20년 전과 비교할 때 우리를 심리적으로 더 건강하고 행복하게 만들어 주었다는 증거는 없다.
다시 말하면, 부가 한 국가의 웰빙의 지표로서 부적절한 유사품에 불과한 것으로 판명된 것처럼( ), 기술의 사용도 개인이나 사회의 웰빙증가의 대리물로 적합하지 않다는 것이 판명되었다.
하지만, 만일 디지털 기술이 우리의 웰빙을 적극 돕는 것이 아니라면, 이는 그저 우리가 디지털 기술을 기술의 디자인 싸이클 내에서만 생각해서 그런 것이다. 이런 실수에는 여러 가지 이유가 있는데, 엔지니어와 컴퓨터과학자들이 심리적 영향과 같은 양화하기 어렵고 가?鰥㈏岵?측면을 비켜있는 것을 더 편안하게 여기게 한 역사적 위치도 한 가지 이유이다. 말하자면, 웰빙은 전통적으로 간과해왔고 때로는 의도적으로 고려대상에서 제외해왔는데, 이는 인간성의 어떤 측면들을 불편해하는 산업의 유산이다.

인간-기계의 유산 (The Human-Machine Legacy)

가?疵?디자인(value-sensitive design)분야의 중요한 작업들과 HCI 분야의 일부 노력들처럼 중요한 예외가 있기는 하지만, 기술 전문가들 중에서 자신의 설계안에 사용자의 웰빙을 추가하기 시작한 사람들은 매우 드물다. 사실 소프트웨어 엔지니어들의 세미나에서 당신이 행복이나 웰빙을 언급하면 눈썹을 찡그리며 언짢아하는(아니면, 학술적 비판을 가장한 야유를 보내는) 사람들이 있다는 것을 보장할 수 있다. 리차드 하퍼(Richard H. R. Harper, 2010)는 저서 Texture에서 HCI 분야에 만연한 실용주의적이고 행동주의적인 사고방식을 튜링(Alan Turing)과 와이너(Norbert Wiener)의 초기 영향 탓으로 돌렸다.

튜링은 자신이 알고리즘을 다루는 새로운 학문분야를 만든 것으로 믿었다. 하지만 이런 비전에는 인간에 대한 관점도 포함되어 있다. 그런 일이 일어나자 와이너는 자신이 발명한 과학인 사이버네틱스가 매우 수학적인 것이며 그래서 튜링자신이 스스로 하고있다고 생각한 작업과 매우 유사한 것이기는 하지만, 결국 모두 사람에 관한 과학이라고 생각했다. 하지만 이들 두 사람이 만들어 낸 세상에 대한 관점은 사람(사용자)을 결국 사람 아닌 것으로 바꾸어 버리는 것이었다. 그것은 사람같은 능력을 가지고 사람같은 행동을 했지만, 감수성이 몰락해버려서 인간성을 잃어버리게 되었다…… 튜링의 관점을 받아들이는 사람들은 [인간이라는] 기계의 안에서 벌어지는 일은 볼 수도 없을 뿐아니라 다루기 힘든 것이어서 피하는게 상책이라고 가정한다.

하퍼( )는 이런 영향을 벗어나는 것에 관해서는 아무런 주장도 하지 않았고, 실제 사람이 사용하지 않아서 실패한 기술개발사업의 통찰력있는 사례들을 제시하였다. “우리는 이 분야에서 인간의 행위라는 문제를 다루는 것이 적절하다는 것을 알았지만 본능적으로 그것을 회피하였다: 도덕적 함의에 대한 튜링의 혐오감이 우리도 그것에 거리를 두게 만들었던 것이다.” 그는 또한 대중도 자신들에 대해 마찬가지 방식으로 생각하는 것을 학습했다고 덧붙였다. “사람들은 자신을 기계라고 생각한다… 그리고 자신들의 활동을 최적화하는 것에 매달렸다.”
튜링과 와이너의 유산을 더 보여주려다 보니 우리는 앞서 언급한 눈썹 찌푸리는 부류의 연구자들을 다음과 같은 네 부류로 범주화할 수 있게되었다.

· 첫 부류(“긍정적 교조주의”라 명명한다)는 기술적 진보 그자체가 세상을 더 나은 곳으로 만들기에 충분하다고 주장한다. 나라가 기술적으로 진보할수록 더 부유해지며 더 많은 교육과 건강을 향유하게 되며, 부유하고 교율을 많이 받고 건강하면 행복해질 것이라고 본다. 이런 견해에서는 기술적 탁월함이 유토피아를 낳는다.
· 두 번째 부류(“부정적 교조주의” 또는 “현대판 러다이트”라 명명한다)는 기술이란 본래 부정적인데, 기술이 실업과 외로움, 스트레스, 우울 등을 증가시키기 때문이라고 믿는다.
· 세 번째 부류(불가지론자)는 생산품이 웰빙에 긍정적 효과라든가 부정적 효과가 있다고 말할 수 없는데, 이는 원칙적으로 우리가 그런 것들을 측정할 수 없기 때문이라고 주장한다.
· 네 번째 부류는 회의론자인 섹스투스(Sextus Empiricus)가 “회의론자(skeptics)“라 할만한 집단인데, 이들은 무엇보다 웰빙과 행복, 정서와 같은 개념 그 자체의 존재를 의심한다.

우리는 이런 상황이 변하고 있다고는 믿지만 역사적으로 많은 기술적 발명에 유용한 것이었던 우리 산업의 전통적 인간관은 더 이상의 진전에 장애가 되고 있음을 알게되었다. 즉 우리는 디바이스가 더 이상 전문가들만이 다룰 수 있었던 과거의 거대한 기계가 아니라 우리의 일상경험에 내재되어 우리 모두를 삶을 조형하는 그런 지점에 와있는 것이다.
그래도 어떤 기술자들은 사용자를 기계로 보는 일견 안전한 관점을 극복하기를 주저할 수도 있다. 이들이 이런 변화가 제공하는 경험적 도전을 경계하고 자신의 분야에서 웰빙과 같은 심리적이고 주관적인 문제를 탐구하는 것의 실현가능성에 회의적인 것은 이해할 만하며 또 그래야 한다. 왜냐하면, 기술분야 혼자만으로는 이런 과제를 할 준비가 충분하다고 할 수 없는 것이 분명한 사실이기 때문이다. 기술분야는 인간의 심리적 웰빙의 복잡성을 다룬 충분한 경험이나 적절한 방법론을 가지고 있지 못하며, 그래서 학제적 파트너쉽이 매우 결정적인 것이다. 심리학자와 인류학자, 사회학자, 교육학자들과 협업하는 것은 이미 HCI의 일부 분야에서는 상식이며, 이들의 발자취를 따르는 것은 그렇게 급진적인 도약을 필요로 하지 않을 것이다.
결론적으로, 긍정컴퓨팅에 관해 이 분야 리더들과 토론하면서 우리는 우리의 동료들이 웰빙과 같은 언뜻 보기에 모호하고 개인적인 개념을 측정하는 것의 가능성에 대부분 확신을 갖지 못하고 있다는 것을 알게 되었다. 다행스럽게도, 이 점에 관해 사회과학은 측정을 위해 수 십년에 걸쳐 측정도구를 세련화 해왔다.

문제의 개념들의 측정 (Measuring What Matters)

“사용자 경험”이 21세기의 초에는 어쩐지 혼란스럽고 비실용적인 느낌이 들었던 것처럼, 긍정컴퓨팅도 처음 볼 때는 손에 잡히지 않는 것처럼 보일 수 있다. 기술분야에서 우리가 심리적 경험을 측정한 경험이 거의 없기는 하지만 심리학이나 정신의학같은 분야는 이런 도전을 받아들일 수 있는 실증적으로 타당화한 방법론과 최고의 실행을 위한 풍부한 경험을 보여주고 있다.
예를 들어, 이 분야의 연구자들은 이미 1970년 대 부터 행복이나 삶의 질, 주관적 웰빙과 같은 속성들을 평가하고 측정해왔다( ). 다양한 특수 하위집단(나이와 문화, 종교, 맥락 등에 맞춘)용의 웰빙과 삶의 질 측정도구가 현재 1,400가지가 넘으며, 이런 측정도구를 타당화한 연구들이 수 천에 이른다.

가장 널리 쓰이는 두 가지 웰빙 측정도구는 23,000개 이상의 연구에 이용된 CES-D(Center for Epidemiological Studies-Depression) 척도와 임상이나 연구분야의 정신의학자와 심리학자들이 많이 사용하는 Global Assessment of Functioning Scale이다. 의사와 보험회사, 정부기관 등이 치료와 보상, 재정지출에 관한 의사결정을 할 때 이런 측정도구에 의존하고 있다.
affective computing, computer vision, data mining과 같은 분야에서 이루어진 최근의 기술적 진보도 도입되고 있다. 이제 기술은 문장과 얼굴표현, 생리, 상호작용 분석과 행동분석을 통해 사람들의 정서경험을 더 잘 이해하는 데에 도움을 주고 있다. 우리는 사이버치료와 교육기술 분야의 연구에서도 배울 수 있는데, 두 분야 모두 사용자의 행동과 인지, 정서에 관한 정보를 결합해서 그들의 작업에 필요한 정보를 얻는다.
의학과 사회과학의 연구와 실무는 웰빙이나 그와 관련된 요인들의 측정가능성을 보여주었고 수 십년에 걸쳐 잘 확립하였다. 하지만 우리가 만든 기술이 도입되어 실제로 웰빙에 긍정적 효과를 낼 수 있는가에 관한 증거가 있는가? 이에 관해서도 심리학자들의 작업이 길을 닦아놓았다.
이미 심리학의 연구들은 인터넷 기반의 “개입(개입이란 심신건강의 증진을 위한 치료나 촉진을 위한 노력을 말한다)“을 전달하기 위한 디지털 기술을 웰빙 측정치와 결합해서 쓰고 있다. Journal of Medical Internet Research와 Journal of Cyberpsychology, Behavior, and Social Networking은 이 분야에서 최고 수준의 학술지들이다. IEEE Transactions on Affective Computing도 컴퓨터의 정서효과에 관한 연구를 싣는데, 공학적 관점에서 이루어진다. 심리학 연구는 장기적인 웰빙을 증가시키는 것으로 입증된 전략들을 밝히려는 지속적 노력을 하고 있는데, 이 책의 뒷부분에서 자세히 다룰 것이다.
심리학자들이 정신적 자원을 강화하는 것으로 입증된 많은 방법을 개발했지만, 우리는 심리학자들과 협업하는 것보다는 디지털 기술에 더 많은 시간을 쓰고 있다. 디지털 기술은 비할 수 없는 인구학적 접근성을 가지고 있다. 심리학자인 슈엘러(Stephen Schueller)와 팍스(Acacia Parks)가 말했듯이, “인터넷 개입의 과학은 웰빙을 촉진하는 옵션과 전략을 전지구적으로 확장함으로써 진보할 수 있다.”
단순한 숫자의 예로, 2012년 Facebook 연구자들은 사회참여 행동에 대한 세 종류의 인터페이스 변종의 효과를 측정한 결과를 네이쳐(Nature)에 실었는데( ), 이 무선화 통제연구의 참여자는 6100만명까지 뛰었고 아주 작은 디자인의 변화만으로도 사용자의 사고와 행동에 상당한 영향을 줄 수 있다는 것을 성공적으로 보여주었다.
우리는 현재 디자인에 관한 우리의 결정이 사용자의 심리적 건강과 만개(flourishing)에 어떤 영향을 미칠지에 대한 아무런 감도 없이 새로운 기술을 설계하고 있다. 아주 적게라도 이런 부분을 고려했을 때의 효과를 상상해보라. 웰빙주도적으로 디지털 경험을 개선하는 것은 상당한 인구 수준의 긍정적 변화라는 독특한 효과를 낼 수 있는 가능성이 있다.
긍정컴퓨팅 분야의 발달은 야심찬 임무와 거창한 주장을 비판적으로 측정할 수 있는 방법을 제공한다는 부수적인 효과도 있을 것이다. “괴물짓 하지 말라”나 “세상을 더 나은 곳으로 만들자”와 같은 약속은 지금으로서는 마케팅을 위한 언사에 불과하다. 우리는 이런 종류의 야심을 엄격하게 검증하고 효과적으로 따져보고 통합성을 부추길 수 있는 준비를 갖추어야 한다. 예를 들어, 구글과 가은 회사가 자사의 기술이 세상을 더 나은 것으로 만든다고 주장할 때,
우리는 이런 주장을 웰빙이나 지속가능성, 사회적 영향을 포함한 다양한 관점에서 의미있는 방식으로 평가할 수 있어야 한다. 긍정컴퓨팅은 인간의 심리적 웰빙이라는 관점에서 우리가 그런 작업을 할 수 있는 역할을 제공하게 될 것이다. 이런 접근은 어떤 기술의 진정한 존재가치를 입증한다는 어려운 퍼즐의 한 조각을 제공할 것이다.

이 책의 구성과 전개(Walk-through)

우리는 이 책에서 학제적 이론과 지식, 방법론을 조율해서 단단하고 전망있는 분야를 위한 하나의 튼튼한 토대를 제공함으로써 기존 선구자들의 작업을 지원하고 미래의 연구를 자극하기를 바란다. 1부에서는 컴퓨팅 분야는 물론이고 리학과 경제학, 교육학 같은 컴퓨팅 이외의 분야들에서 이루어지는 도움 될 만한 선구적 작업이나 웰빙 증진을 이미 겨냥하고 있는 작업들을 살펴본다.
우리는 영광스럽게도 책 전체에 사이드바 형태로 심리학과 신경과학, HCI 같은 학문분야의 여러 전문가들의 견해를 포함시킬 수 있었다. ~ 사람이름~ 등은 향후 기술이 웰빙증진에 어떤 역할을 할 수 있을까에 관한 자신들의 전망을 기꺼이 공유해주었다.
기초문헌들을 개관한 후, 제 5장에서 우리는 긍정컴퓨팅의 이론적 틀을 제시하고 긍정컴퓨팅기술의 연구와 평가에 필요한 적절한 방법론을 생각해보았다. 우리는 이 분야의 전망을 그려내고자 했고 특별히 웰빙증진을 위해 고안된 기술 뿐아니라 모든 기술경험을 향상시킬 수 있는 웰빙연구의 가능성도 살펴보았다.
2부에서는 문헌들에서 밝혀진 긍정정서, 동기, 몰입, 자각, 마음챙김, 공감, 연민, 이타성 같은 구체적인 웰빙요인들 일부를 자세히 들여다보았다. 우리는 이런 요인들을 웰빙과 관련시킨 연구들을 살펴보았고 촉진전략으로 어떤 것들이 있는지, 기술이 이런 개발에 이미 어떻게 활용되는지, 그리고 향후 작업의 가능성이 무엇인지 살펴보았다.
마무리 짓기 전에, 우리는 사생활보호, 온정주의, 심리적 복잡성, 자율성과 같은 쟁점들을 비판적으로 살펴보았다. 이들 모두는 장래 작업의 일부로 신중하게 연구해야 할 필요가 있는 것들이다.
마지막으로 긍정컴퓨팅의 현재와 미래의 작업의 자금을 어떻게 모으고 지속시킬 수 있는가 하는 실용적인 문제를 포함해서 장래를 그려보았다.
이 책을 쓴 목적 중 하나는 더 행복하고 건강한(그저 더 생산적인 것이 아닌) 세상을 가능케하는 디지털 환경을 구축하기 위해 기술디자인에서 웰빙을 고려하는 것이 분명히 가능한 것이고 가치있는 일임을 확신할 수 있는 사례를 만드는 것이었다. 또한 우리는 기술이 웰빙에 미치는 영향에 눈을 감은채로 유비퀴터스 컴퓨팅의 시대로 진입하는 것은 우리의 작업이 미치는 실제 영향을 편하게 무시하는 것을 받아들이는 것이며 그래서 디자이너와 개발자로서 우리자신의 성공을 제한하는 것임을 보여주고자 한다.
기술이 세상의 만개를 위한 수단이 될 가능성은 엄청나며, 열렬한 전문가적 의지는 순수한 것이다. 하지만, 우리의 노력이 효과적이려면 그것은 증거에 기반한 것이어야 하며 평가에 열려있어야 한다. 그리고 결국에는 스스로 입증해야 한다. 이 책은 우리가 희망하는 것이 바로 깊은 인간중심의 디지털 경험을 향한 하나의 지속적이고 탄탄하며 역동적인 학제적 여행의 첫 단계로 시도한 것이다.

“How are you?” “How's it hanging?” “¿Como estas?” “중국어 안녕” Humanity's most frequently asked question is none other than an inquiry into another's wellbeing. Responses can vary in sincerity and sophistication: “Good, you?” “Wicked,” “Been better,” “The clouds of sorrow hang heavy.” Despite the variation, we are generally able to understand something of the state of someone's wellbeing following a simple greeting, and, more importantly, we solicit this information before we do anything else. It's not just a social norm?this feedback is vital to any decisions we make about what to do or say next.

Despite its quotidian and timeless nature, this question remains a formidable research question for scientists. Some of the difficulty lies in how science should define and empirically measure variations on “being well.” The search for an understanding of happiness and how to attain it is arguably a contender for the world's oldest profession. If we are to look to the academic pursuit of happiness as it has unfolded through time, we find ourselves journeying back at least as far as Aristotle and the Buddha, moving on through various schools of philosophy in Europe, Asia, and the Americas, until we land squarely in the modern world. Today the empirical search for wellbeing rests largely in the hands of psychologists and neuroscientists. Before we can involve digital technology more consciously in this pursuit, we'll need to understand the methods, theory, and practice – as they have been refined over hundreds of years – that have formed our complex modern-day understanding of human psychological wellbeing and its correlates.

This chapter looks at key elements of this understanding from the viewpoints of multiple specializations in psychology and the mind sciences. Needless to say, we could never be anything like comprehensive in one chapter about a subject to which libraries might be devoted, but we do aim to highlight core research and practices that may be particularly helpful to technology researchers and professionals looking to incorporate this knowledge into their practice.

“안녕하세요?”, “How are you?”, “니 하오마?” 사람이 가장 많이 묻는 질문이 다름아닌 상대방의 웰빙이다. 그 답변은 성실성과 미묘함에 따라 다르다. “좋아요, 당신은요?”, “완전 잡쳤어요” “별루예요”, “걱정이 많아요.” 다양한 변주가 있지만, 우리는 보통 단순한 인사에 이어 상대방의 웰빙상태를 어느 정도 이해할 수 있고, 더 중요한 것은 그런 정보를 얻어서 후속행동을 하려한다는 점이다. 이런 피드백은 단순한 사회적 규범이 아니라 우리가 어떤 말과 행동을 할지를 결정할 때 매우 중요한 정보가 된다.

이런 질문은 일상적이고 변함없이 이어져온 것이지만, 과학자들에게는 만만치 않은 연구문제로 남아있다. 어려운 점은 과학이 “잘 지낸다”의 다양한 측면을 어떻게 정의하고 경험적으로 측정할 것인가이다. 행복을 이해하려는 그리고 행복을 어떻게 얻는가를 알려는 작업은 세상에서 가장 오래된 전문가들의 도전꺼리였다. 시대에 걸쳐 전개된 행복에 대한 학술적 탐구를 살펴보려면, 최소한 아리스토텔레스와 붓다의 시대로 거슬러 올라가 유럽과 아시아, 미국의 다양한 철학적 전통을 거쳐 정확히 현대에 까지 도달해야 한다. 오늘날의 웰빙에 대한 경험적 연구는 주로 심리학자와 신경과학자들의 손에 달려있다. 이런 여정에 디지털 텍기술을 의도적으로 포함시키려면, 그 전에 수 백 년 동안 정교하게 발달한 인간의 심리적 웰빙에 관한 복잡한 현대적 방법론과 이론 및 실제를 이해할 필요가 있다.

이 장에서는 심리학과 마음과학 분야의 여러 독특한 관점을 이해하는데 필요한 핵심요소들을 살펴본다. 당연히 우리는 도서관을 통째로 뒤져야할 정도의 주제를 한 장으로 이해하는 일은 전혀 할 수는 없고 텍 연구자나 전문가들이 이런 지식을 자신의 작업에 통합하는데 특히 도움이 될 수 있는 핵심적인 연구와 실제를 조망하려는 것이다.

Paradigms of Wellbeing

Because the term happiness is so loaded with diverse interpretations (from fleeting hedonic pleasure to consumer spiritualism), scientists refer with greater precision to “optimal human functioning,” “optimal mental health,” “psychological flourishing,” or “psychological wellbeing.” It is to psychological wellbeing that we are dedicated in this book (and which we generally shorten simply to “wellbeing”). We occasionally also use the word flourishing, which has been widely adopted within the field of positive psychology as a way of emphasizing the optimal (rather than just average) end of possible human psychological functioning.

First off, we should acknowledge that there is an understanding common to all theories of wellbeing that it is contingent on certain basic material needs essential to survival, such as food, water, and shelter. What enhances wellbeing after basic needs are satisfied is more controversial and depends on how wellbeing is defined. For example, is wellbeing defined as the absence of mental dysfunction, in the way that physical health might be described as the absence of illness? Is wellbeing measured as an aggregate of pleasurable experiences (or what percentage of your life you experience positive emotions)? Perhaps it is best understood as the level to which one finds meaning in life and fulfills one”s greatest potential. These three perspectives roughly equate with the medical, hedonic, and eudaimonic approaches, which together form the foundations for modern theories of wellbeing. We look at each of these perspectives here.

It's important to note that none of the theories we include herein is simply hypothetical. Each is supported by ample empirical evidence and is associated with a series of measures and validated methodologies for research. The theories don”t so much contradict each other as they do focus on different components of wellbeing. For designers of technology, the underlying philosophical standpoint is perhaps less important than the strategies arising from these theories that have been proven to improve wellbeing in practice. We call on examples of these strategies throughout the book.

We believe it would be foolhardy for us to arbitrarily select a theory and posit it as the “right” choice for use in technology fields. Instead, we provide a review geared toward technology designers and imagine that professionals will select (as some already have) a theoretical perspective most appropriate to their context, the backgrounds of their teams, their goals, and their opportunities. The important point is that theory and supporting literature are essential. Work in positive computing might sail aimlessly or, worse, head into harmful waters if not anchored in research-based evidence. Therefore, it”s necessary to ground work in existing research, even if the specific literature from which we draw and the disciplinary lens through which we view the problem vary among projects.

For this reason, the framework we propose in chapter 5 is designed to support practitioners in grounding their efforts in the available theory and research, but without prescribing the use of a specific theory. For example, a combination of medical and positive-psychology models of wellbeing shape the work we do with the Young and Well Cooperative Research Centre. A research organization that focuses on the mental health of young people, the center is influenced by the psychologists with whom we work. Specifically, we work to build technologies that support certain psychological strengths such as resilience and autonomy by drawing on the literature in psychiatry and positive psychology. Our target audience contributes via participatory design practice. As new partners get involved in the project, we work with sensitivity to their background and understand that our approaches to influencing and measuring wellbeing may have to adapt over time. Later in the book we look more specifically at how various theories shape design and evaluation in different ways.

Paradigms of happiness

행복(happiness)이라는 용어에 대한 해석이 (일순간의 쾌락에서 소비자적 정신론에 이르기까지) 워낙 다양해서 과학자들은 좀 더 정교하게 “인간의 최적 기능”, “최적의 정신건강”, “심리적 만개(flourishing)”, “심리적 웰빙” 등의 용어를 사용한다. 우리가 이 책에서 채택한 용어는 심리적 웰빙이다(간단히 줄여서 웰빙이라고도 썼다). 또 가끔은 만개(flourishing)라는 용어도 썼는데, 이 말은 긍정심리학 분야에서 인간의 최적의(평균적이 아닌) 심리적 기능발휘를 강조하기 위해 널리 사용되는 개념이다.

먼저, 우리는 모든 웰빙 이론들이 음식이나 물, 거처와 같은 생존에 필요한 기본적인 물질적 욕구에 관해서는 공통적인 이해가 있다는 것을 인정해야 한다. 이런 기본적 욕구가 충족된 이후에 무엇이 웰빙을 향상시키는가에 관해서 많은 논란이 있고 주로 웰빙을 어떻게 정의하는가에 따라 달라진다. 예를 들어, 질병의 부재로 신체건강을 정의하는 것처럼 웰빙을 정신적 역기능의 부재로 정의하는가? 아니면, 웰빙을 즐거운 경험의 총합으로 측정하는가(또는 당신 삶에서 긍정적 정서를 경험하는 비율은 얼마나 되는가)? 아마도 웰빙은 삶에서 개인이 발견하는 의미의 수준과 자신의 최고의 잠재력을 충족시키는 수준으로 가장 잘 이해할 수 있을 것이다. 이상의 세 관점은 대략 의학적 접근, 쾌락적 접근, 그리고 행복론적 접근의 세 가지를 반영하는 것 일 텐데, 이들 관점들이 현대의 웰빙이론의 토대가 된다. 이들을 각각을 살펴보자.

우리가 여기서 다루는 이론들은 모두 단순히 가설적인 것이 아님을 주목해야 한다. 각각은 방대한 실증 증거의 지지를 받고 있으며 연구를 위한 일련의 측정치들과 타당한 방법론을 가지고 있다. 이 이론들은 서로 많이 상충되는 것은 아니며 다만 서로 다른 웰빙 요소들에 초점을 맞추고 있다. 텍 디자이너들에게는 실제 웰빙에 도움이 되는 것으로 입증된 이론에서 도출된 전략들이 기본적인 철학적 입장에 비해 더 중요할 것이다. 우리는 이 책 전체에서 이런 전략들의 사례를 보여줄 것이다.

하나의 이론을 인위적으로 선정해서 그것을 텍분야에 적용할 수 있는 “올바른” 선택이라고 주장하는 것은 쓸데없는 일이라고 믿는다. 그보다 우리가 텍 디자이너들에게 적합한 개관을 제시하면 전문가들이 자신의 맥락이나 팀의 배경, 목표, 기회 등에 가장 적합한 하나의 이론적 관점을 선택할 것이라고 믿는다(이미 그렇게 하는 사람들도 있지만). 중요한 것은 이론과 이를 지지하는 문헌들이 꼭 필요하다는 것이다. 이런 연구기반의 증거를 토대로 하지 않는다면, 긍정컴퓨팅의 작업은 정처없이 헤매거나 아니면 오히려 더 해로운 결과를 낳을 수도 있다. 따라서 우리가 어떤 문헌들을 참고할 것이고 어떤 학문적 관점에서 문제를 조망할 것인가는 프로젝트에 따라 달라지겠지만, 모든 작업은 필수적으로 기존의 연구를 토대로 해야 한다.

그래서, 우리가 제 5장에서 제시한 준거틀은 특정 이론에 전적으로 기대지 않고 현재 가용한 이론과 연구들을 토대로 구성함으로써 이를 바탕으로 실 사용자들이 자신들의 노력을 할 수 있게 설계한 것이다. 예를 들어, 우리가 영앤웰 합동연구센터(Young and Well Corporative Research Center)와 했던 작업은 의학모형과 긍정심리학 모형을 조합해서 수행한 것이다. 젊은이들의 정신건강에 초점을 맞춘 연구센터는 우리와 함께했던 심리학자들의 영향을 받았다. 특히 우리는 정신의학과 긍정심리학 문헌에서 이끌어 낸 회복탄력성(resilience)과 자율성(autonomy) 같은 심리적 강점을 지원하는 텍를 구축하고자 했다. 우리의 디자인 작업에는 표적고객도 참여하여 기여했다. 이 프로젝트에 새로운 파트너가 들어오면서 이들의 학술적 배경에 반응하는 작업을 했고 그 결과 웰빙을 측정하고 웰빙에 영향을 미치려는 우리의 접근법은 지속적으로 수정되었다. 이 책의 뒷부분에서 다양한 이론들이 어떻게 서로 다른 방식으로 디자인과 평가를 구축하게 되는지 더 자세히 살펴볼 것이다.

The Medical Model - Wellbeing as the Absence of Dysfunction

“How does that make you feel?” asked Sigmund. Despite its wild success as a cliche, if you seek professional assistance for any number of mental health problems, you are more likely to be asked about your appetite, your sleep patterns, and your sense of hopelessness. These questions are just a few in a standard slew that will allow your doctor to determine a diagnosis using a method recognized by the American Psychiatric Association (or the equivalent in your country).

These questions are not random. They have been carefully evaluated in hundreds of studies as accurate indicators of mental illness. Health-care workers, psychiatrists, and insurance companies rely on these methods to determine treatment, write prescriptions, initiate therapy, recommend hospitalization or calculate insurance coverage. The questions included in these standardized questionnaires have been refined over time and after considerable debate have been included in what is known as the Diagnostic and Statistical Manual (DSM), recognized by an organization of more than 36,000 American psychiatrists. Similarly, the International Classification of Diseases (ICD) is a statistical classification of diseases and related health problems (including mental health) published by the World Health Organization.

Psychiatrists, like other doctors, treat illness, dysfunction, and disease. You can't get much out of a doctor's appointment if there's nothing identifiably wrong with you. You can't, for example, drop in to see your general practitioner because you feel you're not thriving emotionally, you'd like to make wiser decisions, or you want to experience happiness more frequently. The initial evaluation made in the medical field is generally a binary one: you're either sick (and need treatment), or you're not (have a sticker). If you're not ill, your needs will generally fall outside of your doctor's area of professional responsibility.

But the focus of this book is on designing technologies to support and promote psychological wellbeing, not specifically for those who are ill and who seek help, but for the population at large, situated as we all are along a continuum from languishing to thriving. Only then can we promote improved life experience and optimum functioning for everyone. Promotion is differentiated from prevention and treatment in the health professions. For example, Mary Ellen O'Connell, Thomas Boat, and Kenneth Warner (2009) describe prevention as the avoidance of risk factors, whereas promotion strives to advance supportive conditions and protective factors. In this context, a medical or psychiatric model may seem inadequate. Nevertheless, even in the context of promotion, a medical model can contribute to our work in many ways.

First, psychiatric methods for diagnosis and intervention have a long history of empirical study and have been extremely successful at evolving diagnosis and treatment for many disorders. Moreover, when we work with teams of mental health professionals, they generally expect to use established medical instruments for assessing the impact of an intervention (even a promotional one). Take, for example, a prototypical randomized control trial evaluating the impact of a preventative intervention on young people at risk of depression (Clarke et al., 2001). In the study, research psychiatrists used cognitive restructuring therapy to prevent the symptoms of depression in young people who were mentally healthy but were nevertheless at risk because their parents were clinically depressed. The study evaluated a preventative intervention using two scales: the CES-D and the DSM-IV Global Assessment of Functioning, which are generally used both before the treatment and again in follow-ups (e.g., 15 months later). Clearly, these scales were especially appropriate in this case because the goal was preventing mental illness. But other studies have used these scales to measure increases in wellbeing by showing decreases in symptoms of depression or anxiety.

Another way to leverage a medical model for informing work in flourishing is to flip it upside down. Felicia Huppert, director of the Cambridge Well-being Institute and wellbeing adviser to the UK government, specializes in multidimensional approaches to the measure of wellbeing. In a recent study, Huppert and her colleague Timothy So (2013) examined various internationally accepted measures of depression, anxiety, and other forms of mental disorder. They aggregated common symptoms from the ICD and DSM (such as hopelessness, lack of interest, and negative emotions) and then looked to their mirror opposites (optimism, engagement, and positive emotions). In this way, they were able to identify two poles that formed ranges both below a tipping point for mental illness as well as above that point into flourishing. In doing so, they identified 10 components of wellbeing, which include competence, emotional stability, engagement, meaning, optimism, positive emotion, positive relationships, resilience, self-esteem, and vitality. These components were analyzed on a sample of 43,000 Europeans from 23 countries, providing national governments and the European Union with a new tool for evaluating progress.

One thing to keep in mind is that if you are designing for people suffering from mental health problems or for those people close to the sufferers, you must ensure that mental health experts are at the helm of your project. There are ethical and legal responsibilities associated with online therapeutic intervention?for example, requirements for allowing people at high risk to connect with professional help directly. For an organizational perspective on creating technologies designed specifically to promote mental health, see the sidebar by Jonathan Nicholas in this chapter.

Although the medical model of mental health will remain essential to work on wellbeing technology, many positive-computing projects will find the model too limited to be useful for promotion rather than treatment. In these cases, researchers often turn to hedonic and eudaimonic models of wellbeing.

의학모형-역기능 부재로서 웰빙

“그래서 기분이 어땠습니까?”하는 질문은 정신분석에서 전형적인 것이다. 이는 하나의 클리셰로는 대성공이지만, 당신이 정신건강상의 문제로 전문가의 도움을 받을 경우라면 식욕이나 수면양상, 무기력감 등에 대한 질문을 받을 가능성이 더 크다. 이런 질문은 미국정신의학회가 인정하는 방법으로 진단명을 확정하기 위해 의사들이 사용하는 표준적인 과정의 일부이다.

이런 질문은 무작위로 하는 것이 아니다. 모두 정신질환의 정확한 지표로 수 많은 연구들??세심하게 평가된 질문들이다. 건강관련 종사자, 정신과의사, 보험회사들은 이런 방법을 통해 치료법을 결정하고, 처방을 내고, 치료를 시작하고 입원을 권하거나 보험료를 계산한다. 이런 표준적 질문에 포함된 질문들은 오랜 기간에 걸쳐 정련된 것이며 상당한 논의를 거쳐 36,000명이 넘는 의사들의 조직인 미국정신의학회가 인정한 진단통계편람(DSM; Diagnostic and Statistical Manual)에 포함된 것들이다. 비슷한 것으로 국제보건기구(WHO)가 펴낸 질병 및 관련건강문제(정신건강을 포함)에 관한 통계적 분류인 국제질병분류(ICD; International Classification of Disease)가 있다.

다른 의사들과 마찬가지로 정신과의사들도 질병과 역기능, 질환을 치료한다. 만일 당신??뭔가 식별가능한 잘못된 것이 전혀 없다면, 의사와 약속을 잡을 수가 없다. 예를 들어, 당신은 그저 정서적으로 힘들다고 느끼거나 의사결정을 잘 할 수 없다거나, 좀 더 자주 행복을 느끼고 싶다거나 하는 이유로 가정의를 막바로 만날 수는 없다. 의학분야에서 내리는 첫 번째 평가는 보통 이분법적이다. 즉, 당신은 병이 있거나(그래서 치료를 필요로 하거나) 아니면 안아픈 것이다. 만일 질병이 없다면, 당신의 욕구는 의사들이 전문가적 책임을 질 것이 아닌 부차적인 것이다.

하지만 이 책의 초점은 심리적 웰빙을 촉진하고 지원하는 텍을 설계하는 것이며 질병이 있거나 그래서 도움을 필요로 하는 사람을 위한 것이 아니라 쇠약함과 건강함의 연속선 상에 있는 모든 사람들을 위한 것이다. 그래야 우리가 모든 사람들의 생활경험을 향상시키고 최적의 기능을 촉진할 수 있다. 촉진은 전문적인 건강분야의 치료나 예방과는 다르다. 예를 들어, 오코넬과 보트, 워너(O‘Connel, Boat, & Warner, 2009)는 예방은 위험요인의 회피인 반면 촉진은 지지적 조건과 보호요인을 향상시키려는 것이라고 설명한다. 이런 맥락에서 의학적인 또는 정신의학적 모형은 부적절한 것 같다. 그래도, 의학모형은 촉진이라는 맥락에서도 여러 가지로 우리의 작업에 기여할 수 있다.

첫째, 정신의학적 진단 및 개입법은 오랜 실증연구의 역사가 있고 다양한 질병의 진단과 치료에 지극히 효과적이었다. 게다가 정신건강전문가들과 팀으로 일할 때, 이들은 개입의 효과를 평가하는 잘 확립된 의학적 도구를 사용하기를 원한다(비록 촉진을 위한 것일지라도). 우울위험이 있는 젊은이를 위한 예방적 개입의 효과를 평가하는 전형적인 무선화 통제연구(randomized control trial)를 예로 들어보자( ). 이 연구에서 연구자는 정신적으로 건강하고 부모들도 임상적 우울이 없었던 위험요인이 전혀 없는 젊은이들의 우울증상을 예방하기위한 인지재구조화 치료를 사용했다. 이 연구는 CES-D와 DSM-IV Global Assessment of Functioning의 두 가지 척도를 개입전과 개입 후, 그리고 추수기간(15개월 후)에 측정하여 효과를 평가했다. 이 경우에 이 척도들은 특히 적절한 것인데, 왜냐하면 목적이 정신질환을 예방하는 것이었기 때문이다. 하지만 다른 연구들에서는 이 철도를 이용해서 우울이나 불안 증상의 감소를 보여줌으로써 웰빙의 증가를 측정하기도 했다.

의학모형을 적용하는 또 다른 방법은 만개(flourishing)에 관한 유익한 연구에서 했던 것처럼 그 모형을 뒤집어서 활용하는 것이다. 캠브리지 웰빙연구소의 소장이자 영국정부의 웰빙자문인 후퍼트(Felicia Hupert)는 웰빙측정에서 다차원적 접근법의 전문가이다. 최근 후퍼트와 소(Hupert, & So, 2013)는 국제적으로 인정받는 다양한 우울, 불안 기타 다른 정신장애 측정치들을 검증하였다. 이들은 ICD와 DSM에서 공통 증상들을 모아서(무망감, 흥미부족, 부적 정서와 같은) 그와 반대되는 것들(낙관성, 몰입, 정적 정서)을 살펴보았다. 이런 식으로 이들은 정신질환의 발화점 아래에서부터 만개에 이르는 범위의 두 양극단을 찾아낼 수 있었다. 그리하여 이들은 10개의 웰빙요소를 찾아냈는데, 유능감, 정서안정성, 몰입, 의미, 낙관성, 정적 정서, 정적 관계, 회복탄력성, 자존감과 활력이 그것이다. 23개국의 43,000명의 유럽인 표본을 대상으로 이들 요소들을 분석함으로써 웰빙 평가를 위한 새로운 도구를 각국 정부와 유럽연합에 제공하였다.

한 가지 염두에 둘 것은 만일 당신이 정신건강문제를 겪는 사람들이나 아니면 여기 근접하는 사람들을 위한 디자인을 한다면, 당신의 프로젝트에 정신건강 전문가들을 꼭 합류시켜야 한다는 것이다. 온라인 치료적 개입과 관련한 윤리적, 법적 책임의 문제가 있다. 예를 들어, 고위험군의 사람들?都?전문가의 직접적 도움이 가능하도록 필히 연결해주어야 한다. 특별히 정신건강 촉진을 위한 텍 디자인 개발에서 조직의 관점을 살펴보려면, 이 장의 sidebar의 니콜라스(Johnathan Nicolas)를 참고하라.

정신건강의 의학모형은 웰빙 텍을 위한 작업에 필수적인 것으로 남겠지만, 많은 긍정컴퓨팅 프로젝트는 이 모형이 치료가 아닌 촉진에 쓰기에는 너무 제한적임을 알게 될 것이다. 그런 경우 연구자들은 웰빙의 쾌락모형과 행복론적 모형으로 눈을 돌리게 된다.

Hedonic Psychology - Wellbeing as the Experience of Positive Emotion

When a friend asks, “How are you?” you probably don't base your response on a clinical diagnosis. We're guessing you're more likely to base it on how well your current circumstances match your intentions or simply how well you feel in that moment and have felt of late. If you're stuck working late on your taxes, your answer might be “miserable”; if you're enjoying a nice dinner with friends, it might be “fantastic.”

Thinking of wellbeing as something attained through the fulfillment of pleasures has a long history in philosophy. In Greece, Aristippus (born c. 435 BCE) taught that our highest ambition should be to experience as much pleasure as possible. Happiness, he claimed, can be measured as the sum of one's hedonic moments. Many others have written about hedonic pleasures since then. Famously (or infamously), the Marquis De Sade insisted that sensuous pleasures are the ultimate goal in life.

More recently and perhaps more convincingly, Daniel Kahneman, a psychologist and winner of the Nobel Prize in Economics, has looked deeply into the hedonic aspects of human psychology (see, e.g., Kahneman, Diener, & Schwarz, 1999). The field of “hedonic psychology” explores the ancient hedonic view but extends it beyond sensual pleasures to include all the things we judge as pleasant or unpleasant, including the attainment of goals or outcomes in any aspect of life. Kahneman's seminal research in hedonic psychology and behavioral economics has looked at how our quest for pleasurable experiences influences the way we act and think, which in turn manifests in the workings of our economies and societies.

Kahneman's work aggregates both in-the-moment and remembered experiences, and both types of experience have been used from a therapy perspective. In one study (Quoidbach, Berry, Hansenne, & Mikolajczak, 2010), 282 participants completed questionnaires that measured positive affect, life satisfaction, and overall happiness and inquired about their savoring and dampening strategies. Their results showed that mindfulness on the present moment and positive rumination promoted positive emotions and that sharing with others increased measures of life satisfaction. However, mind wandering reduced positive emotions, and ruminating on negative details reduced life satisfaction. Research like this points to the potential importance of remembered experience and focus as a part of technology design.

Modern industrial, architectural, and digital design owes much to a hedonic perspective of wellbeing. Artifacts are designed to heighten feelings of pleasure (at what Don Norman [2005] calls the visceral, behavioral, and reflective levels). User-experience designers seek experiences for their users that are delightful and pleasurable. Researchers in HCI have studied how devices can be built to regulate positive emotions (Hassenzahl & Beu, 2001), and companies such as Apple have built and strengthened a reputation on the idea of product as positive emotional experience.

In his book The Architecture of Happiness, philosopher Alain De Botton (2006), describes how art and architecture “talk” to those who experience them and change the way they feel and behave. One could argue that digital technology has the incredibly unique ability to turn the architectural monologue into an interactive dialogue. Digital technologies have the ability also to listen and adapt to what they hear. Imagine an empathic Siri or an emotionally attuned mobile phone. We discuss positive emotions more thoroughly as a factor for increasing wellbeing in chapter 7.

쾌락 심리학 - 긍정정서 경험이 웰빙이다

친구가 “요새 어때?” 하고 물을 때 그에 대해 임상적 진단을 토대로 대답하지는 않을 것이다. 그보다는 요즘 여건이 원하는 것과 얼마나 일치하는지 아니면 방금 전이나 지금의 기분이 어떤지를 토대로 대답을 할 것이다. 세금 때문에 늦게까지 씨름했다면 그 답은 아마 “끔찍해”일 것이고, 친구와 멋진 저녁식사를 하는 중이라면 “끝내줘” 같은 대답을 할 것이다.

웰빙을 즐거움의 충족을 통해 얻을 수 있는 어떤 것으로 보는 생각은 철학적 역사가 길다. 그리스의 철학자인 아리스토푸스( )는 가능한 최대한의 기쁨을 경험하는 것이 인간최고의 야망이어야 한다고 가르쳤다. 그는 행복이란 그 사람이 즐거웠던 순간의 합으로 측정할 수 있다고 주장했다. 그 이래로 다른 많은 사람들도 쾌락적 즐거움에 대해 언급했다. 유명한(악명높을 수도 있는) 사드( )는 감각적 쾌락이 인생궁극의 목표라고 주장했다.

노벨 경제학상을 받은 심리학자인 카네만( )은 최근 인간심리의 쾌락적 측면을 깊게 파헤쳤다( ). “쾌락심리학” 분야는 고대의 쾌락적 관점을 견지하지만 쾌락을 감각적 즐거움을 넘어서 우리가 유쾌하거나 불쾌하다고 판단하는 모든 것 즉, 인생의 모든 측면에서 나타나는 결과나 목표의 달성에 까지 확장시켰다. 쾌락심리학과 행동경제학에서 카네만의 중요한 연구는 즐거운 경험의 추구가 우리의 행위와 사고에 어떻게 영향을 미치며, 그것이 우리의 경제와 사회의 작용에 어떤 결과를 낳는가를 탐구한 것이다.

카네만의 작업은 현재의 경험과 과거의 경험을 합쳐서 이 두 종류의 경험 모두를 치료적 관점에서 활용하는 것이다. 한 연구에서( ), 참여자는 긍정 정서와 인생만족도, 전반적 행복을 측정하는 질문지에 응답하게 하고, 개인별 향유 및 감퇴 전략을 조사했다 역주. savoring dampening 전략. savoring은 긍정정서를 높이는데 도움이 되는 기법을 쓰는 것, dampening은 긍정정서를 오히려 줄이려는 기법을 쓰는 것
전자의 예: 행동적 표현(비언어적으로 긍정정서를 표현, 제스츄어, 표정 등) 현존(현재에 존재하기. 의식적으로 주의를 현재의 긍정사건에 초점화함), capitalising(긍정사건을 알리고 함께 축하하기 등), 상상(과거나 미래의 긍정사건을 생생하게 상상)
후자의 예: 억제, 주의분산, 실책찾기(긍정사건의 부정요소나 더 좋을 수 있었던 측면에 초점), 부정적 상상
. 그 결과, 현재 순간에 대한 마음챙김과 긍정적 반추는 긍정 정서를 증가시키며, 타인과 공유하는 것은 인생만족도 측정치를 높여주었다. 하지만, 산란한 마음은 긍정 정서를 감소시키며, 세세한 부정적인 것에 대한 반추는 인생만족도를 감소시켰다. 이런 연구는 기억경험과 주의초점이 텍 디자인의 일부로 중요할 수 있음을 지적하는 것이다.

현대의 산업 및 건축, 디지털 디자인은 웰빙에 대한 쾌락적 관점에 크게 의존하고 있다. 인공물들은 즐거운 느낌(Don Norman(2005)이 내장수준, 행동수준, 반영수준이라 부른 수준들에서)을 높이기 위해 설계된다. 사용자 경험(UX) 디자이너들은 사용자들의 즐겁고 기분좋은 경험을 추구한다. HCI 연구자들은 어떻게 하면 기기들을 긍정적인 정서를 조절할 수 있게 만들 수 있을까 연구한다( ). 애플같은 기업은 긍정적인 정서경험을 상품의 컨셉으로 한다는 명성을 구축하고 강화해왔다.

철학자인 알랭 드 보통( )은 자신의 저서 The Architecture of Happiness에서 예술과 건축이 이를 경험하는 사람들과 어떻게 “대화(talk)“해야 하는지, 어떻게 그들의 기분과 행동을 바꿀 수 있는지 설명하였다. 디지텍이 건축적 독백을 상호작용적 대화로 바꾸어 놓을 수 있는 상상이상의 독특한 힘을 가지고 있다고 주장할 수 있다. 디지텍은 귀기울일 수 있는 능력 뿐 아니라 이를 활용할 수 있는 능력도 가지고 있다. empathetic Siri나 정서적 공조가 가능한 휴대폰을 상상해보라. 웰빙증진의 한 요소로서 긍정정서에 대해서는 제 7장에서 더 상세하게 논의할 것이다.

Subjective Wellbeing - If You're Happy and You Know It, Let Us Know

Modern hedonic psychology has come a long way since Aristippus, but there are still problems with relegating evaluations of wellbeing to measures of fleeting emotions, which neglects the long-term overall stability that generally differentiates the concept of wellbeing from definitions of happiness. Kahneman, among others, has approached the need for a measure of longer-lasting characteristics by developing measures of wellbeing based on an individual's self-reported assessment of his or her own life satisfaction. “Subjective wellbeing” (SWB) (Kahneman, Diener, and Schwarz, 1999) consists of the cognitive and affective evaluations of one's life, including life events, life satisfaction, and fulfillment. These measures have been used, for example, for the development of national happiness indices (Diener, 2000; Diener & Suh, 2003), which are increasingly used to inform policymaking in multiple countries (examples are discussed in more detail in chapter 3 from within the multidisciplinary context of economics).

Subjective measures of wellbeing generally consist of three components: life satisfaction, the presence of positive mood, and the absence of negative mood. Life satisfaction is based on more reflective judgment, whereas the latter two refer to hedonic, affective components and can be either retrospective (as in “Over the last week I felt happy”) or present focused (as in “I feel happy”).

Most of the academic research in hedonic psychology has employed SWB measures that have shown substantial validity, as reflected by their agreement with other types of measures, such as third-party reports and biological measures of wellbeing (e.g., functional magnetic resonance imaging). A review by Ed Diener (2000), for example, highlights what was already known about subjective wellbeing and its different measures at the end of the twentieth century. Progress since then has come on several fronts, including new brain-imaging and genomic techniques (Fredrickson et al., 2013) and digitally facilitated methods for data collection and self-report.

Some research studies employ experience-sampling methods, in which emotions are repeatedly reported at random times during the day (Kahneman, 1999), and others have used diary methods (Bolger, Davis, & Rafaeli, 2003), also common in HCI research, to record memories of good and bad events or satisfaction about different aspects of life. According to these self-reports, people (those not living in extreme poverty or dire circumstances) tend to report being slightly happy. It is uncommon to find people reporting very high or very low levels of wellbeing.

On a time scale, an individual's self-reports can be classified as either “online” (as they occur in real time) or “recalled” (as reported in a diary) or as life evaluations that span long periods of time. These three time scales influence behavior in different ways. For example, Diener has shown that recalled feelings predict future behavior better than moment-to-moment feelings, a finding that relates to how we remember and judge our previous experiences. Because our personal values change very slowly, when we reflect on life satisfaction over a number of weeks or months, our judgments tend to be quite stable. However, reports of satisfaction with life will change over extended periods of time because both personal values and circumstances change more dramatically as we age and as time goes by.

One interesting thing about the effects of external circumstance on wellbeing is our ability to adapt to it. According to the “hedonic treadmill” concept, people adapt to or “get used to” all changes, be they good or bad, by returning to a personal neutral baseline. In other words, that new TV that fills you with happiness the day you buy it will have little to no effect on your happiness level in a month or so. More dramatic is the research showing smaller than expected changes to life satisfaction for both lottery winners and recent paraplegics after their life-changing events (Boyce & Wood, 2011; Brickman, Coates, & Janoff-Bulman, 1978). The hedonic treadmill concept could render efforts to increase happiness pointless if we simply return to a previous set point every time. However, the Boyce and Wood study (2011) shows the importance of personality and attitudes in predicting positive adaptation, and Diener and others have revised the hedonic treadmill model (Diener, Lucas, & Scollon, 2006), arguing that the set point is not neutral, but instead generally positive, and, more importantly, that it can be changed.

Genetic predispositions and environmental influences play out at the cultural level as well. Large-scale longitudinal databases of self-reports allow researchers to compare SWB across cultures and time, noting differences in various dimensions. For example, France is consistently associated with surprisingly low levels of subjective wellbeing, but Scandinavian countries with unusually high levels. Digging deeper, Huppert and So (2013) point out that although France has the highest ranking of all countries on engagement, it has the lowest ranking on self-esteem and is in the bottom for optimism and positive relationships. They highlight this as evidence for why multidimensional measures for wellbeing are critical to understanding differences between people and nations. National measures of wellbeing together with regional and cultural differences represent an ongoing area of study (Diener & Suh, 2003; Huppert et al., 2009). Measures such as the Happy Planet Index, World Happiness Report, and Eurobarometer provide a looking glass into the differences across countries and cultures as well as into the impact of national events and policy interventions. Some of this research is discussed in the next chapter.

Measures of life satisfaction, SWB, and quality of life are all widely used within various economic, social, and research contexts. But positive emotions are only part of the picture. For the rest of it, we turn to Aristotle's notion of eudaimonia.

주관적 웰빙- 당신이 행복하고, 그걸 안다면, 우리?鍍?알려다오

현대 쾌락심리학은 멀리 아리스티푸스에 뿌리가 닿는다. 하지만, 일시적인 정서로 웰빙을 평가할 수 있는가하는 문제가 있다. 이는 일반적으로 장기적이고 전반적 안정성이라는 특성을 웰빙의 개념과 행복의 정의의 차이로 보기 때문이다. 특히 카네만은 장기적인 특성을 측정할 필요에 맞추어 개인의 삶에 대한 만족도를 자기보고식으로 측정하는 것을 토대로 웰빙 측정치를 개발하였다. “주관적 웰빙(Subjective Wellbeing; SWB)”( )은 인생 사건과 만족, 성취를 포함하는 자신의 삶에 대한 인지 및 정서적 평가로 구성되어 있다. 예를 들어, 이 측정도구를 이용해서 국가행복지수( )를 개발했는데, 많은 나라에서 정책결정을 위한 정보로 활용도가 높아지고 있다(다른 사례들을 제 3장에서 경제학의 학제적 맥락에서 좀 더 자세히 논의하였다).

웰빙의 주관적 측정치는 보통 세 요소로 구성된다: 인생만족, 긍정적 기분의 존재, 부정적 기분의 부재. 인생만족은 상대적으로 회고적 판단인 것에 반해 기분의 존재는 회고적일 수도 있고(“지난 1주일 간 나는 행복했다”처럼), 현재초점적일 수도 있다(“나는 행복하다”처럼).

쾌락심리학의 대부분 연구는 상당한 타당도를 입증한 SWB를 이용하였다. SWB는 제 3자 보고형 측정치와 같은 다른 유형의 측정도구나 생리적 웰빙측정치(예를 들면, fMRI)와 일치도가 높다. 디너( )는 개관연구를 통해 20세기 말까지 주관적 웰빙과 이에 대한 다양한 측정도구들에 대해 그동안 밝혀진 것들을 정리하였다. 그 이후의 진전이 여러 측면에서 있었는데, 새로운 뇌영상 및 게놈기법( )과 디지털을 이용한 자료수집 및 자기보고 방법의 개선 등이 포함된다.

어떤 연구는 경험표집법(experience sampling)을 활용했는데, 이 방법은 하루 중 임의의 시간에 정서를 여러 번 보고하게 하거나( ), 일기를 쓰게 하는 것인데( ), HCI 연구에서도 흔히 삶의 여러 측면에 대한 만족이나 여러 좋고 나쁜 경험에 대한 기억을 기록하도록 하는 방법을 쓴다. 이런 자기보고에 따르면, 사람들은 (극단적으로 가난하거나 어려운 환경에 사는 경우를 제외하고) 약간 행복하다고 보고하는 경향이 있다. 아주 높거나 낮은 웰빙수준을 보고하는 사람은 드물다.

시간이라는 측면에서, 개인의 자기보고는 “온라인”(실시간으로 보고하는 것처럼)이냐 “회상”(일기로 보고하는 것처럼)이냐 아니면 장기간을 아우르는 인생평가와 같은 것으로 대별할 수 있다. 이렇게 서로 다른 세 종류 시간척도는 서로 다른 방식으로 행동에 영향을 미친다. 예를 들어, 디너( )는 장래 행동에 대해서는 회상된 느낌이 매순간의 느낌에 비해 예측력이 높아서, 우리가 이전의 삶을 어떻게 기억하고 판단하느냐 하는 것이 미래행동과 상관이 더 높다는 것을 발견했다. 사람의 가치는 매우 느리기 변하기 때문에 몇 주나 몇 달 간의 인생만족도를 회상할 때는 우리의 판단은 매우 안정적인 경향이 있다. 하지만 상당히 긴 기간을 통해서 인생 만족도에 대한 보고를 살펴보면 바뀌게 될 텐데, 이는 나이를 먹고 시간이 흐름에 따라 개인적 가치와 환경이 모두 극적으로 바뀌기 때문이다.

외부환경이 웰빙에 미치는 효과에 관해 흥미로운 점은 우리가 거기에 적응하는 능력이 있다는 것이다. “쾌락적 쳇바퀴(hedonic treadmill)” 개념에 따르면, 사람은 나쁜 것이든 좋은 것이든 모든 변화에 적응하거나 “익숙해져”서 개인의 중립적인 기저선으로 돌아온다. 말하자면, 새 티브이를 구입할 때 느꼈던 행복감은 한 달이나 그 후에는 당신의 행복에 아무런 영향력이 없어진다. 더 극적인 것을 보여준 연구가 있는데, 복권 일등당첨자와 최근 마비를 겪은 사람 모두 이 같은 삶을 바꾼 사건들 이후의 인생만족도는 기대했던 것보다 훨씬 조금 변했다는 것을 보여주었다( ). 쾌락적 쳇바퀴 개념은 우리가 과거의 설정점으로 매번 돌아오기 때문에 행복을 증진시키려는 노력을 허사로 만들 수 있다는 것이다. 하지만, 보이스와 우드( )연구는 긍정적 적응의 예측에 성격과 태도가 중요함을 보여주었고, 디너와 동료들은 쾌락적 쳇바퀴 모형을 개정해서 설정점이 중립적인 것이 아니라 일반적으로 긍정적이 되며, 나아가서 설정점 자체가 변할 수 있다고 주장한다( ).

유전적 성향과 환경은 문화적 수준과 마찬가지로 영향을 미친다. 대규모 자기보고 종단자료로 문화와 시대에 따른 SWB를 비교해볼 수 있는데, 여러 차원에서 차이가 있다. 예를 들어, 프랑스는 놀랄정도로 주관적 웰빙이 꾸준히 낮으며, 스칸디나비아 국가들은 특이하게 높다. 후퍼트와 소( )가 깊이 파본 결과, 프랑스는 모든 국가 중 몰입(engagement)은 가장 높지만 자존감 순위가 가장 낮고 낙관주의와 긍정적 관계는 바닥수준이었다. 이들은 이런 결과를 서로 다른 사람과 국가 간의 차이를 이해하는 데에 왜 웰빙을 다차원적으로 측정하는 것이 중요한지를 보여주는 증거로 보았다. 지역과 문화와 함께 국가 수준의 웰빙을 측정하는 것은 지속적인 연구영역이다( ). 행복지구지표(Happy Planet Index), 세계행복보고서(World Happiness Report), 유로바로미터(Eurobarometer)와 같은 측정치들은 국가적 사건과 정책적 개입의 효과뿐 아니라 나라와 문화에 따른 차이를 들여다볼 수 있는 수단이 된다. 다음 장에서 이에 관한 연구를 일부 살펴본다.

인생만족도나 SWB, 삶의 질 측정치들은 모두 다양한 경제사회 및 연구맥락에서 널리 사용되고 있다. 하지만 긍정적 정서가 다는 아니다. 이제 아리스토테레스의 행복론을 살펴보겠다.

Eudaimonic Psychology - Wellbeing as Engagement with Meaning and the Fulfillment of Potentials

Few among us eschew pleasure or positive emotion. In fact, most of us spend much of the day seeking pleasures out in small ways, from that nip to the cookie jar or that session of online games to the sitcom after dinner or cuddles before bed. Positive emotions are part of a happy life, but we're nevertheless stuck with the reality that you can get too much of a good thing, and positive emotions alone may not be a complete answer to lasting wellbeing. Here enters the much celebrated notion of the “middle path” or “golden mean,” along with theories of wellbeing that go beyond the experience of positive emotion into the realms of engagement, meaning, relationships, and human potential.

행복론적 심리학 - 의미추구와 잠재력 발휘

즐거움이나 긍정정서를 멀리하는 사람은 거의 없다. 실제로, 우리 대부분은 대부분의 시간을 술을 홀짝이거나 주전부리를 하고, 식사 후에 온라인 게임과 시트콤을 보거나 포옹을 하는 등 소소한 방식으로 쾌락을 추구하는데 쓴다. 긍정 정서는 행복한 삶의 일부이지만 우리는 항상 그렇게 좋은 일만 겪을 수 없다는 현실에 살며, 긍정적 정서만으로는 장기적인 웰빙의 완벽한 해결책이 될 수 없다. 긍정적 정서경험을 넘어서 몰입과 의미, 관계, 잠재성의 영역을 포괄하는 웰빙이론들이 말하는 “중도(middle path)” 또는 “중용(golden mean)“이라는 훨씬 유명한 주장을 살펴보자.

Self-Determination Theory -- Wellbeing as Determined by Autonomy, Competence, and Relatedness

Don't ask how we can motivate people. That's the wrong question. Ask how we can provide the conditions within which people can motivate themselves. Edward Deci, TEDxFlourCity

Richard Ryan and Edward Deci's self-determination theory (SDT),[(See http://www.selfdeterminationtheory.org/.)] which posits that autonomy, competence, and relatedness are the key components of both motivation and wellbeing, is one of the theories of wellbeing most readily applied to a technology context, in part because it is relatively straightforward to operationalize.

In order to be self-determined, we must feel autonomous – that is, be able to attribute the outcomes of our activity to our own intentions (what researchers call the “internal locus of causality”). We must feel competence or confident in our ability to meet challenges (e.g., experience optimal challenges and freedom from threats or demeaning evaluations). And finally, we must feel secure and connected to others.

SDT has many implications for design, perhaps the most conspicuous of which is its attention to intrinsic motivation and autonomy. In chapter 7, we look later at how these implications can influence the design of technologies, in particular those that seek to change or support behavior.

Another implication for design stems from the way in which SDT deals with interpersonal, social, and cultural factors. SDT does not suggest that autonomy, competence, and relatedness would be equally valued by people from different socioeconomic backgrounds, families, or cultures. It does maintain, however, that environmental conditions that hinder these factors will have negative psychological consequences in all social or cultural contexts. According to this line of thought, sociocultural (and, we argue, digital) environments that support these needs can influence wellbeing at both between-person and within-person levels of analysis.

Whereas hedonic theories of wellbeing rely on SWB research, eudaimonic theories often use measures of how well an individual does on a set of factors that support wellbeing (such as autonomy or positive relationships). Those with a eudaimonic perspective have challenged SWB models for being too narrow and a flawed indicator of healthy living. Those with a hedonic perspective, in turn, have argued that eudaimonic criteria are generally defined by experts, whereas the focus on “subjective” in SWB research respects people's individual ideas on what makes a good life. We believe both measures can be valuable to work in technology design, sometimes in combination, and we look more deeply at how wellbeing can be measured from each of these viewpoints in chapter 5.

자기결정 이론-자율성과 유능감, 관계성에 의한 웰빙

우리가 사람을 어떻게 동기화할 수 있는지 묻지 마세요. 잘못된 질문입니다. 사람들이 스스로 동기화할 수 있는 조건을 어떻게 조성할 수 있는지 질문하세요.
- 드시( )

자율성과 유능감, 관계성이 동기화와 웰빙 모두의 핵심요인이라 주장하는 라이언과 드시( )의 자기결정 이론(Self-Determination Theory; SDT)은 텍 분야에 가장 쉽게 응용할 수 있는 이론 중의 하나인데, 조작화(operationalization)가 비교적 단순하다는 것도 그 이유의 일부이다.미주.

. http://www.delfdeterminationtheory.prg/. 참조

자기결정적이려면, 우리는 자율감을 꼭 느껴야 한다. 즉 행위나 활동의 결과가 우리 자신의 의도에 의한 것이라 느낄 수 있어야 한다(연구자들은 이를 “내적 인과소재”라 한다). 도전에 대응할 수 있는 능력에 확신이나 유능감을 느껴야 한다(즉, 적절한 도전이며 위협이나 모욕적인 평가로부터 자유롭다는 느낌). 마지막으로 다른 사람들과 안전하게 연결되어있다고 느껴야 한다.

SDT는 내적 동기와 자율성에 대해 가장 확실하게 주의를 기울이고 있는 이론이어서 디자인에 대해 많은 시사점을 가지고 있다. 제 7장에서 이런 시사점이 텍 디자인에 어떻게 영향을 미칠 수 있는지를 특히 행동변화와 지지와 관련해서 살펴본다.

디자인을 위한 또 다른 시사점은 SDT가 대인관계와 사회문화적 요인들을 다루는 방식에 있다. SDT는 자율성과 유능감, 관계성의 상대적 중요성이 서로 다른 사회경제적 배경, 가족, 문화에 따라 같지 않다고 주장한다. 하지만, 이것이 이들 요인을 가로막는 환경적 조건은 어떤 사회나 문화적 맥락에서든 모두 부정적인 심리적 결과를 낳는다고 본다. 이런 식의 생각에 따르면, 이런 욕구를 지지하는 사회문화적 (그리고, 우리가 보기에 디지털적) 환경은 개인 간이나 개인 내 수준 모두의 분석에서 웰빙에 영향을 미칠 수 있다.

웰빙의 쾌락주의적 이론들이 SWB에 의존하는 것과 달리, 행복론적 이론들은 종종 개인이 웰빙을 지원하는 요인들(자율성이나 긍정적 관계같은)을 얼마나 잘하는가의 측정치를 사용한다. 행복론적 관점을 가진 사람들은 SWB 모형들의 건강한 삶의 지표가 너무 좁고 부적절하다고 비판한다. 반대로 쾌락주의적 관점을 가진 연구자들은 행복론적 준거가 주로 전문가의 정의에 의존하는 것인데 반해 SWB의 “주관적” 측정은 무엇이 좋은 삶인가에 관한 사람들 개개인의 생각에 초점을 맞춘 것이라고 주장한다. 우리는 두 측정법이 모두 텍디자인에 가??있으며, 때론 조합으로도 가??있다고 믿는다. 이들 각 관점을 대변하는 웰빙 측정법에 대해서는 제 5장에서 더 자세히 살펴보았다

Combining Hedonic and Eudaimonic Approaches

Many current theories include both hedonic and eudaimonic aspects as factors of wellbeing, such as the model by Huppert and So mentioned previously. Corey Keyes combines emotional wellbeing (hedonic aspects) with aspects of psychological and social wellbeing (eudaimonic) to describe a mental health continuum. Martin Seligman, originator and ongoing champion of the positive-psychology movement, has developed the PERMA model, which stands for Positive Emotions, Engagement, Relationships, Meaning, and Achievement. Seligman and Keyes are among a number of researchers making inroads to our understanding of wellbeing from within the field of positive psychology.

쾌락론과 행복론적 접근의 통합

많은 현대의 이론들은 앞서 후퍼트와 소( )의 예에서 볼 수 있듯이 쾌락적 측면과 행복론적 측면을 모두 웰빙의 요소로 포함하고 있다. 키예스( )는 정서적 웰빙(쾌락적 측면)을 심리사회적 웰빙(행복론적 측면)과 결합해서 하나의 정신건강 연속체를 설명하였다. 긍정심리학 운동의 창시자이자 지속적인 보급에 힘쓰고 있는 셀리그만( )은 긍정정서, 몰입, 관계, 의미, 성취로 구성된 PERMA 모형을 개발했다. 많은 연구자들 중 특히 셀리그만과 키예스는 긍정심리학 분야를 통해 웰빙에 대한 우리의 이해에 영향을 주고 있는 사람들이다.

Positive Psychology - Wellbeing as Flourishing

The field of positive psychology at the subjective level is about valued subjective experiences: well-being, contentment, and satisfaction (in the past), hope and optimism (in the future); and flow and happiness (in the present).
- Martin Seligman and Mihaly Csikszentmihalyi, “Positive Psychology”

Thanks to life-saving progress in psychology and psychiatry, many mental disorders can now be diagnosed, treated, and sometimes cured. Psychologists, however, have come to question the nearly exclusive disease focus of their discipline. In 2000, Martin Seligman, then president of the American Psychological Association, and Mihaly Csikszentmihalyi (Seligman & Csikszentmihalyi, 2000) argued for placing greater emphasis on promoting healthy functioning rather than exclusively on dysfunction. The idea of “positive psychology,” as they called it, resonated with a great number of researchers and has come to represent an active field of work with ever-increasing influence.

Positive psychology has matured to an extent that it now influences education, policy, management, and mental health. Journals such as the Journal of Happiness Studies and the Journal of Positive Psychology as well as conferences, symposia, and handbooks of academic literature have developed from this approach. It has been argued that a special term is no longer needed and that a study of healthy and optimal functioning should simply be understood as an essential part of psychology as a whole.

Many researchers in the area of positive psychology have translated their research findings into self-help books for public benefit. These books often have enough detail that they can go some way to informing design work and ideation. They include Seligman's Flourishing; Ed Diener and Robert Biswas-Diener's Happiness, Barbara Fredrickson's Positivity, Sonja Lyubomirsky's The How of Happiness, and Daniel Gilbert's Stumbling on Happiness, all of which present practical information based on findings from the authors' research.

It's worth noting that some aspects of human behavior and thinking are easier to change than others. Christopher Peterson and Martin Seligman (2004) have identified four sets of components linked to positive mental health: talents, enablers, strengths, and outcomes. Talents are seen as those traits that are hard to change. Enablers include environmental conditions that support wellbeing, such as the right social conditions, a caring family, and so on. Most interesting from a technology perspective are strengths?those personal facets such as curiosity, kindness, and gratitude that are susceptible to interventions and therefore where psychologists and technologists can more easily make a difference.

It was in the context of positive psychology that the terms positive computing (Sander, 2011) and positive technologies (Botella & Riva, 2012; Riva & Banos, 2012) were first introduced. Tomas Sander's use was hypothetical?a vision and a call to action for technology to play a role in meeting Seligman's challenge that 51 percent of the population be flourishing by 2051. The influential work of Giuseppe Riva, Brenda Wiederhold, Andrea Gaggioli, and their respective teams in cyberpsychology has pioneered research on developing virtual and augmented reality tools for psychotherapy (e.g., Gorini, Gaggioli, Vigna, & Riva, 2008) and for supporting interventions for physical and mental health (e.g., Riva, Cipresso, Mantovani, Dakanalis, & Gaggioli, 2013).

Giuseppe Riva and Rosa Banos (2012) were the first to suggest an approach to supporting the development of tools for positive psychology. They define a “positive technology” approach as “the scientific and applied approach to the use of technology for improving the quality of our personal experience through its structuring, augmentation and replacement.” Based on Seligman's original model described in his book Authentic Happiness (2002), they divide personal experience into Positive emotions, Engagement, and Meaning (i.e., eudaimonia) – a model that Seligman has now extended to include “Relationships” and “Achievement,” or PERMA. Riva and Banos have proposed improving hedonic wellbeing by providing positive emotional and sensorial experiences; improving eudaimonic wellbeing by providing training for “systematic mood induction,” “wellbeing,” “reminiscence,” and “life theme”; and improving social connectedness by providing “shared positive emotional experiences,” “wellbeing training” and “setting shared significant goals.”

In this book, although we take a deliberately broad and inclusive view of what research can and should inform positive computing, positive psychology models and methods remain some of the most relevant. We have already presented our notion of positive computing from the context of technology in articles for the engineering community (Calvo & Peters, 2013) and within HCI (an early manifestation) (Calvo & Peters, 2012).

The influence of positive psychology can also be found in other related fields, such as emotional intelligence, an area of study that has seen wide real-world application throughout work and education.

긍정심리학 - 만개(flourishing)로서 웰빙

주관적 수준에서 긍정심리학의 분야는 주관적으로 가치있게 여기는 경험 즉, 웰빙, 자족(contentment), 만족(과거의), 희망과 낙관주의(미래의), 플로우(flow)와 행복(현재의)에 관한 것이다.
- 셀리그만과 칙센미하이( )

이제는 심리학과 정신의학에서 이룬 생명을 살리는 진보 덕분에 많은 정신질환을 진단하고 치료할 수 있게 되었다. 하지만, 심리학자들은 그동안 심리학이 거의 전적으로 질병에 초점을 맞추었던 것에 의문을 갖게 되었다. 셀리그만( )은 2000년도에 미국심리학회장이었는데 칙센미하이( )와 함께 역기능적인 것에만 초점을 맞추기보다는 건강한 기능의 촉진에 더 많은 관심을 가져야한다고 주장했다. 이들이 “긍정심리학”이라 부르는 이런 생각은 상당히 많은 학자들의 공감을 받아 지금도 계속 영향을 확대하고 있는 하나의 역동적인 활동분야를 대표하게 되었다.

긍정심리학은 이제 교육과 정책, 관리, 정신건강에 영향을 미칠 정도로 성숙하였다. 이런 접근법에서 Journal of Happiness Studies, Journal of Positive Psychology 같은 학술지와 학술대회, 심포지아, 학술문헌 핸드북 등이 개발되었다. 이제 더 이상 다른 특수한 용어가 필요하지 않으며 건강하고 적절한 기능에 대한 연구는 전체 심리학의 핵심적인 부분이라고 이해될 정도라고 한다.

많은 긍정심리학 분야의 학자들은 자신들의 연구결과를 일반인을 위한 자조서(self-help book)로 출판하였다. 이런 책들은 대개 디자인 작업과 아이디어 개발에 어떤 식으로든 도움을 받을 수 있을 정도로 자세한 설명을 제공하고 있다. 셀리그만의 만개(flourishing), 디너와 비스워스 디너( )의 행복(Happines), 프레드릭슨( )의 긍정성(Positivity), 길버트( )의 행복의 장애물(Stumbling on Happiness) 같은 책은 저자들의 연구결과를 토대로 한 실용적인 정보를 제공하고 있다.

인간행동과 사고는 어떤 부분은 다른 부분에 비해 바꾸기가 쉽다. 피터슨과 셀리그만( )은 긍정적인 정신건강과 연관된 요소로 재능과 enablers, 강점, 성과라는 네 가지 요소를 밝혀내었다. 재능(talents)은 바꾸기 어려운 타고난 특질로 간주한다. enablers 에는 좋은 사회적 상태, 잘 돌보아주는 가정과 같이 웰빙을 지지하는 환경적 조건들이 포함된다. 텍의 관점에서 가장 흥미로운 것은 강점(strength)인데, 이는 호기심, 친절함, 관대함 같은 개인적 특성으로서 개입을 통해 영향을 줄 수 있고 그래서 심리학자와 텍스트들이 쉽게 차이를 만들어 낼 수 있는 요소이다.

긍정컴퓨팅(positive computing)이라는 용어( )와 긍정기술(positive technologies)이라는 용어( )가 처음 소개된 것도 이런 긍정심리학의 맥락에서 이루어진 것이다. 샌더스( )의 용어사용은 개념적인 것이어서 셀리그만이 주창한 2051년까지 인구의 51%가 만개하도록 하자는 비전의 실현에 텍이 역할을 할 수 있는 활동을 촉구하는 수준이었다. 사이버심리학의 리바( ), 와이더홀드( ), 개그지올리( ) 같은 인물과 팀들이 했던 영향력이 큰 작업들이 선구적이라 할 수 있는데, 이들은 심리치료를 위한( ) 또는 심신건강을 위한 개입을 지원하기 위한( ) 가상현실과 증강현실 툴 개발연구를 선도하였다.

리바와 바노스( )는 긍정심리학을 위한 툴 개발을 지원하는 접근법을 처음 주장한 인물이다. 이들은 “긍정텍” 접근법을 “텍을 그 structuring, augmentation, replacement를 통해 우리의 개인적 경험의 질을 향상시키는데 사용하는 과학적이고 응용적인 접근”이라고 규정했다. 이들은 셀리그만이 Authentic Happiness(2002)에서 설명한 오리지널 모형에 근거해서 개인의 경험을 긍정정서(Positive emotions), 몰입(Engagement), 의미(Meaning)(즉, 행복론적)로 구분하였다(이 모형은 이제는 셀리그만이 관계와 성취를 추가해서 PERMA모형으로 확장되었다). 리바와 바노스( )는 쾌락적 웰빙은 긍정적인 정서와 감각경험을 제공함으로써 증진할 수 있으며, 행복론적 웰빙은 ‘체계적 무드유도’, ‘웰빙’, ‘추억’, ‘생애주제‘ 훈련을 통해 증진할 수 있고, 사회적 연결성은 ‘긍정적 정서경험의 공유‘, 웰빙훈련‘, ‘중요한 공동목표설정’을 통해 을 증진할 수 있다고 제안하였다.

우리는 이 책에서 긍정컴퓨팅에서 어떤 연구를 할 수 있고 해야 하는가에 관해 의도적으로 광범위한 포괄적인 견해를 취하기는 했지만 긍정심리학의 모형과 방법론은 가장 적절한 것이라 할 수 있다. 우리는 이미 공학계를 위한 논문과( ) HCI 계의 논문들( )을 통해 긍정컴퓨팅에 관한 우리의 주장을 발표한 바 있다.

긍정심리학의 영향은 정서지능처럼 이미 작업장과 교육장면의 실세계에 널리 적용되는 분야에서도 찾아볼 수 있다.

Emotional Intelligence

Anyone can become angry?that is easy. But to be angry with the right person, to the right degree, at the right time, for the right purpose, and in the right way?that is not easy.
- G. E. Vaillant, “Positive Mental Health”

A stroll through any bookstore can lead to a generous section on emotional intelligence (EI). Our historically narrow definition of intellectual intelligence was long in need of an upgrade, and incorporating social and emotional capacities has allowed researchers and professionals to better understand some of the sources of success, performance, and even wellbeing separate from intellectual prowess.

In terms of the academic literature, socioemotional intelligence originates with the research of Jack Mayer, David Caruso, and Peter Salovey (Mayer, Caruso, & Salovey, 1999; Salovey & Mayer, 1990) and was popularized and extended by Daniel Goleman (2005). According to Goleman, EI includes the capacities of self-awareness (to recognize your own emotions), self-regulation (to control them), motivation (to have a passion for what you do), empathy (to recognize others emotions), and social skills (to manage relationships with others).

A number of measures of EI have been developed and evaluated. One of the most commonly used is the Mayer-Salovey-Caruso Emotional Intelligence Test (Mayer, Salovey, & Caruso, 2002). Having such measures means that researchers have been able design interventions such as training modules or policies and then evaluate their outcomes.

Hundreds of studies of interventions have been designed to develop EI in businesses, schools, and professional sports. Positive emotions, such as the ones we feel when receiving compliments, tend to increase prosocial behavior. In contrast, empirical evidence has shown that punitive practices can increase antisocial behavior (Mayer, 1995). This research has been used to promote positive interventions rather than punitive ones in schools and prisons. For example, the Los Angeles Unified School District (2007) recently adopted a policy that requires the implementation of systems of positive reinforcement in schools as an alternative to punishment. Interventions like these for social and emotional learning (Payton et al., 2000) are often grounded in EI theory. We discuss EI in greater detail in part II. (For more detail on EI capacities and the potential of technology to support them, see David Caruso's sidebar in chapter 8.)

정서지능

누구나 화를 낼 수 있다. 이것은 매우 쉽다. 하지만 적절한 사람??적절한 수준으로 적적한 시점에 적절한 목적으로 그리고 적절한 방식으로 화를 내는 것. 그것은 쉽지 않다.
- 베일런트( )

어떤 서점에서든 정서지능(Emotional Intelligence; EI)에 관한 진열대를 쉽게 찾아볼 수 있다. 역사적으로 지능은 협소하게 정의되어서 이를 개선해야 한다는 필요성은 오래 전부터 있었다. 학자와 전문가들은 사회정서적 역량을 도입함으로써 성공과 성과, 나아가 웰빙의 원천을 지적인 능력과는 분리해서 이해할 수 있게 되었다.

학술문헌을 보면, 사회정서적 지능에 대한 연구는 마이어와 카루소, 살로비( )의 연구가 그 기원이며, 이를 확산시켜 대중화한 것은 골맨( )이다. 골맨에 따르면 EI는 자각(자신의 정서 인식)과 자기조절(자기 정서의 통제), 동기(무엇을 하려는 열정을 갖는 것), 공감(타인의 정서 인식), 사회적 기술(대인관계 관리) 능력을 포함한다.

EI 측정도구가 여럿 개발되어 있고 평가도 이루어졌다. 가장 널리 쓰이는 것은 마이어-살로비-카루소 정서지능검사( )( )이다. 이런 측정도구가 있다는 것은 연구자들이 훈련모듈이나 정책적 개입을 설계하고 그 결과를 평가할 수 있었다는 것을 뜻한다.

기업과 학교, 스포츠 분야들에서 개발된 개입법들에 대한 많은 연구가 있다. 칭찬을 받았을 때 느끼는 것 같은 긍정적 감정은 친사회적 행동을 증가시키는 경향이 있다. 반대로, 처벌은 반사회적 행동을 증가시킨다는 경험적 증거도 있다( ). 이런 연구들은 학교나 교도소에서 처벌보다는 긍정적 개입을 촉진하는 데에 활용되었다. 예를 들어, 로스엔젤레스 통합교육청(2007)에서는 최근 처벌 대신에 긍정적 강화체계를 적용하도록 하는 정책을 채택했다. 이러한 사회정서적 학습을 위한 개입법( )은 통상 EI 이론을 토대로 하고 있다. 2부에서 EI에 대해 더 자세히 논의하겠다( EI 능력과 이를 지원하는 텍의 잠재적 가능성을 더 자세히 보려면 제 8장의 카루소( )의 sidebar를 참조).

Buddhist Psychology - a Science of the Mind

The primary orientation of the Buddhist investigative tradition has been toward understanding the human mind and its various functions. The assumption here is that by gaining deeper insight into the human psyche, we might find ways of transforming our thoughts, emotions and their underlying propensities so that a more wholesome and fulfilling way of being can be found. It is in this context that the Buddhist tradition has devised a rich classification of mental states, as well as contemplative techniques for refining specific mental qualities.
His Holiness the Dalai Lama, “Science at the Crossroads”

To focus only on Western theory would be strangely remiss for a topic such as wellbeing, which has been studied systematically by Eastern philosophers for thousands of years. An interest in Buddhism for its practices such as mindfulness and meditation and for the culture of peace and compassion it represents has led to a growing integration of Buddhist philosophy into Western notions of wellbeing.

This has been possible in part because Buddhist philosophy and practice can be investigated separate from the religious aspects of cultural rituals and belief systems in which it is nested. It is probably the relatively bare-bones, nonreligious style of Zen that has made it one of the most widely accessed sources of Buddhist thought in Western culture. In fact, the term zen has become a cliched colloquial synonym for simplicity and tranquility of mind (visit any home furnishings store for evidence). But the other essential element that makes Buddhist philosophy amenable to a partnership with Western science is its commitment to empiricism.

The Dalai Lama is adamant that Buddhist doctrine is subject to scientific evaluation and should change in light of new evidence. He explains that “in the Buddhist investigative tradition, between the three recognized sources of knowledge?experience, reason and testimony?it is the evidence of the experience that takes precedence, with reason coming second and testimony last. This means that, in the Buddhist investigation of reality, at least in principle, empirical evidence should triumph over scriptural authority, no matter how deeply venerated a scripture may be” (2005).

Psychologist Paul Gilbert (2011) puts it this way:

For thousands of years Buddhist scholars and devotees studied and developed practices of introspective and reflective psychology and an ethic based on compassionate insights?these are ways by which individuals can become very familiar with their minds, learn to stabilise and organise them for their wellbeing, and cultivate key qualities that are associated with personal and social health. … While the focus of science has been on understanding and alleviating the physical nature and causes of pain, spiritual traditions like Buddhism have tended to focus more on alleviating suffering, that is, working with how the mind reacts to pain.

It is perhaps owing to this empirical stance that technologists interested in Buddhist philosophy are now significant enough in number to have motivated the creation of the annual “Buddhist Geeks” conference. Interest lies in how Buddhist practitioners investigate the interrelationships between emotion, cognition, and behavior as well as in Buddhist practices such as mindfulness and various forms of meditation, taught for centuries as paths to wellbeing. These practices have also of late been increasingly evaluated by Western psychology and neuroscience. Work in multiple fields using multiple measures has consistently shown Buddhist meditative and mind-training practices to be highly effective for treating mental illness and increasing wellbeing. So compelling is the evidence of their effectiveness that mental health professionals at institutions such as Oxford, Harvard, Stanford, Yale, the University of California at Berkeley, and the University of Wisconsin at Madison, among many other institutions around the world, have incorporated them into clinical and research work.

Jon Kabat-Zinn (2003), the originator of the Mindfulness-Based Stress Reduction program, one of the most successful integrations of Buddhist and Western psychology to date (which we discuss in greater detail in chapter 9), adeptly describes Buddhist practices in untraditional and elucidating terms: “Of course, the Buddha himself was not a Buddhist. One might think of dharma as a sort of universal generative grammar, an innate set of empirically testable rules that govern and describe the generation of the inward, first-person experiences of suffering and happiness in human beings. … It is neither a belief, an ideology, nor a philosophy. Rather, it is a coherent phenomenological description of the nature of mind, emotion, and suffering and its potential release, based on highly refined practices aimed at systematically training and cultivating various aspects of mind and heart via the faculty of mindful attention.” In the following chapters of this book, we look more closely at how these practices are used in various contexts.

불교심리학 - 마음의 과학

불교적 탐구전통의 기본 지향점은 인간의 마음과 그 다양한 기능을 이해하는 것이었다. 인간정신에 대한 깊은 통찰을 얻으면 우리의 생각과 정서 및 기저의 특성을 변환할 수 있는 방법을 찾을 수 있으며 이를 통해 온전하고 충만한 존재방식을 알아낼 수 있다는 기본적 가정이 바탕에 있었다. 이런 맥락에서 불교전통은 정신상태를 매우 풍부하게 분류하고 구체적인 정신적 특성을 정련하는 명상기법을 갖게 된 것이다.
- 달라이 라마( )

동양철학자들이 수 천 년 간 웰빙을 체계적으로 연구한 것과 달리, 서구이론의 초점은 이상하게도 웰빙과 같은 주제를 간과했다. 마음챙김이나 명상과 같은 수련법과 평화와 연민의 문화에 대한 불교의 관심은 불교철학을 서구의 웰빙연구에 점차 통합하도록 이끌었다.

이는 부분적으로 불교철학과 수련법이 그것이 내재하고 있는 문화적 의례나 신념체계와 분리해서 연구할 수 있다는 점에 기인한다. 서구문화에서 불교적 사고의 원천에 가장 널리 알려진 것이 선(Zen)인데, 아마도 선이 비교적 단순하고 비종교적인 스타일이어서일 것이다. 사실 Zen 이라는 용어는 마음의 단순성과 고요함과 동의어가 될 정도로 하나의 상용어가 되었다(증거가 필요하다면 아무 가정용 ?망×〉?가보라). 하지만, 불교철학이 서구과학의 파트너가 된 데에는 다른 핵심적인 요소가 있는데, 이는 불교철학이 경험주의를 중시한다는 점이다.

달라이 라마는 불교의 교리는 과학적 평가의 대상이며 새로운 증거가 나타나면 바뀌어야 한다는 점을 단호하게 고집한다. 그는 이렇게 설명한다. “불교의 탐구전통이 인정하는 지식의 세 가지 원천 즉, 경험(experience)과 사유(reason), 증언(testimony) 중에서 가장 앞자리를 차지하는 것은 경험적 증거이고 그 다음이 사유이고 마지막이 증언입니다. 이는 실재에 대한 불교적 탐구에서 최소한 원칙적으로는 경험적 증거가 문헌적 권위보다 우월하다는 것을 의미한다. 그 문헌이 아무리 깊은 존경을 받는 것일지라도 그러합니다(2005).”

심리학자 길버트( )는 이를 다음과 같이 썼다.

수 천 년 간 불교학자들과 신자들은 내관적이고 반성적인 심리적 수련법과 연민적 통찰에 기반한 윤리를 개발하고 연구했다. 이는 개인이 자신의 마음에 매우 친숙해지고, 자신의 웰빙을 위해 마음을 안정시키고 조직하는 것을 배우며, 개인적이고 사회적인 건강과 관련된 중요한 특성을 계발하는 방법이었다….. 과학의 초점이 통증(pain)의 신체적 본성과 원인을 이해하고 완화시키는 것인 것과 달리, 불교와 같은 영적 전통은 괴로움(suffering)의 완화 즉, 마음이 통증에 어떻게 반응하는가를 다루는 데에 더 초점을 두는 경향이 있었다.

불교철학에 관심이 있는 텍스트들이 이제는 연례 “불교 Geeks” 대회를 여는 데에 충분할 정도로 그 수효가 많게 된 것도 아마 불교의 이 같은 경험주의적 자세 때문일 것이다. 웰빙을 위한 방법으로 수 세기 동안 가르쳐온 마음챙김과 다양한 형태의 명상수련에 대한 관심은 물론이고 불교수련자들이 어떻게 정서와 인지, 행동의 상호관계를 탐구하는가의 문제에도 많은 관심이 있다. 최근 서구에서 이런 수련에 대한 평??늘고 있는데, 주로 심리학자와 뇌과학자들이 수행하고 있다. 다양한 측정법을 이용하는 다양한 분야의 작업을 통해 불교 명상과 마음을 다루는 수련법들이 정신질환의 치료와 웰빙의 증진에 매우 효과적임이 계속 보고되고 있다. 이러한 효과에 대한 증거들이 너무나 설득력이 있어서 전세계의 많은 기관들 중에서도 특히 옥스퍼드( ), 하바드( ), 스탠포드( ), 예일( ), 버클리( ), 위스컨신( ) 대학의 연구소의 전문가들이 이런 연구결과들을 임상 및 연구작업에 통합하고 있다.

마음챙김기반 스트레스감소(MBSR) 프로그램을 만든 카밧진( )은 지금까지 서구심리학과 불교를 가장 성공적으로 통합한 사람들 중의 하나인데(제 9장에서 자세히 다룬다), 불교의 수련법을 비전통적이면서 설득력있는 용어로 멋지게 설명했다: “당연히 붓다 자신은 불교도가 아니었다. 우리는 불법(dharma)을 일종의 보편적인 생성문법으로서, 내적이며 즉자적인 인간존재의 괴로움과 행복경험의 발생을 관장하고 묘사하는 본디 경험적으로 검증할 수 있는 규칙들이라고 생각할 수 있다…. 그것은 신념이나 이데올로기, 철학이 아니다. 그것은 오히려 마음챙긴 주의라는 능력을 통해 마음과 가슴의 다양한 측면을 체계적으로 훈련하고 계발하려는 고도로 정련된 수련에 기반한 설명으로서, 마음과 정서, 괴로움의 본성과 그 소멸가능성에 대한 논리정연한 현상학적 묘사이다.” 다음 장에서 이런 수련법들이 다양한 맥락에서 어떻게 활용되는지 살펴본다.

Biology and Neuroscience - Wellbeing as Physiologically Identifiable

Researchers in biology and neuroscience have used physiological and brain signals to detect and understand individual emotions. Others study biological factors that influence wellbeing (such as genes or physical health), while some investigate how those biological systems interact with environmental conditions.

This work intersects with HCI most clearly in affective computing. Rafael's research group has been among those to use physiological signals to detect emotions during HCI, particularly for applications within education and mental health. For example, physiological signals can be used to measure the impact of feedback when students receive it during online activities (Pour, Hussain, AlZoubi, D'Mello, & Calvo, 2010). Moreover, signals from multiple physiological systems can be combined, including electroencephalography (EEG), electromyography, skin conductivity, and respiration (AlZoubi, Hussain, D'Mello, & Calvo, 2011). We come back to this work with respect to affective computing in chapter 4.

Neuroscience researchers seek to identify patterns of electrical and chemical activity in the brain that correlate with the emotion, cognition, and behavior we experience. In the past two decades, their research has come to include positive emotions as well as characteristics associated with increases in wellbeing, such as resilience and meditative practice.

Using brain-imaging techniques, scientists can learn more about the brain's structures and the processes behind emotions. For example, researchers may have found the neural network responsible for answering our opening question: “How are you?” The anterior insula cortex seems to contain the interoceptive representation of our embodied feelings and emotions (Craig, 2009b). Together with the anterior cingulate cortex, it is activated in subjects experiencing emotional feelings such as love, anger, fear, sadness, happiness, indignation, social exclusion, and empathy.

These neural correlates have been used to propose a model of awareness that includes homeostatic, environmental, hedonic, motivational, social, and cognitive activity to describe both a “global emotional moment” and the fact that a series of such moments produces a representation of sentiments over time. Eight prosocial positive emotions (love, hope, joy, forgiveness, compassion, faith, awe, and gratitude) are often identified as the components of wellbeing in this model. Notably, almost all involve human connection rather than just the self. These models do not require that all our emotions be positive and acknowledge that negative emotions are necessary for survival (Craig, 2009a, 2009b).

Affective and social neuroscience recognize that our brain is also shaped by what we experience. For example, studies using functional magnetic resonance imaging (fMRI) show that early stressful and nurturing environments have a strong effect on how the brain develops. Richard Davidson and others (e.g., Davidson & McEwen, 2012) have been gathering evidence that certain interventions can be intentionally designed to promote prosocial behavior and wellbeing. According to Davidson's research, structural changes in the brain can be triggered by regular exercise, cognitive therapy, and meditation practices, suggesting that we can develop training practices for this purpose. This work poses tantalizing questions for the potential impacts of technologies in these same areas.

In a recent article, Davidson and colleagues (2012) discuss how such results can inform education. They posit that it should be possible to support prosocial behaviors and academic success in young people by developing the underlying elements of wellbeing through systematic contemplative practices that have been shown to be effective and to trigger neuroplastic change. They have also pointed to the potential for technologies such as videogames to be used to develop positive characteristics, including mindfulness and empathy.

Others who study the biological factors of wellbeing look at the relationship of physical behaviors such as circadian rhythms, diet, and exercise to psychological health. For example, Ian Hickie at the University of Sydney studies the chronobiology system (our physiological clock) and its effect on depression. Even research in this area can inform work in positive computing. For example, together with Hickie we are exploring how information about sleep cycles collected from social networks might be used for detecting people at risk of depression.

Personality traits (Costa & McCrae, 1992) and genetics are other acknowledged determinants of wellbeing. During the 1990s, neuroscientists hoped to be close to identifying the genetic determinants of mental illnesses. Since then we have come to better recognize the complexity and sheer number of genes involved in both mental disorders and in flourishing, yet progress has been made on many fronts. A groundbreaking paper (Caspi et al., 2003), for example, revealed the impact of a certain gene configuration known as the 5-HTT promoter that determines how well our neurons transport serotonin?a neurotransmitter famously linked to depression and wellbeing. They found that those with one or two copies of the short allele of the gene were more vulnerable to depression when faced with life-stressing situations. Another study (Pluess & Belsky, 2013) resulted in four categories of resilience: (1) those that are highly reactive to both negative and positive events, (2) those that are low reactive to both types of events, (3) those that are vulnerable to negative events (low resilience), and (4) those that are more influenced by positive events or “vantage sensitive.”

Even the apparently predetermined factors of genetics and personality traits can be influenced and changed. For instance, we now understand that gene expressions are modified by the environment and personal experience, an area of research known as “epigenetics.” One extraordinary example is presented in recent work by Barbara Fredrickson and her colleagues that shows how different forms of wellbeing correlate with different gene transcription (as discussed in the next section).

생물학과 신경과학 - 생리적으로 확인할 수 있는 웰빙

생물학자와 신경과학자들은 생리신호와 뇌신호를 이용해서 정서를 탐지하고 이해한다. 웰빙에 영향을 주는 생물학적 요인을 연구하는 사람들도 있지만(유전자나 신체건강과 같은) 일부는 이런 생물학적 체계가 환경조건과 어떻게 상호작용하는가를 연구한다.

이런 작업은 정서컴퓨팅 분야에서 HCI와 가장 확실하게 교차한다. 라파엘( )의 연구팀은 HCI에서 정서를 탐지하기 위해 생리신호를 활용하며 특히 교육이나 정신건강분야에 대한 적용을 위한 연구를 한다. 예를 들어, 학생이 온라인 활동을 통해 피드백을 받을 대의 영향을 측정할 때 생리신호를 활용할 수 있다( ). 또 뇌전도( ), 근전도( ), 피부전도(skin conductance), 호흡 등 여러 생리체계의 신호를 조합할 수도 있다. 정서컴퓨팅과 관련한 이런 작업들에 대해 제 4장에서 다시 다룬다.
신경과학자는 우리가 경험하는 정서나 인지, 행동과 관련된 전기화학적 활동패턴을 찾아내려고 한다. 지난 20년 간, 이런 연구에 회복탄력성과 명상수련 같은 웰빙증가와 관련된 특징 뿐 아니라 긍정정서가 들어??되었다.

과학자들은 뇌영상 기법으로 정서와 관련된 뇌의 구조와 과정을 더 많이 알게되었다. 예를 들어, 학자들은 처음 만나서 하는 질문인 “잘 지내?”와 같은 질문에 답하는 것을 관장하는 신경망을 찾아낼 수도 있다. 우리의 체화된(embodied) 느낌과 정서의 내적 표상은 전측 섬뇌(anterior insula cortex)인 것같다. 전측 섬뇌는 피험자가 사랑과 분노, 공포, 슬픔, 행복, 모욕감, 사회적 배제, 공감과 같은 주관적인 정서경험을 할 때 함께 활성화된다.

이런 신경관련물들은 “global emotional moment” 및 이런 moment가 일련의 시간에 따른 분위기의 표상을 산출한다는 사실을 설명하는 동질정체적( ), 환경적, 쾌락적, 동기적, 사회적, 인지적 활동을 포함하는 자각모형을 제안하는 데에 활용되었다. 이 모형에서는 웰빙의 요소로 보통 8가지 친사회적 정서(사랑, 희망, 기쁨, 용서, 연민, 믿음, 경외감, 관대함)를 꼽는다. 주목할 만한 것은 이 정서들이 모두 자기보다는 인간적 연결성을 포함하는 것이라는 점이다. 이런 모형들은 우리의 모든 정서가 긍정적이어야 한다고 요구하지 않으며, 부정적 정서도 생존을 위해서 필요한 것임을 인정한다( ).

정서 및 사회신경과학은 우리의 뇌가 우리의 경험에 따라 만들어진다는 것을 인정한다. 예를 들어, fMRI연구들은 생애초기의 스트레스와 영양환경이 뇌의 발달에 강력한 영향을 미친다는 것을 보여준다. 데이비슨 등( )은 의도적으로 친사회적 행동과 웰빙을 촉진할 수 있는 개입법을 설계할 수 있다는 증거를 모았다. 데이비슨의 연구에 따르면, 규칙적인 운동과 인지치료, 명상수련을 통해 뇌의 구조적 변화를 촉발할 수 있는데, 이는 우리가 그런 목적으로 훈련과정을 개발할 수 있음을 시사한다. 이런 작업은 텍 역시 그런 분야에 영향을 미칠 잠재력이 있음을 보여준다.

최근 연구에서 데이비슨 등( )은 이런 결과를 어떻게 교육장면에 쓸 수 있는지 논의했다. 그들은 이미 효과가 있으며 또한 뇌의 가소성에 따른 변화를 촉발할 수 있는 것으로 밝혀진 체계적인 명상수련을 통해 웰빙의 기본요소를 발달시킴으로써 젊은이들의 친사회적 행동과 학업성취를 지원할 수 있다고 주장한다. 또한 비디오게임과 같은 텍이 마음챙김과 공감을 포함하는 긍정적 성격을 개발하는 데에 가능성이 있다고 지적했다.

웰빙의 생리적 요인을 연구한 학자들은 일주기와 섭식조절, 운동과 같은 신체활동과 심리적 건강의 관계를 연구한다. 예를 들어, 시드니 대학의 힉키( )는 만성생리체계(우리의 신체시계)와 그것이 우울에 미치는 영향을 연구한다. 이런 분야의 연구도 긍정컴퓨팅의 작업에 도움이 될 수 있다. 우리는 힉키와 함께 사회관계망에서 수면주기에 대한 정보를 모아서 우울의 위험이 있는 사람들을 탐지해내는 방법을 연구하고 있다.

성격특질( )과 유전자도 웰빙을 결정하는 요인으로 알려져있다. 1990년 대에 신경과학자들은 정신질환의 유전적 결정요인을 찾아낼 수 있으리라는 희망을 가졌다. 그 이래로 우리는 정신장애와 만개 모두에 포함되는 유전자의 정확한 숫자와 복잡한 특징을 더 잘 인식하게 되었고 여러 분야에서 진전이 있었다. 예를 들어, 어떤 획기적인 논문은 우울과 웰빙에 관련된 유명한 신경전달물질인 세로토닌을 우리의 신경세포가 얼마나 잘 운반하는가를 결정하는 5-HTT 촉진자로 알려진 어떤 유전자 배열의 영향을 밝혀냈다. 이들은 짧은 대립형질 유전자복제판을 한 두 개 가지고 있는 사람들은 생활스트레스 사건을 겪을 때 우울에 더 취약하다는 것을 밝혀냈다. 다른 연구( )는 회복탄력성의 네 가지 범주를 밝혀냈는데, (1) 부정이나 긍정사건 모두에 매우 반응적인 유형, (2) 둘 모두에 반응성이 낮은 유형, 3) 부정사건에 취약한 유형, (4) 긍정사건의 영향을 많이 받거나 “유리한 점에 민감한” 유형이 그것이다.

명백하게 타고난 요인인 유전이나 성격특질도 영향을 받을 수 있고 바뀔 수 있다. 예를 들어, 우리는 이제 유전자의 발현이 환경과 개인적 경험에 의해 수정될 수 있음을 알고 있는데 이런 연구 분야가 발생기구학(epigenetics)이다. 한가지 예외적인 사례를 프레드릭슨 등( )의 최근 연구에서 찾아볼 수 있는데, 그녀는 서로 다른 유형의 웰빙이 어떻게 서로 다른 유전체 전사(gene transcription)와 관련이 있는지를 보여준다(다음 절에서 논의한 것처럼).

Hedonic versus Eudaimonic Wellbeing at the Molecular Level

If you're confused about whether to take a hedonic or eudaimonic approach to wellbeing, you might consider letting your cells decide. Fascinating new research (Fredrickson et al., 2013) suggests that the human genome may be more sensitive to the differences between hedonic and eudaimonic wellbeing than either our affective states or our philosophers have been. It turns out that hedonic wellbeing and eudaimonic wellbeing are correlated with different patterns of gene expression. Moreover, the molecular patterns associated with hedonic wellbeing are associated with a stress response that promotes inflammation and decreases antibody production. In contrast, eudaimonic wellbeing is associated with transcription patterns that increase antibody production. Fredrickson and her colleagues conclude: “If ‘the good life' is a long and healthy life free from the allostatic load of chronic stress, threat, and uncertainty, CTRA gene expression may provide a negative reference point for how not to live. … If we ask which type of happiness most directly opposes that molecular antipode, a functional genomic perspective favors eudaimonia”. According to their findings, hedonic forms of wellbeing (arising from pleasure) are associated with increases in a particular type of stress-related gene expression, whereas eudaimonic wellbeing (arising from connectedness and purpose) is associated with decreases in the same stress-related gene expression. The message is that in the long term it's eudaimonic wellbeing that promotes health.

The growth in scientific and popular understanding of wellbeing over the past decade has been transformative, but how exactly does one draw a connection between theories of wellbeing and the design of technology? In our experience, the philosophical underpinnings of any design work, be they explicit or unconscious, can have profound effects on design outcomes. By way of demonstrating just how different wellbeing theories might support different and often complementary design approaches, we take a look at the driverless car in the hypothetical case study in the next section.

분자수준의 쾌락적 웰빙과 행복론적 웰빙

웰빙을 어떤 접근법으로 해야할지 혼란스럽다면, 당신의 세포가 결정하도록 할 수 있다. 재미있는 새로운 연구가 ( ) 인간 유전체는 우리의 정서 상태나 철학의 차이보다는 쾌락적 웰빙과 행복론적 웰빙의 차이에 더 민감할 수 있음을 보여준다. 쾌락적 웰빙과 행복론적 웰빙은 서로 다른 유전자 발현패턴과 상관이 있는 것으로 드러났다. 게다가 쾌락적 웰빙과 관련된 분자수준의 패턴은 염증을 촉진하고 항체생산을 감소시키는 스트레스반응과 관련이 있다. 반대로 행복론적 웰빙은 항체생산을 촉진하는 전사패턴과 관련이 있다. 프레드릭슨 등은 이렇게 결론지었다. ” ‘좋은 삶’이 만성 스트레스와 위협, 불확실성이라는 알로스테틱(allostatic) 부하를 받지 않고 오래도록 건강하게 사는 것이라면, CTRA 유전자의 발현은 어떻게 하면 살지 않을 수 있을까를 보여주는 부정적 참조점이 된다. … 만일 우리가 어떤 종류의 행복이 그같은 분자수준의 대립물과 가장 직접 대립하는 것인지 묻는다면, 기능적 유전자의 관점은 행복론적 행복을 선호한다.” 이런 결과에 따르면, 쾌락적 유형의 웰빙(즐거움에서 나오는)은 특정 유형의 스트레스관련 유전자 발현을 증가시키는 것과 관련이 있는 반면에 행복론적 웰빙(연결성과 삶의 목적에서 나오는)은 바로 그 스트레스관련 유전자 발현의 감소와 관련이 있다. 이 메시지는 장기적으로 건강을 촉진하는 것은 행복론적 웰빙이라는 것이다.

지난 10년 간 웰빙에 대한 대중적 이해와 과학적 이해는 많이 달라졌다. 하지만, 웰빙 이론과 텍 디자인간의 연결을 끌어내려면 정말 어떻게 해야할 것인가? 우리의 경험으로는 모든 디자인 작업의 철학적 탐구는 그것이 의식적이든 무의식적이든 디자인 결과에 강력한 영향을 미칠 수 있다. 서로 다른 웰빙 이론들이 어떻게 서로 다르면서 때로는 보완적인 디자인 접근법들을 지원할 수 있는지 보여주는 방법으로 다음 절에서는 가상적인 무인 자동차 사례를 살펴본다.

Wellbeing-Informed Design - a Hypothetical Case Study

The challenges of designing driverless cars go far beyond aerodynamics, fuel efficiency, and safety. We speculate here (albeit playfully) about the approach that four different designers, drawing on four different theoretical viewpoints, might take to the design process.

• The hedonic designer: Driving time is pleasure time. The hedonic designer will focus on improving those aspects of car design from which we derive positive emotion (heated leather seats, movie screens, and the flower vase in a Volkswagen Beetle come to mind). This designer might improve the quality of the sound system by personalizing music to mood or include massage functions in the chair (we're sold already). She might also seek to identify and remove aspects that caused negative emotions in previous models. She could look to develop driver happiness over a longer term as well?for example, by providing information to help the driver understand his own triggers for road rage. Like an emotionally aware geographical positioning system (GPS), the hedonic car would choose routes based on the feelings of happiness they inspire?for example, by avoiding traffic or privileging scenic views.

• The SDT designer: Driving is about connectedness, competence, and control. A designer guided by SDT would be concerned with a user's sense of autonomy, competence, and relatedness. As such, he might seek to compensate the sense of autonomy lost by not physically doing the driving. Features that allow the user to shift to manual control, to enact some steps modularly, and/or to give clear directions to the system would be critical. Research on brain?computer interfaces and wheelchair design for paraplegics make the human need for autonomy very clear (Nijholt et al., 2008). A nondriving driver's sense of autonomy relies on the driver's sense of competence in controlling the vehicle, in endorsing its behavior, and in getting where he wants to go. Finally, the SDT designer may look to support a feeling of relatedness via easy communication with the driver's network of contacts or perhaps with other people in nearby cars or the people and places going past.

• The values-sensitive designer: Driving the way you think it should be. Whereas vehicle engineers may value automation for its own sake and without question, those who love to drive may consider automation an absolute killjoy. A designer with a background in values-sensitive design (VSD) will seek to make explicit particular values, relating both to the audience and to the designers of the vehicle. To those considering overall effects on society, automation is a threat to the livelihood of the millions of people who make a living from driving. A VS designer might also focus on the serious issues of privacy posed by a driverless car, which may be of greater or lesser importance to different cultural groups. For example, since a driverless car is connected to a mapping system that tracks its coordinates, a VS designer might aim to add a way for GPS data to be anonymized, encrypted, or customized. Although VSD is not a theory of wellbeing or based on a theory of wellbeing, work on values will inevitably interact with work on wellbeing (we discuss this area in more detail in chapter 4).

• The biological wellbeing designer: Driving that's good for you. A designer aware of the relationships between physical health and psychological wellbeing might seek to make better use of the copious amount of time a user spends sitting down in a car. He might incorporate exercise devices into the seating (modeling her design after the Flintstones' car for example), design pods for power napping, provide a fresh-water dispenser, or program the car to deliberately park several blocks away to encourage the user to walk.

In this chapter, we have endeavored to highlight and synthesize a number of growing research areas that inform the science of optimal human functioning. We have also sought to demonstrate how various theories of wellbeing can practically influence design decisions and technological affordances. Although the focus has been on the physical and mental health fields, in the next chapter we expand our horizon to include some of the critical fonts of discovery emerging from disciplines outside of health?from economics and policy to architecture and education.

웰빙을 고려한 디자인 - 가상의 사례연구

무인자동차 역주. 이 맥락에서 무인자동차란 운전자가 따로 없는 자동차를 말한다. 원문은 driverless car이다.
디자인이라는 도전은 공기역학, 연료효율성, 안전성을 훨씬 능가하는 문제이다. 우리는 여기서 서로 다른 네 가지 이론적 관점을 취하는 네 명의 디자이너가 디자인과정에 접근하는 방식을 살펴본다.

• 쾌락주의적 디자이너: 운전하는 시간은 즐거운 시간. 쾌락주의적 디자이너는 긍정적 정서를 이끌어낸다는 관점에서 자동차디자인을 개선하는 데에 초점을 맞출 것이다(폭스바겐의 방열 가죽시트, 영화감상용 스크린, 꽃 병이 떠오른다). 이 디자이너는 개인별 분위기에 맞출 수 있게 사운드 시스템의 질을 개선한다거나 좌석에 마사지 기능을 부가할 수도 있다(이미 그런 차가 있다). 또한 과거 모델에서 부정적 정서를 야기하는 측면들을 찾아내어 제거할 수도 있다. 운전자의 장기적인 행복을 향상시키는 방법, 예를 들어, 운전자가 자신의 운전 중 분노를 유발하는 요인을 이해할 수 있는 정보를 제공한다거나 하는 방법도 찾아볼 수 있다. 쾌락주의적 자동차는 정서 자각 GPS(지리좌표체계)처럼 체증구간을 우회한다거나 경??좋은 경로를 택하는 등으로 행복감을 기준으로 운행할 수도 있을 것이다.
• SDT 디자이너: 운전은 연결성과 유능감, 통제감의 문제. SDT 중심의 디자이너는 사용자의 자율성과 유능감, 관계성의 정서에 관심이 있을 것이다. 그래서 실제 운전을 하지 않음에 따른 자율감 상실을 보상할 방도를 찾으려 할 것이다. 수동조작으로 변환할 수 있거나 어떤 단계는 모듈화한다거나 자동차에 명확한 지시를 할 수 있게 한다는 등의 장??중요할 것이다. 뇌와 컴퓨터 상호작용 및 마비환자를 위한 휠체어 디자인에 대한 연구는 인간의 자율감 욕구를 극명하게 보여준다( ). 직접 운전을 하지 않는 운전자의 자율감은 그 운송수단을 통제하고, 작동을 허락하고, 원하는 곳으로 갈 수 있는 유능감에 달려있다. SDT 디자이너는 운전자의 인적 네트웤이나 ?樗?있는 차안의 다른 사람들 또는 들르는 곳의 사람들과 쉽게 소통할 수 있게 함으로써 연결감을 지원할 수 있는 방법을 찾아낼 수도 있을 것이다.
• 가치지향 디자이너: 운전은 내가 원하는 가치를 구현하는 방법. 자동차 공학자들은 자동화를 아무 의심 없이 그 자체로 가치 있는 것으로 볼지 모르지만, 운전을 즐기는 사람들한테 자동화는 완전히 쥐약이다. 가치민감형 디자인(value-sensitive design; VSD)의 배경을 가진 디자이너는 겉으로 드러나는 독특한 가치를 창출해서 디자이너와 고객을 연결할 방법을 찾을 것이다. 전체적인 사회적 효과를 고려하는 사람들??자동화는 운전으로 살아가는 수백만명의 삶에 대한 큰 위협이다. 어떤 가치지향 디자이너는 무인자동차가 제기하는 사생활보호라는, 문화에 따라 중요성이 다를 수 있는, 심각한 쟁점에 초점을 맞출 수도 있다. 예를 들어, 무인자동차는 항법장치와 연동되어 있기 때문에, 가치지향의 디자이너는 GPS 자료를 익명화하거나 암호화하거나 개별화할 수 있는 방법을 부여하고자 할 수 있다. VSD는 웰빙이론이 아니고 또 그 이론을 바탕으로 하는 것도 아니지만, 가치의 문제는 웰빙에 관한 작업에서 피해갈 수가 없을 것이다(이에 관해 제 4장에서 더 자세히 다룬다).
• 생물학적 웰빙 디자이너: 운전자??유익한 운전. 신체건강과 심리적 웰빙의 관계를 아는 디자이너는 사용자가 자동차에 앉아있는 긴 시간을 더 잘 활용할 수 있는 방법을 찾으려 할 것이다. 좌석에 운동기구를 통합할 수도 있고(예를 들어, Flintstones의 자동차를 추종하는 디자인 역주. 프린스톤 가족은 1960년 9월 30일부터 1966년 4월 1일까지 ABC에서 방영한 미국의 애니메이션 텔레비전 시트콤이다. 구석기 시대를 배경으로 하며 가족들의 에피소드를 그린 애니메이션이다. 여기 등장하는 프린스톤의 자동차는 돌과 나무로 만들었고 발의 힘으로 가는 차이다. Time지의 10대 가상 자동차 3위에 뽑히기도 했다. ), 낮잠용 공간이나 정수장치를 설계한다거나 아니면 내려서 걷도록 일부러 목적지에서 좀 떨어진 곳에 주차하는 프로그램을 장착할 수도 있다.

이 장에서는 인간의 최적 기능이라는 과학에 도움이 되는 새로이 성장하는 연구분야의 성과을 소개하고 통합하고자 했다. 우리는 또한 다양한 웰빙이론이 실제 디자인과 텍의 구체적 행동에 어떻게 영향을 미칠 수 있는지를 예증하려고 하였다. 초점은 심신건강분야에 있지만, 다음 장에서는 우리의 지평을 넓혀서 건강이외의 분야인 경제학과 정치학에서 건축과 교육에 이르는 분야에서 나오고 있는 중요한 시사점들을 살펴볼 것이다.

Expert Perspectives - Technology for Mental Health

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Note

1. See http://www.selfdeterminationtheory.org/.

References

AlZoubi, O., Hussain, M. S., D'Mello, S., & Calvo, R. A. (2011). Affective modeling from multichannel physiology: Analysis of day differences. In Affective computing and intelligent interaction: International conference, ACII 2011, proceedings (pp. 4-13). Heidelberg: Springer-Verlag Berlin.
Bolger, N., Davis, A., & Rafaeli, E. (2003). Diary methods: Capturing life as it is lived. Annual Review of Psychology, 54(1), 579-616.
Botella, C., & Riva, G. (2012). The present and future of positive technologies. Cyberpsychology, Behavior, and Social Networking, 15(2), 78-84.
Boyce, C. J., & Wood, A. M. (2011). Personality prior to disability determines adaptation: Agreeable individuals recover lost life satisfaction faster and more completely. Psychological Science, 22(11), 1397-1402.
Brickman, P., Coates, D., & Janoff-Bulman, R. (1978). Lottery winners and accident victims: Is happiness relative- Journal of Personality and Social Psychology, 36(8), 917-927.
Calvo, R. A., & Peters, D. (2012). Positive computing: technology for a wiser world. Interactions (New York, N.Y.), 19(2), 28-31.
Calvo, R. A., & Peters, D. (2013). Promoting psychological wellbeing: loftier goals for new technologies. IEEE Technology and Society, 32(4), 19-21.
Caspi, A., Sugden, K., Moffitt, T. E., Taylor, A., Craig, I. W., Harrington, H., … Poulton, R. (2003). Influence of life stress on depression: Moderation by a polymorphism in the 5-HTT gene. Science Signaling, 301(5631), 386-389.
Clarke, G. N., Hornbrook, M., Lynch, F., Polen, M., Gale, J., Beardslee, W., … Seeley, J. (2001). A randomized trial of a group cognitive intervention for preventing depression in adolescent offspring of depressed parents. Archives of General Psychiatry, 58(12), 1127-1134.
Costa, P., & McCrae, R. (1992). The five-factor model of personality and its relevance to personality disorders. Journal of Personality Disorders, 6, 343-359.
Craig, A. D. B. (2009a). Emotional moments across time: A possible neural basis for time perception in the anterior insula. Philosophical Transactions B, 364(1525), 1933-1942.
Craig, A. D. B. (2009b). How do you feel-now- The anterior insula and human awareness. Nature Reviews, Neuroscience, 10(1), 59-70.
Davidson, R., Dunne, J., Eccles, J. S., Engle, A., Greenberg, M., Jennings, P., … Vago, D. (2012). Contemplative practices and mental training: Prospects for American education. Child Development Perspectives, 6(2), 146-153.
Davidson, R. J., & McEwen, B. S. (2012). Social influences on neuroplasticity: Stress and interventions to promote well-being. Nature Neuroscience, 15, 689-695. doi:10.1038/nn.3093.
De Botton, A. (2006). The Architecture of Happiness. New York: Pantheon.
Diener, E. (2000). Subjective well-being: The science of happiness and a proposal for a national index. American Psychologist, 55(1), 34-43.
Diener, E., Lucas, R. E., & Scollon, C. N. (2006). Beyond the hedonic treadmill: Revising the adaptation theory of well-being. American Psychologist, 61(4), 305.
Diener, E., & Suh, E. M. (2003). National differences in subjective well-being. In Well-being: The foundations of hedonic psychology (pp. 434-450). New York: Russell Sage Foundation.
Fredrickson, B. L., Grewen, K. M., Coffey, K. A., Algoe, S. B., Firestine, A. M., & Arevalo, J. M. G. … Cole, S. W. (2013). A functional genomic perspective on human well-being. Proceedings of the National Academy of Sciences of the United States of America, 110(33), 13684-13689.
Gilbert, P., & Choden (2013). Mindful compassion. London: Constable & Robinson.
Goleman, D. (2005). Emotional intelligence: Why it can matter more than IQ. 10th anniversary ed. New York: Bantam Books.
Gorini, A., Gaggioli, A., Vigna, C., & Riva, G. (2008). A second life for eHealth: Prospects for the use of 3-D virtual worlds in clinical psychology. Journal of Medical Internet Research, 10(3), e21.
Hassenzahl, M., & Beu, A. (2001). Engineering joy. IEEE Software, 18(February), 70-76.
His Holiness the 14th Dalai Lama of Tibet. (2005). “Science at the crossroads.” November 12. At http://dalailama.com/messages/buddhism/science-at-the-crossroads.
Huppert, F., Marks, N., Clark, A., Siegrist, J., Stutzer, A., Vittersø, J., … Wahrendorf, M. (2009). Measuring well-being across Europe: Description of the ESS well-being module and preliminary findings. Social Indicators Research, 91(3), 301-315.
Huppert, F. A., & So, T. T. C. (2013). Flourishing across Europe: Application of a new conceptual framework for defining well-being. Social Indicators Research, 110(3), 837-861.
Kabat-Zinn, J. (2003). Mindfulness-based interventions in context: Past, present, and future. Clinical Psychology: Science and Practice, 10(2), 144-156.
Kahneman, D. (1999). Objective happiness. In D. Kahneman, E. Diener, & N. Schwarz (Eds.), Well-being: The foundations of hedonic psychology (pp. 3-25). New York: Russell Sage Foundation.
Kahneman, D., Diener, E., & Schwarz, N. (Eds.). (1999). Well-being: The foundations of hedonic psychology. New York: Russell Sage Foundation.
Mayer, G. R. (1995). Preventing antisocial behavior in the schools. Journal of Applied Behavior Analysis, 28(4), 467-478.
Mayer, J. D., Caruso, D. R., & Salovey, P. (1999). Emotional intelligence meets traditional standards for an intelligence. Intelligence, 27(4), 267-298.
Mayer, J., Salovey, P., & Caruso, D. (2002). Emotional intelligence test. Toronto: MSCEIT.
Nijholt, A., Tan, D., Pfurtscheller, G., Brunner, C., Millan, J. R., Allison, B., et al. (2008). Brain-computer interfacing for intelligent systems. IEEE Intelligent Systems, 23(3), 72-79.
Norman, D. A. (2005). Emotional design: Why we love (or hate) everyday things. New York: Basic Books.
O'Connell, M. E., Boat, T., & Warner, K. (2009). Preventing mental, emotional, and behavioral disorders among young people: Progress and possibilities. Washington, DC: National Academies Press.
Payton, J., Wardlaw, D., Graczyk, P. A., Bloodworth, M. R., Tompsett, C. J., & Weissberg, R. P. (2000). Social and emotional learning: A framework for promoting mental health and reducing risk behavior in children and youth. Journal of School Health, 70(5), 179-185.
Peterson, C., & Seligman, M. E. P. (2004). Character strengths and virtues: A handbook and classification (p. 800). Oxford: Oxford University Press.
Pluess, M., & Belsky, J. (2013). Vantage sensitivity: Individual differences in response to positive experiences. Psychological Bulletin, 139(4), 901-916. doi: 10.1037/a0030196.
Pour, P. A., Hussain, M. S., AlZoubi, O., D'Mello, S. K., & Calvo, R. A. (2010). The impact of system feedback on learners' affective and physiological states. In V. Aleven, J. Kay, & J. Mostow (Eds.), Intelligent tutoring systems (vol. 6094, pp. 264-273). Berlin: Springer.
Quoidbach, J., Berry, E. V., Hansenne, M., & Mikolajczak, M. (2010). Positive emotion regulation and well-being: Comparing the impact of eight savoring and dampening strategies. Personality and Individual Differences, 49(5), 368-373.
Riva, G., & Banos, R. (2012). Positive technology: Using interactive technologies to promote positive functioning. Cyberpsychology, Behavior, and Social Networking, 15(2), 69-77.
Riva, G., Cipresso, P., Mantovani, F., Dakanalis, A., & Gaggioli, A. (2013). New technologies for improving the psychological treatment of obesity. Berlin: Springer.
Salovey, P., & Mayer, J. D. (1990). Emotional intelligence. Imagination, Cognition, and Personality, 9(3), 185-211.
Sander, T. (2011). Positive computing. In R. Biswas-Diener (Ed.), Positive psychology as social change (pp. 309-326). New York: Springer.
Seligman, M. (2002). Authentic happiness: Using the new positive psychology to realize your potential for lasting fulfillment. New York: Free Press.
Seligman, M. E. P., & Csikszentmihalyi, M. (2000). Positive psychology: An introduction. American Psychologist, 55(1), 5.
Vaillant, G. E. (2012). Positive mental health: Is there a cross-cultural definition- World Psychiatry: Official Journal of the World Psychiatric Association (WPA), 11(2), 93-99.

Let's be honest: engineers and computer scientists aren't known for advanced social skills or for their perspicacity with regard to human emotions. Some would also be quick to point out we have a weakness for letting technological interests drive all our decision making. But shameless stereotyping aside, we believe that when it comes to designing for wellbeing, no matter what field you're in, it's critical not to go it alone.

No attempt to influence or investigate issues as multifaceted as human psychological wellbeing should be undertaken without a rigorously multidisciplinary approach. Neglecting human experience is bad for technology design generally, but it is totally counterproductive for positive computing. Truly human-centered design for positive computing will rely on interdisciplinary teams and collaboration.

In addition to work in psychology, medicine, and brain science, our contemporary understanding of wellbeing has been contingent on progress in anthropology, sociology, philosophy, economics, public policy, media studies, and even architecture, literature, and art. In this chapter, we look at wellbeing through the lenses of some of these disciplines and at how they have charted significant territory on the journey to understanding psychological flourishing.

Economics -- Wellbeing as Something Money Still Can't Buy

Economics is surprisingly, or perhaps quite logically, one of the richest sources of research on wellbeing. Most notably, it has provided rigorous methods for measuring levels of wellbeing across populations. For example, the Handbook on the Economics of Happiness (Bruni & Porta, 2007) is a compendium of research at the intersection of economics, public policy, and psychological wellbeing. Well-Being: The Foundations of Hedonic Psychology (Kahneman, Diener, & Schwarz, 1999) is an earlier volume that supported much of the growth in this field. In the chapter “Objective Happiness,” Daniel Kahneman provides one of the best introductions to wellbeing measurement techniques available, a topic we discuss in greater detail in chapter 5 on methodologies.

Economics may also help to explain the recent growth of lay interest in wellbeing psychology. Richard Ryan and Edward Deci (2001) have identified two periods of peaking interest in wellbeing in the history of psychology: the 1960s and the 2000s. They note that these two periods coincide with times of affluence.

Despite the recent global financial crisis, those in industrialized Western society are still in general relatively wealthier than we ever have been before?gross national product per capita has tripled since the 1960s (Helliwell, Layard, & Sachs, 2012). This wealth has also come with great progress in the development of digital technologies?we are certainly more immersed in technology than we ever have been before. And yet for the so-called industrialized world neither increased technification nor continued increases in wealth have led to much greater psychological wellbeing according to the statistics.

A seminal study by Richard Easterlin (1974) famously provided early evidence that the link between wealth and happiness is weaker than popular culture would have us think. Easterlin found that wealthier people within a country do tend to be more satisfied with their lives at any given point in time, but that happiness does not increase with economic growth over time (a finding henceforth dubbed the “Easterlin Paradox”). In other words, the increased happiness that money can provide is relative and seems to adapt as economies grow. Therefore, using economic growth measures, such as gross domestic product, as proxy measures for a nation's wellbeing is ineffective.

It's also worth noting that, according to Easterlin's research, the impact that wealth has on wellbeing is significant up to the point at which basic needs are met. After that point, the impact is small. Easterlin's results suggest that relative increases in happiness are influenced not only by an individual's state of wealth, but also by how it compares to others. The powerful impact of comparison on wellbeing is echoed in psychological research on happiness and self-esteem, which we look at in more detail in part II.

As Easterlin himself noted, his original work had some limitations. The study combined data from 29 Gallup Poll?type surveys and produced a single measure of self-reported wellbeing on a scale from 1 to 10. Forty years later, approaches to measuring wellbeing have evolved significantly. Researchers such as Felicia Huppert and Timothy So have studied such measures seeking multidimensional approaches for greater validity and explicatory power. We look more closely at these measures in the methodologies chapter. But for now we consider how findings in economics have influenced change in public policy.

Easterlin's work has been the focus of dozens of studies and remains hotly debated. The United Nations' first World Happiness Report (Helliwell et al., 2012) provides a summary of the sometimes contradictory literature on this topic. In general, it is understood that economic growth does not automatically increase the average wellbeing of a population. But both wellbeing and economic status need to be unpacked further. For example, the impact of income comparison is significant. When people are asked, “How important is it for you to compare your income with other people's income?” the greater the importance they report, the less satisfied they are with their lives (based on the European Social Survey, as cited in Helliwell et al., 2012).

Furthermore, employment (and presumably its concomitant benefits, security and self-esteem) is a core component of the economic equation. There is no doubt that higher levels of employment have a positive effect on wellbeing. But economic booms often produce inflation, which has a negative effect. In the end, stability seems to be a good target, especially considering evidence that loss aversion (losing x dollars) has a bigger impact than an equivalent gain (receiving x dollars).

It's hard to avoid speculation that the growing interest in wellbeing in the Western world is at least in part due to a gradual societal realization that money doesn't, after all, bring reliable happiness. But this is probably not the whole picture. Significant advancements in our ability to research, evaluate, and operationalize wellbeing are also at the heart of this trend.

For instance, after a seminal study published in Science (Golder & Macy, 2011) showed that social media data could be used to study moods over time, many other studies plundering the wealth of publically available social interaction data have followed in aid of better understanding the human experience. One such study (Mitchell, Harris, Frank, Dodds, & Danforth, 2013) combined geotagged tweets (80 million words in total) with demographic and health information from annual surveys. They used the data to build taxonomies that describe the happiness of states and cities across the United States, to correlate demographic information with wellbeing, and to correlate linguistic features to levels of education and even obesity rates. These studies provide evidence that public social media data can be used to investigate communities' overall wellbeing levels in real time?an incredible opportunity for nonintrusive methods to inform research and even policy.

Government and Policy: Increasing Gross National Happiness and General Wellbeing

The care of human life and happiness, and not their destruction, is the sole legitimate object of government.

- Thomas Jefferson, To the Citizens of Washington County, Maryland (1809)

In an influential paper, psychologists Ed Diener and Martin Seligman (2004) argued that “policy decisions at the organizational, corporate and governmental levels should be more heavily influenced by issues related to wellbeing?people's evaluations and feelings about their lives.” They proposed the creation of a national wellbeing index that would periodically measure wellbeing in representative samples of the population. The index would be multidimensional, including “positive and negative emotions, engagement, purpose and meaning, optimism and trust, and the broad construct of life satisfaction,” and would be assessed and updated periodically so it could more accurately inform policymaking. Since then, much has happened to see Deiner and Seligman's vision made real.

In 2007, a group of partners including the European Commission, the European Parliament, and the Organization for Economic Cooperation and Development hosted a high-level conference called “Beyond GDP,” with the objectives of determining “which indices are most appropriate to measure progress, and how these can best be integrated into the decision-making process and taken up by public debate.” The partners continue to work on developing and measuring social, environmental, and wellbeing indicators.1

In 2008, French president Nicolas Sarkozy commissioned a panel of experts, including Nobel Prize?winning economists Joseph Stiglitz and Amartya Sen, to reassess measures of national progress. The resulting report moved the French government to launch a new era in which national measures of progress would take wellbeing into account.

In 2011, the United Kingdom launched the National Well-Being Programme, a part of the Office for National Statistics, with the motto “Measuring what matters.” The New Economics Foundation (whose tagline is “economics as if people and the planet mattered”) created the Happy Planet Index, which combines data on experienced wellbeing, life expectancy, and ecological footprint into a “global measure of sustainable well-being.”2

Although the United States has been slower to consider measures beyond gross domestic product, individual cities and counties have established regional measurement initiatives to inform local leadership, and the federal government established a panel to investigate measures of happiness. US commercial initiatives are also collecting data in ways similar to government efforts in other countries: The Gallup?Healthways Well-Being Index undertakes an impressive live daily assessment of health and wellbeing measures across the United States.3

But policy change has by no means been relegated to Europe and North America. In fact, the seeds of this movement were planted by the king of Bhutan, who in 1972 declared that gross national happiness was more important than gross national product. For decades, the country took to measuring a multidimensional gross national happiness index and to spreading the word internationally.

Although the current prime minister of Bhutan has set aside focus on gross national happiness, the idea of alternative metrics for national progress has had global impact. In 2012 at a meeting entitled “Happiness and Well-Being: Defining a New Economic Paradigm,” United Nations Secretary-General Ban Ki-moon declared the need for “a new economic paradigm that recognizes the parity between the three pillars of sustainable development. Social, economic, and environmental well-being are indivisible. Together they define gross global happiness” (“Ban: new economic paradigm…,” 2012).

In the same year, the United Nations proclaimed March 20 the “International Day of Happiness” to recognize “the relevance of happiness and well-being as universal goals and aspirations in the lives of human beings around the world and the importance of their recognition in public policy objectives.”4 The United Nations' first World Happiness Report (Helliwell et al., 2012) provides a detailed analysis of how different countries compare on the happiness scale.

But, of course, measurement is only half the battle. Governments are also engaged in determining how best to use these measures in public policy, and we in the technology field can learn much by observing their various strategies. Encouraging healthy behavior is one approach policymakers have often taken. The UK government's Behavioural Insights Team within the Cabinet Office (referred to as the “Nudge Unit”) “applies insights from academic research in behavioural economics and psychology to public policy and services.”5

Educating the public as to things they can do to improve their own wellbeing is another approach. In 2008, the UK Government Office for Science commissioned a set of evidence-based actions people can take to improve their psychological wellbeing. The idea was to do for mental health what a campaign promoting “five a day” (of fruits and vegetables) had done for physical health. The result was a thorough review (Denham, Beddington, & Cooper, 2008) of extensive research into wellbeing consolidated into “five ways to well-being”: “connect,” “be active,” “take notice,” “learn,” and “give.” Elegant in their simplicity and yet powerful in the strength of the research behind them, the “five ways” could provide a valuable set of pillars for work in positive computing.

Initiatives will continue to emerge and evolve, and they all will face the challenge of deciding how to be guided by new information toward the development of effective and equitable public policy that respects both privacy and autonomy. As with any government decision, the line between where a government should and shouldn't intervene on behalf of national wellbeing will remain a point of ongoing controversy and negotiation. Since large economic gaps within a society produce unhappiness, should we design the tax code to minimize the gap, thus supporting happiness? Should government regulate junk-food advertising targeted to children in order to reduce the harm to wellbeing done by consumption of these foods? If married people tend to be happier according to research, should the government invest in matchmaking? Some decisions will seem easier to rule out than others, but the line will represent a constant point of dialectic? what's most heartening is that we are finally having these discussions.

Even in the United States, where the population is arguably among the most publically averse to tax increases and government intervention, a government's responsibility to promote public happiness has been woven into the very foundations of the country. The Declaration of Independence famously states that we are all divinely entitled to “Life, Liberty, and the pursuit of Happiness” and, less famously, “that to secure these rights, Governments are instituted among Men, deriving their just powers from the consent of the governed.” B. S. Bernanke, former chairman of the US Federal Reserve gave a commencement address in 2010 that brought these eighteenth-century ideals into modern focus. Entitled “The Economics of Happiness,” his address suggested that wealthy countries have the resources to invest in things that contribute to happiness, such as medical care, good nutrition, and sanitation; to maintain a clean environment, and to “provide leisure time and facilities, less physically exhausting and more interesting work, higher education levels, greater ability to travel, and more funding for arts and culture.”6

Bernanke's commencement advice suggests that organizations focus on supporting conditions for wellbeing by investing in those things that can positively affect it. Richard Thaler and Cass Sunstein (2008) support a “libertarian paternalism” that seeks to help citizens make healthier decisions while preserving autonomy and choice. Wellbeing researcher Nic Marks (who led the creation of the Happiness Index) echoes Bernanke's address in a TED Talk: “Government shouldn't try to make us happy directly, that would be a bit weird. Government should be about making the conditions out of which well-being can emerge.”7 The notions of gently nudging healthier behavior or creating the right conditions for it are two pathways that also will (and already do) guide researchers in positive computing. We look at examples of these pathways in part II of the book.

Where there is much to be learned from the methods and strategies employed in economics and public policy, where keywords such as nudge, expenditure, and provision shape the landscape, a third approach to increasing psychological wellbeing across a population is to be found in education.

Education: Wellbeing as Learnable and Good for Learning

It's estimated that at any given point in time 10 to 20 percent of youth will suffer a mental health problem (O'Connell, Boat, & Warner, 2009). Why do we wait for serious problems to occur before taking action? The lack of preventative and promotional efforts for wellbeing have caused many psychologists and neuroscientists to turn to schooling as an obvious partner in giving people a better and more resilient start in life.

In a recent report of the US National Research Foundation (O'Connell, Boat, & Warner, 2009), numerous leading researchers from across the social sciences call on “the nation?its leaders, its mental health research and service provision agencies, its schools, its primary care medical systems, its community-based organizations, its child welfare and criminal justice systems?to make prevention of mental, emotional, and behavioral disorders and the promotion of mental health of young people a very high priority. By all realistic measures, no such priority exists today.”

Although the focus of the report is prevention, it also embarks on an analysis of mental health promotion through supportive families and schools?the very environments where young people develop the traits that will support their wellbeing and help them manage negative emotion and behavior throughout their lives. The report highlights evidence that the best strategies for preventing cognitive, emotional, and behavioral disorders are early intervention. It calls on the nation first to support those at risk, providing them with the best evidence-based interventions available, and then to promote the development of socioemotional skills in children and young adults more generally.

Just as modern economists and politicians are looking to “measure what matters,” educators are interested in “teaching what matters.” However, their discussions are understandably dominated by a focus on traditional academic subjects such as literacy, math, and science. Despite significant evidence that youth is the most critical window of opportunity for the development of attributes necessary to a happy stable life, only a small fraction of the efforts of educators, learning scientists, and education policymakers has been directed at developing psychological resources.

In fact, it is far more likely to find school-based peer-reviewed evaluations of wellbeing initiatives in journals such as Addiction than in education publications such as the Journal of Educational Psychology. The term wellbeing for example appears in only twenty articles in the latter, and half of them are from before 1950. The term mathematics, on the other hand, appears 795 times. Wellbeing was evidently not the focus of educational psychology in the second half of the twentieth century. Government funding, especially over the past decade, has encouraged a focus on what is collectively referred to as “STEM education,” consisting of science, technology, engineering, and math.

Without any doubt, society needs the scientists and engineers who will address the serious challenges of energy, climate change, and future technologies essential to our survival. And, of course, it's also critical that future generations gain the sophisticated understanding in these areas that will allow them to tackle twenty-first-century issues. But it seems that socioemotional skills?which are predictors of success in life?creative problem solving, and better decision making have been undervalued for far too long.

From the policy perspective, not only should adding wellbeing to the curriculum increase national wellbeing measures, it will also attend to other problems governments face, such as crime, poverty, drug abuse, and illness, all of which are frequently born from and exacerbated by ill-being. Intervening only once things are diagnosably bad requires expensive strategies such as long-term treatment and incarceration.

Despite the minimal attention given wellbeing in academic education research, new approaches geared at integrating socioemotional learning into the curriculum are emerging at the level of practice and within policy groups. For example, all children from kindergarten to sixth grade in New South Wales, Australia, follow a curriculum titled “Personal Development, Health, and Physical Education” that includes such modules as “Self and Relationships,” “Own Feelings and Empathy,” “Respect and Responsibility,” “Dealing with Conflict,” and “Diversity.” In the United States, the term social-emotional learning is used to describe similar curricula that aim to improve relationships and to develop emotional awareness and regulation, self-control, and healthy values. In the National Research Foundation report mentioned earlier, some of these programs were “shown to promote positive youth development while preventing mental health problems as well as substance abuse, violence, and other antisocial behaviour” (O'Connell, Boat, & Warner, 2009). Programs include:

• Inner Kids Program
• Inner Resilience Program
• Mindful Schools Program
• MindUP Program
• Still Quiet Place Program
• Stressed Teens Program
• Wellness Works in Schools Program

A RAND technical report titled Interventions to Improve Student Mental Health (Stein et al., 2012) provides an interesting review of the literature on such interventions written for policymakers in California. Prevention and early-intervention initiatives are grouped into those aiming to reduce stigma and discrimination, those on suicide prevention, and those on student mental health.

Others outside universities and governments have also recognized the importance of such research. The largest philanthropic organization in the world, the Bill and Melinda Gates Foundation, recently funded a project led by neuroscientist Richard Davidson aimed at developing mindfulness in children.8 We discuss this project and other such schools projects in part II.

Of course, the difficulty in attending more seriously to this area of development in schools is compounded by a modern reliance on test scores as measures of student and teacher competence. Yet, remarkably, research shows that, in addition to making happier, safer, more resilient kids, these wellbeing programs also increase their academic performance. A recent meta-analysis (Durlak, Weissberg, Dymnicki, Taylor, & Schellinger, 2011) of studies that included more than 200 schools (more than 270,000 students) showed that social and emotional learning programs lead to an impressive 11 percent gain in academic achievement.

This relationship is perhaps not surprising since positive emotions have been linked to better problem solving and enhanced creativity. Don Norman, among others, has highlighted the importance of designing for emotion (2005), much of which can be applied to the design of learning technologies. In Dorian's book Interface Design for Learning (2014), she looks at some of the emotions critical to learning and how design can support these emotions for better learning outcomes. For example, numerous studies have shown that positive emotions increase learning, creativity, problem-solving ability, and big-picture thinking. This work is related to Barbara Fredrickson's research on how positive emotions improve not only life experience, but also efficacy and resilience by increasing awareness, creativity, and exploratory behaviors (we look at the evolutionary importance of positive emotions in chapter 6).

As such, developing wellbeing in the learning environment also benefits from a better understanding of the dynamics of emotion involved in learning experiences as they occur. Educational psychology has tended to focus heavily on the cognitive aspects of learning rather than on the affective phenomena involved. Nevertheless, a number of researchers in the field have worked on certain areas of emotional experience, such as test anxiety, anger, frustration, and self-regulation (in both students and teachers) (Schutz & Pekrun, 2007). Among these emotions, test anxiety has received the most attention (particularly in the past few years in response to the increased reliance on standardized testing measures for evaluation in the United States).

The control-value theory of academic emotions (Pekrun, 2006) provides a way to analyze the antecedents and consequences of what students feel in learning situations. The theory assumes that appraisals of control (what is under a student's control and what is not) and values (how important the task is to a student) are essential to understanding the emotions felt in these activities (e.g., enjoyment, frustration, and boredom related to the learning activity as well as joy, hope, pride, anxiety, hopelessness, shame, and anger related to the outcome of the activity). There are clear overlaps with self-determination theory and its pillars of autonomy and competence. Education and wellbeing research undoubtedly have much to learn from each other, and we anticipate that they will begin to partner more consistently over the coming decade and will in all likelihood increasingly turn to technologists in their search for new tools to support investigation, learning, and wellbeing.

Learning from Learning Technologies

Both of us have spent much of our professional careers developing, evaluating, and researching technologies for learning. One interesting thing about these technologies is that they represent an area in which researchers have begun to combine emotions and technology in at least two ways. Despite the focus on STEM, there are at least two areas in which wellbeing measures have already been incorporated. First, at the convergence of affective computing and learning, we see experimental research in the use of emotionally aware, intelligent tutoring systems?systems that recognize and respond to boredom, confusion, and frustration and that promote engagement and resilience (see Calvo & D'Mello, 2011, 2012). We look at affective computing more closely in the next chapter.

Second, at the intersection of education, technology, and mental health, there exists a body of research on various Internet-based and technology-delivered interventions in schools. For example, one program on alcohol education (Champion, Newton, Barrett, & Teesson, 2012; Newton, Teesson, Vogl, & Andrews, 2010) randomly allocated 764 young teenagers from across ten schools to an Internet course or to a standard face-to-face health class. After 12 months, those who did the online course were found to be more knowledgeable, to consume less alcohol, and to have fewer binge-drinking episodes than those who did the face-to-face class. Although digital programs for personal development and wellbeing in schools have been surprisingly slow to take off (particularly in contrast with how much digital attention has been given to math and literacy), we expect to see growth in this area over the next decade as interest (and funding) in technology intersects with that of wellbeing.

With regard to learning that occurs outside of schools, researchers in the area of interaction design for children (IDC) have been pioneering in their attention to factors of wellbeing. Svetlana Yarosh and her colleagues (Yarosh, Radu, Hunter, & Rosenbaum, 2011) surveyed the papers published in each year of the IDC conference from 2002 to 2010 and sought to understand the type of behaviors and qualities the IDC community tried to promote in children. These behaviors and qualities were broadly grouped into social interaction and connectedness, learning, expression, and play, all of which impact on wellbeing. Furthermore, a number of apps for children are intended to promote wellbeing factors specifically. For example, Focus on the Go! and Sesame Street for Military Families are designed to help military children build resilience skills. Emotionary is among a number of apps designed to help kids identify and communicate emotions, and PositivePenguins supports them in challenging their thinking (in the style of cognitive behavioral therapy). For older kids, Middle School Confidential is a high-quality app-delivered comic that deals with confidence and bullying issues. Although such trailblazers represent just the beginning, a research field in positive computing will help support further work in this largely untapped area as the field matures.

Education, economics, and policy can help us to measure or influence wellbeing across a group or population, but these fields do less to explain why variations in wellbeing occur in the first place. To understand this higher-level question, we have to look at how various societal and cultural influences shape our wellbeing and our understandings of it.

Social Science: Wellbeing as a Changing Cultural Construct Shaped by Technology

A purely psychological analysis aims to understand wellbeing as an internal positive state we aim to attain. A sociocultural approach, in contrast, places more focus on how the definition of wellbeing changes over time and across cultures. Technology and Psychological Well-Being (Amichai-Hamburger, 2009) contains a series of essays exploring the relationships from a social sciences perspective. Work in sociology and media studies is critical to helping us understand how technology has already impacted our wellbeing and why.

George Rodman and Katherine Fry's (2009) historical account highlights wellbeing as a historical and cultural construct. The authors focus on wellbeing's relationship to social connections and discuss how the predominant communication technologies of each culture might have influenced its views on concepts and values such as individuality, society, privacy, and wellbeing. For example, the invention of typography in the 1450s introduced major social and economic changes, and, according to Rodman and Fry's reading of Marshall McLuhan, some of the changes were dehumanizing as they reduced the need for face-to-face interactions, but other changes were liberating as they democratized information and raised the sense of self. Certainly we see similar parallels arising with the spread of modern information communication technologies, some of which are elegantly explored in Richard H. R. Harper's book Texture: Human Expression in the Age of Communications Overload (2012).

Social media in particular have made whole new social behaviors possible with both positive and negative consequences to wellbeing. Social media researcher danah boyd, of Harvard and Microsoft Research, points to the life-saving potential provided in parallel with challenges posed by social media with regard to the wellbeing of youth (see her sidebar in this chapter for more detail).

Although economics has helped to uncover the links (or lack thereof) between wealth, technology, and wellbeing, knowing that more wealth or more advanced personal technology hasn't made society much happier doesn't tell us why it hasn't. Perhaps wealth would be a more effective indicator if some other variable were changed. Perhaps technology would have greater positive impact if it were designed differently. The weakness in our current understanding is certainly influenced by the difficulty that exists in isolating variables within such a complex system.

For example, one study that surveyed a cross-section of 22 European countries (Frey, Benesch, & Stutzer, 2007) shows a negative correlation between TV ownership/viewership and wellbeing (more TV time was linked to lower life satisfaction). Another study (Dolan, Metcalfe, Powdthavee, Beale, & Pritchard, 2008) suggests the opposite?that having TV and computers improved self-reported wellbeing measures. A third study (Kavetsos & Koutroumpis, 2011) used a cross-sectional database of 29 European countries and found that those who owned a phone, CD player, and computer and who had an Internet connection were more likely to report higher subjective wellbeing. In this third study, correlation with TV ownership was statistically insignificant.

There is obviously much we need to learn about which technologies can support wellbeing, when, in what circumstances, in what combinations, and why. Ethnographic and anthropological research, historical and sociological inquiry, along with other methods matured by the social sciences will be essential to moving us forward toward this understanding.

Moving away from the social sciences and toward examples of application, we come to business?an area for which investment in wellbeing poses a clear value proposition.

Business and Organizational Psychology?Wellbeing in the Workplace

In the past 20 years, growing research evidence has shown that happier employees can be more productive, innovative, and empathic with their clients (Goleman, 1998; Linley, Harrington, & Garcea, 2010). This is part of the reason why an increasing number of corporations and nongovernment organizations have begun turning to wellbeing-related training and initiatives in the form of emotional intelligence training, mindfulness and meditation events, as well as changes intended to improve work?life balance, social connectedness, and autonomy.

From the perspective of positive computing, companies are likely to provide many opportunities because they are significant users of online and technology-supported training. In addition, companies now rely on enterprise-level social media and communication platforms, many of which will likely be found to benefit from and feed into wellbeing-informed design.

Human-resource systems are rather sophisticated beasts, recording and analyzing employee performance data and creating strategic maps to guide employee skill sets (knowledge capital) to adapt to changing needs. Yet, there is much room for improvement in how they manage mental capital, or an organization's wellbeing skills.

In countries such as the United Kingdom, employers are liable for the consequences of work-related stress. One of the ways of addressing this liability (and helping employees) is to offer counseling services. This approach has persuaded employers to provide training and counseling programs, often delivered by private companies, which arguably has bootstrapped an industry in wellbeing. The University of Sydney, for example, has a Health and Wellbeing Program that includes professional counseling, self-help books and materials, peer-support programs, and a number of health initiatives (e.g., Weight Watchers and a smoke-free environment).

Just as new training requirements arising from health and safety compliance fed the e-learning industry, the same kind of energy toward improved employee wellbeing can now drive an industry of positive computing?for example, in the form of wellbeing-informed redesigns of employee systems. Indeed, there is evidence this is already happening. For example, Crane software by Kanjoya provides managers with information about the mood of their organization and of the groups of people within it. We suspect that we will soon see more examples in this genre?for instance, customer-service software designed to increase empathy between customer and rep or more sophisticated ways of measuring the wellbeing effects of management changes or human-resource programs. As with education, this area presents massive potential for research and practice in positive computing to make significant contributions.

One final way to approach the role of technology in our experience of wellbeing is by viewing technology as part of our environment. Fortunately, the question of how environments impact wellbeing is not new to architects and environmental designers, so as a final multidisciplinary foray we turn to them.

Design and Architecture: Places and Things That Improve Wellbeing

In The Architecture of Happiness (2006), Alain de Botton writes about ways in which art and architecture have been used over the ages to influence what we feel, think, and do. A cathedral, for example, in its very proportions, its magnificent statues, and its filtered light invites contemplation and awe in a way that a fast-food restaurant doesn't. In contrast, the restaurant architects favor the emotional effects of modernity, economy, and speed, with visible kitchen staff, pop music, and bright colors that pique the appetite.

Environmental psychology provides a methodological approach to studying the affordances and effects of place (Bell, Greene, Fisher, & Baum, 2005). The field connects research on the physical environment with research on health and wellbeing, investigating ways in which certain designs promote, hinder, or completely rule out certain behaviors. Topics within their sphere range from how the availability of informal spaces can increase a sense of community and reduce criminal behavior to how high ceilings lead to more open-ended thinking (known as the “cathedral effect”) and how an office window might increase job satisfaction.

Although environmental psychology focuses on physical rather than digital environments, it suggests what some of the methodological challenges facing positive-computing work will be. Rather than studying perception as a separate phenomenon of the stimuli, environmental psychologists study both as a single entity (similarly, the stimulus?response situation of a website and a user does not depend on just one or the other of them). These ideas can be adapted to digital environments in that interaction phenomena depend on website design, but also on the experiences of the person interacting (i.e., their previous experience, interests, level of education, etc.). In environmental psychology, the environment?perception unit is more than the sum of its parts. This focus means that environmental psychologists, like other psychologists, tend to work in the field rather than in the laboratory. The challenges of field study have led environmental psychologists to use a rich mixture of methods (Bell et al., 2005), some of which are discussed in chapter 6.

Recent work by researchers Pieter Desmet and Anna Pohlmeyer in what they term “positive design” shows how the aim to support psychological wellbeing is playing out in parallel with positive computing within the field of industrial design. In a special issue of the International Journal of Design, Desmet, Pohlmeyer, and Jodi Forlizzi (2013) bring together work on design for subjective wellbeing from the perspectives of experience design, business, ethics, and codesign.

. . .

In chapters 2 and 3, we have looked at some of the seminal wellbeing-related work in a diversity of disciplines. The unique perspectives and opportunities that arise from multidisciplinary views will act as rich resources of information as well as fertile areas of future application as work in positive computing moves forward. As always, drawing from and working across multiple disciplines will pose challenges to communication as well as to funding mechanisms, but the rewards are great, and they come in the form of unique solutions, broader perspectives, and greater benefits to users.

In the next chapter, we come back to base and review some of the ways in which researchers in engineering and computer science have already begun to consider wellbeing issues as part of their work in technology.

Expert Perspectives -- Multidisciplinary Views

Notes

1. From the website beyond-gdp.eu.
2. See happyplanetindex.org.
3. See well-beingindex.com.
4. From un.org/en/events/happinessday/.
5. From the Behavior Insights Team website at gov.uk/government/organisations/behavioral-insights-team.
6. See Bernanke's address at federalreserve.gov/newsevents/speech/bernanke 20100508a.htm.
7. See “Nic Marks: The Happy Planet Index,” at ted.com/talks/nic_marks_the_happy _planet_index.htm.
8. For this project, see news.wisc.edu/releases/17368.

References

• Amichai-Hamburger, Y. (Ed.). (2009). Technology and psychological well-being. Cambridge, UK: Cambridge University Press.
• “Ban: New economic paradigm needed, including social and environmental progress.” (2012). UN News Centre. April 2. Retrieved March 2014, from http://www.un.org/apps/news/story.asp-NewsID=41685#.UzOETCTvWkB.
• Bell, P. A., Greene, T., Fisher, J. D., & Baum, A. (Eds.). (2005). Environmental psychology. Vol. 4. 5th ed. Fort Worth, TX: Routledge.
• Bruni, L., & Porta, P. L. (Eds.). (2007). Handbook on the economics of happiness. Malden, MA: Edward Elgar.
• Calvo, R. A., & D'Mello, S. (Eds.) (2011) New perspectives on affect and learning technologies. New York: Springer.
• Calvo, R. A., & D'Mello, S. (2012). Frontiers of affect-aware learning technologies. Intelligent Systems, IEEE, 27(6), 86-89.
• Champion, K. E., Newton, N. C., Barrett, E. L., & Teesson, M. (2012). A systematic review of school-based alcohol and other drug prevention programs facilitated by computers or the Internet. Drug and Alcohol Review, 2013(32), 115-123.
• De Botton, A. (2006). The architecture of happiness. New York: Pantheon.
• Denham, J., Beddington, J., & Cooper, C. (2008). Mental capital and well-being project. London: UK Office for Science.
• Desmet, P. M. A., Pohlmeyer, A. E., & Forlizzi, J. (2013). Special issue editorial: Design for subjective well-being. International Journal of Design, 7(3). Retrieved from http://www.ijdesign.org/ojs/index.php/IJDesign/article/view/1676/594.
• Diener, E., & Seligman, M. E. P. (2004). Beyond money. Psychological Science in the Public Interest, 5(1), 1-31.
• Dolan, P., Metcalfe, R., Powdthavee, N., Beale, A., & Pritchard, D. (2008). Innovation and well-being. Innovation index working paper. London: Nesta.
• Durlak, J. A., Weissberg, R. P., Dymnicki, A. B., Taylor, R. D., & Schellinger, K. B. (2011). The impact of enhancing students' social and emotional learning: A meta-analysis of school-based universal interventions. Child Development, 82(1), 405-432.
• Easterlin, R. A. (1974). Does rapid economic growth improve the human lot- Some empirical evidence. In P. A. David & M. W. Reder (Eds.), Nations and households in economic growth: Essays in honor of Moses Abramovitz (vol. 8, pp. 88-125). New York: Academic Press.
• Frey, B. S., Benesch, C., & Stutzer, A. (2007). Does watching TV make us happy- Journal of Economic Psychology, 28(3), 283-313.
• Golder, S. A., & Macy, M. W. (2011). Diurnal and seasonal mood vary with work, sleep, and day length across diverse cultures. Science, 333(6051), 1878-1881.
• Goleman, D. (1998). Working with emotional intelligence. New York: Bantam.
• Harper, R. H. R. (2012). Texture: Human expression in the age of communications overload (p. 320). Cambridge, MA: MIT Press.
• Helliwell, J., Layard, R., & Sachs, J. (2012). World happiness report. New York: Earth Institute.
• Kahneman, D., Diener, E., & Schwarz, N. (Eds.). (1999). Well-being: The foundations of hedonic psychology. New York: Russell Sage Foundation.
• Kavetsos, G., & Koutroumpis, P. (2011). Technological affluence and subjective well-being. Journal of Economic Psychology, 32(5), 742-753.
• Linley, A., Harrington, S., & Garcea, N. (Eds.). (2010). Oxford handbook of positive psychology and work. New York: Oxford University Press.
• Mitchell, L., Harris, K. D., Frank, M. R., Dodds, P. S., & Danforth, C. M. (2013). The geography of happiness: Connecting Twitter sentiment and expression, demographics, and objective characteristics of place. PLoS ONE, 8(5), 15.
• Newton, N. C., Teesson, M., Vogl, L. E., & Andrews, G. (2010). Internet-based prevention for alcohol and cannabis use: Final results of the Climate Schools course. Addiction, 105(4), 749-759.
• Norman, D. A. (2005). Emotional design: Why we love (or hate) everyday things. New York: Basic Books.
• O'Connell, M. E., Boat, T., & Warner, K. (2009). Preventing mental, emotional, and behavioral disorders among young people: Progress and possibilities. Washington, DC: National Academies Press.
• Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18, 315-341.
• Peters, D. (2014). Interface design for learning: Design strategies for learning experiences. San Francisco: New Riders.
• Rodman, G., & Fry, K. G. (2009). Communication technology and psychological well-being: Yin, yang, and the golden mean of media effects. In Y. Amichai-Hamburger (Ed.), Technology and psychological well-being (pp. 9-33). Cambridge, UK: Cambridge University Press.
• Ryan, R. M., & Deci, E. L. (2001). On happiness and human potentials: A review of research on hedonic and eudaimonic well-being. Annual Review of Psychology, 52, 141-166.
• Schutz, P. A., & Pekrun, R. (2007). Emotion in education. Salt Lake City: Academic Press.
• Stein, B. D., Sontag-Padilla, L., Chan Osilla, K., Woodbridge, M. W., Kase, C. A., Jaycox, L. H., … Golan, S. (2012). Interventions to improve student mental health: A literature review to guide evaluation of California's mental health prevention and early intervention initiative. Santa Monica, CA: RAND.
• Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. New Haven, CT: Yale University Press.
• Yarosh, S., Radu, I., Hunter, S., & Rosenbaum, E. (2011). Examining values: An analysis of nine years of IDC research. In 10th International Conference on Interaction Design and Children. IDC 2011 (pp. 136-144). Ann Arbor: University of Michigan.

Computers should be able to do X. Current techniques only do X-I. We contribute a technique that does I.

It's not exactly an inspiring narrative, but this humble argument has nevertheless fueled incremental technological progress over the past century and ushered us through three generations of computing and into the Internet of Things we find ourselves moving today. As devices get embedded into the fabric of our lives and become inextricable parts of the experiences that shape us, their inevitable impact on our wellbeing grows ever greater. Yet engineering hangs onto technology-focused approaches. Sometimes humans are included in the equation, although mainly as comparison points:

Computers should be able to do X. Humans do X very well. Current techniques do only X-I. We contribute a technique that does I by emulating the way a human does it.

I (Rafael), for one, have used both of these arguments in my work (just replace X with “recognize emotions” or “help students” and I with “use language” or “give feedback”). Yet any system created for human use will have some effect on human psychological wellbeing, however profound or negligible. In order to be able to take this effect into account in our design, we can start by looking at how current technologies already impact wellbeing and at how current research areas can or already do contribute to our understanding in this area.

Ubiquitous Computing: Opportunities and Challenges for Wellbeing

Two decades ago in a seminal paper, Mark Weiser (1991) coined the term ubiquitous computing, now affectionately abbreviated to “ubicomp.” He simultaneously predicted many of the technology developments that would come to characterize modern digital experience. He was dissatisfied with the contemporary personal-computing model and argued that computing devices could fulfill their potential most effectively through seamless integration into the world: “My colleagues and I at the Xerox Palo Alto Research Center think that the idea of a 'Personal' Computer itself is misplaced and that the vision of laptop machines, dynabooks and 'knowledge navigators' is only a transitional step towards achieving the real potential of information technology.”

Weiser's article both reflected and shaped an important era of technology work. The ubicomp vision has nurtured myriad academic projects, journals, and conferences. The technical challenges of building these systems are formidable and have been reviewed with regularity (Abowd & Mynatt, 2000; Estrin, Govindan, Heidemann, & Kumar, 1999; Yick, Mukherjee, & Ghosal, 2008). The future, thanks to ubicomp, promises to bring us constant access to information and computational capabilities, together with new ways of interacting with them. The challenge now is figuring out how best to recruit these new capabilities to best serve human needs.

Some would undoubtedly argue that because many of these technologies are designed to support safety, productivity, and enjoyment in ways that are more sophisticated, more readily available, and more personalized than ever before, they will naturally lead to happier lives. Perhaps?but as we have argued previously, relying on assumptions or using proxies such as productivity or personalization for wellbeing is a weak approach to a future of human-centered engineering. We now have the tools and theory it takes to be more precise in our evaluations and to inform our design more consciously; in other words, we can do better than just relying on assumptions in ensuring that technology fosters flourishing.

Two decades have gone by since the ubicomp vision entered the world, and we now have what it takes to move genuine human-centeredness to the next level. One area of development has already begun to explore the potential for data collection, evaluation, and reflection to support personal growth, and it's known as “personal informatics.”

Personal Informatics -- New Tools for an Old Quest

Sometime around 400 BCE, a passing Greek paused at the Temple of Apollo long enough to inscribe these timeless words into its stone: “Know Thyself.” This aphorism was thereafter interpreted in at least three different ways by the ancient Greeks to follow. Socrates invokes the inscription to explain why the pursuit of self-knowledge is more important than any other intellectual pursuit: “I am not yet able, as the Delphic inscription has it, to know myself; so it seems to me ridiculous, when I do not yet know that, to investigate irrelevant things.”((Socrates says this in Plato's Phaedrus, 229e.)] In a second interpretation, the maxim is better translated as “Know thy place” or “Who do you think you are?” and is used as a means of restoring modesty to those who need it. Finally, it was used as a reminder that we should aim to know truth directly rather than blindly relying on the status quo. “Pay no attention to the opinion of the multitude and revalue not the truth but the accepted custom.”[(Found in the entry “gamma, 334” of the Suda translations of the Stoa Consortium and explained in Wikipedia. The Suda is a massive tenth-century Byzantine Greek historical encyclopedia of the ancient Mediterranean world. See /stoa.org/sol.)] There is certainly something to be learned from each of these interpretations, but it is the first that seems to have most powerfully sparked the imaginations of technologists over the past few years.

Life logging, the now familiar digital recording of life events, actually began in the 1980s. Steve Mann at the University of Toronto strapped laboratory equipment to his body and proceeded to diligently record physiological and video data of all his daily activities. In 1994, he went public and started webcasting video of his everyday life, and, like a good convenience store, he remained open seven days a week, 24 hours a day, inviting the world to drop in. Despite Mann's pioneering work in wearable computing, life logging didn't see mainstream uptake until the turn of the century, when the necessary equipment became more affordable and more acceptable to be seen in.

The proliferation of mobile digital devices have seen life-logging tools break out of research labs and move stylishly into the jogging hands of the masses. The use of blogs, microblogs, status updates, cameras, GPS, and other low-cost tools for recording and sharing personal events has become increasingly commonplace.[(For one of the earliest examples of life logging, see Buster Benson's Why I Track video presentation at vimeo.com/54881153.)] In 2007, Gary Wolf and Kevin Kelly of Wired magazine recognized this growing interest in tools that support self-knowledge through “self-tracking” and helped consolidate that interest into a thriving movement that they called the “quantified self” (recruiting Socrates's interpretation of the Delphic inscription as a kind of motto).

Several years on, hundreds of dedicated consumer products allow you to record your movements, sleep patterns, eating habits, and other behaviors. Some quantified-self applications are built as extensions to existing technologies leveraging built-in features of standard devices such as accelerometers, GPS, and gyroscopes, whereas others are separate custom tools. Large sports brands such as Nike and Adidas produce sensors and software to monitor and collect physical activity data. The Fitbit, one of the first sensors to be widely popular, uses a low-cost accelerometer to record your movement walking, running, and sleeping.

In addition, standardized formats are allowing the data produced by these devices to be effectively merged. For example, heart rate and blood pressure data from sensor watches can be synchronized with data from gym machines and wireless scales and then uploaded to one of the many websites available (e.g., Movescount) for people to share their athletic lives, struggles, and success stories.

We have even brought man's best friend into the mix. Modern dog-collar technology allows owners to track Fido's activity level, geographic location, and even happiness throughout the day. If he's at home and you're at work, you can check his activity monitor remotely (opening up whole new opportunities for procrastination). Who knows, maybe in the future we'll be able to sync pet emotional data with our own and finally learn how to be as consistently jolly as dogs are.

But how do all these data get turned into useful information? Log data generally get transferred to a computer, where they can be visualized, analyzed, and shared with others. Companies typically store data for free so that they can mine, process, and transform the data into information that is useful both to users and to company profits.

“Self-trackers” describe experiences in which tracking consumption, medication, and activity data allows them to unearth the causes of health problems. Ian Li, Anind Dey, and Jodi Forlizzi (2010) surveyed 68 self-trackers (and interviewed 11 of those) in order to improve our understanding of what motivates and deters tracking. Most of the tracking activities reviewed had to do with personal finances, energy use, exercise, or work, and their primary motivations to engage included general curiosity and social influence. Findings led the authors to propose five stages in the way people engage with personal informatics technology:

• Preparation includes the point at which the decision to track is made along with any associated activities (e.g., deciding on what tool to use).
• Collection is when the user records data points that can occur on various time scales, such as hourly or yearly (e.g., food at each mealtime or books you have read over months). This stage is characterized by the technical challenges associated with gathering large sums of data from the user with minimal effort and intrusion.
• Integration includes the processing strategies that allow a person or the system to build a meaningful synthesis or visualization from the various data sources.
• Reflection occurs when the user reflects on his or her behavior based on the data, and this reflection can happen in real time as in “How many steps have I just walked?” or after the fact as in “How many hours a day have I been walking this month?”
• Action is the phase most closely related to the challenges of positive computing. It is here where Li, Dey, and Forlizzi ask, “What are the effects of personal informatics on daily life?” and list aspects such as “trust in the system, motivation, better decision making, loss of control, etc.,” some of which are not directly related to wellbeing.

In part II, we look more deeply at the reflective thinking that personal-informatics technologies can support as well as at how reflection can, in the right circumstances, lead to increased wellbeing.

The quantified-self movement, (a.k.a. “personal Informatics,” “self- surveillance,” “self-tracking,” or “personal analytics”) has been wildly successful on many fronts. Thousands participate in the online communities, meeting as part of groups around the world, and the movement has received extensive mainstream press coverage. It is driving a significant amount of innovation, academic research, commercial enterprise, and ideally, positive personal change.

But the full story is only beginning to take shape. The workshop on personal informatics held at the Association of Computing Machinery's Computer?Human Interaction conference has sought to develop the dialogue between those in “design, ubiquitous computing, persuasive technology and information visualization” (Li, Dey, Forlizzi, Hook, & Medynskiy, 2011) who are involved in personal informatics. Psychologists are conspicuously missing from the list, despite the fact that psychological impact and issues such as self-awareness, motivation, self-esteem, balance, frustration, pride, self-criticism, ironic processes, and wellbeing are at the core of these digital experiences. Research such as the study by Li, Dey, and Forlizzi has helped illuminate many of the technical obstacles people face at each stage of self-tracking, but research on psychological barriers and variations to experience will be critical to future work. Yvonne Rogers at University College London discusses this point further (see her sidebar in this chapter).

Deborah Lupton (2012), a sociologist at the University of Sydney, has explored how digital technologies affect the people who use them, including their experiences of embodiment, selfhood, and social relationships. Lupton describes self-tracking using “m-health” devices as a conceptual shift in health promotion. On the one hand, digital self-tracking brings a great deal of technology into an area that has been largely low tech and focused on prevention campaigns. These technologies (i.e., social networks, mobile phones, tracking devices) now allow messages to be better personalized.

On the other hand, Lupton cautions that the design of these technologies requires multiple perspectives?technical professionals will focus on the technical problems of a device, and health professionals will look at how these tools can be used efficiently for the treatment and management of medical conditions. However, personal values and moral and ethical concerns must also be addressed. Lupton's (2012) sociological work, in her own words, deals with how these technologies may operate to construct various forms of subjectivities and embodiments, including identifying the kinds of assumptions that are made about the target of these technologies and what the moral and ethical ramifications of using them may be. Moral implications include the kinds of meanings and the representation of the ideal subject that are related to the use of these technologies in the interests of promoting health. Ethical issues include questioning the extent to which health promotion practice should intrude into their targeted populations' private lives and what kinds of messages and practices they employ when using digital surveillance devices.

Clearly, if we want to see the field mature, we need to share it with those in the social sciences who have academic knowledge in the kinds of human experience we hope to support. For some initial examples of collaboration models for working in multidisciplinary ways as technologists, we might look to affective computing, a field that has studied emotions as well as how to detect, influence, and model them in the context of HCI.

Affective Computing -- Technology and Emotions

It wasn't until the early 1990s that computer scientists begun to take emotions more seriously when a small number of researchers started developing computer systems that could detect human emotions. Rosalind Picard at the MIT Media Lab crystallized an emerging interest in affect in her seminal book Affective Computing (1997). She described three types of affective computing applications:

1. Affect detection, in which the computer uses video, microphones, physiological sensors, posture sensors, and other sensing devices to recognize emotions (via facial expressions, voice modulation, posture, etc.). These data are used to train a classifier that maps patterns into emotional dimensions or labels?for example, the so-called six basic emotions (Ekman, 1992): anger, surprise, happiness, disgust, sadness, and fear.

2. Affect expression, in which software agents (e.g., avatars in virtual-reality environments) are able to express emotions. By doing so, users can establish closer relationships and receive more natural feedback.

3. Emotional computers, in which a new kind of computer capable of feeling (mechanically embodying) and expressing emotions (albeit machine versions of them) would be developed.

Most affect-detection systems (Calvo & D'Mello, 2010) extract key features from recorded data, then build computational models that map those features to actual emotion labels (or to coordinates if using a dimensional model). In order to generate those models, a classifier is built using machine-learning techniques. The classifier is trained on data collected through a number of possible techniques. Techniques that produce more “ecologically valid” data (i.e., closer to real life) are harder to obtain in laboratory conditions. The most commonly used techniques either interrupt participants in whatever they are doing to ask them how they feel (i.e., to label the training data, often using a standard form or diagram) or ask them once they have finished.

The area has matured into a thriving field with a dedicated journal, a regular conference, and threads within leading HCI journals and conferences.[(The journal is IEEE Transactions on Affective Computing, and the conference is the International Conference on Affective Computing and Intelligent Interaction.)] Several reviews (Calvo & D'Mello, 2010) and the Oxford Handbook on Affective Computing (Calvo, D'Mello, Gratch, & Kappas, 2014) are further indications of the field's advancement. What is possibly more important for positive computing is that the field's explicit focus on emotions has facilitated strong relationships with other research communities in psychology, psychiatry, education, and neuroscience.

There are a number of examples of affective-computing projects that venture beyond improving HCI. In the next section, we describe three cases in which affective-computing technologies (specifically those for detection) have been used to support psychological wellbeing, the first in the area of attentive technologies, the second in the context of learning, and the third in mental health.

Affect and Attentive Interfaces -- When Systems Are Considerate of Your Mental State

Concerned by the capacity for new technologies to produce cognitive overload, a group of researchers turned to the development of what they call “attentive user interfaces” (Vertegaal, 2003). By tracking the user's gaze, an interface can adapt, highlighting urgent issues while backgrounding those of less importance. The significance of such systems is most obvious in technology-rich environments where managing cognitive load is crucial, such as emergency and air-traffic-control rooms. These systems can also be used to study different psychological phenomena?for example, attention, engagement, and mind-wandering?that, as we will see in chapter 8, are related to wellbeing.

Affective Computing for Reflection

One particularly fruitful point of intersection between affect and reflection is in the area of writing. According to research, it's extremely difficult to be writing one thing and thinking another (though we certainly try). This makes writing a uniquely interesting proposition for studying what someone is thinking at a given moment. It's also much easier to analyze writing in the twenty-first century than it ever has been because most writing and the analysis of it are now done on digital devices connected to the Internet. These same devices enable writers to interact with content and other people in completely new ways as part of the writing process. At the convergence of these features, the door is wide open to whole new data-collection channels and new opportunities for understanding ourselves, how we write, and how we think.

It is within this context that my students and I (Rafael) have been working on what we call “Data-Rich Writing Studios” (Calvo, 2014). These systems allow for a combination of work on software architectures, multimodal sensing and fusion, and machine learning for data processing to study writing phenomena in a holistic way, taking into account the writer's physical and social surroundings as well as her cognitive processes and affective states. This information can then be returned to the user in the form of various types of feedback for reflection and learning.

Take, for example, a tool called Glosser, which is a web-based framework for providing automated feedback on writing (Calvo & Ellis, 2010; Villalon, Kearney, Calvo, & Reimann, 2008). Glosser analyzes cognitive aspects of writing, including the development of argument, structure, and topic coverage in order to produce a wide range of feedback. The feedback provided can be on surface or content features, on the writing product (the final document), or on the process itself and is presented as text and visualizations. A quick processing of your essay might reveal at a glance that you haven't covered all topics adequately, that there is a lack of flow from one paragraph to the next, or that the three main arguments you have made lead nicely to the conclusion.

Although this area of research has been focused on education rather than on wellbeing, a number of instructive similarities can be drawn between the two. For example, subjective areas (such as writing and psychological wellbeing) don't involve simple universal right or wrong answers. Therefore, a key design principle has been to provide reflective rather than directive feedback (“consider this” rather than “do this”). Furthermore, feedback designed to trigger reflection that is based on written text lends itself to use in cybertherapy (an area that already relies heavily on reflective writing in journals). Add to this an ability to detect emotional states from text mining and facial expressions, and whole new opportunities for mental health promotion emerge.

Affect and Technology for Mental Health

The use of writing in therapy is based on research that suggests that writing about thoughts and feelings associated with an experience is beneficial to some individuals. J. W. Pennebaker (1997, 2004) at the University of Texas, Austin, has performed many of these studies. The precise size of these activities' effect is still debated, but it is generally agreed to be positive for physical and mental health.

One of the difficulties is that there are various ways of structuring these writing activities that are helpful to different people. For example, in one study, Laura King and Kathi Miner (2000) found that writing about the positive benefits of an upsetting past experience was beneficial to health. The suggestion is that such structure may enhance self-regulation skills and foster a sense of self-efficacy. The evidence provided by these studies can inform activities and tools for the psychological development of people within clinical scenarios but can also be extended to the design of tools for everyday life.

Another way in which affective computing has been used in psychotherapy is the enhancement of virtual-reality environments. Timothy Bickmore (see his sidebar in chapter 10) and Giuseppe Riva are two researchers spearheading work in this area. Riva (2005) has argued that using virtual-reality exposure therapy for the treatment of anxiety disorders (e.g., fear of heights and speaking in public) is safer, less embarrassing, and less costly than reproducing real-world situations. In this technique, a client is confronted with the stimuli in a way that allows anxiety to attenuate over time. In real life, every time a client avoids situations that cause the anxiety, the phobia is reinforced. In treatment, each successive exposure to the stimuli reduces anxiety through habituation.

Researchers are also exploring how the ever-present mobile phone might also be used for interventions of various kinds for the promotion of wellbeing. For example, one application sends daily motivational text messages based on a number of different psychoeducation campaigns (e.g., stress, random acts of kindness, etc.); another provides mindfulness exercises; and yet another aims to increase sociopolitical participation. Riva and his colleagues have used mobile phones to reduce student stress during exam periods (Preziosa, Grassi, Gaggioli, & Riva, 2009) and commuter stress (Grassi, Gaggioli, & Riva, 2009). More studies that use mobile devices in various ways to reduce stress and improve wellness and wellbeing are regularly published in journals such as Cyberpsychology, Behavior, and Social Networking, the Journal of Medical Internet Research, and The Lancet. Some of these studies involve campaigns to change behavior and offer examples from that increasingly influential area of research and practice known as behavior change technology.

Behavior Change Technology

In the last decade, swelling interest in behavioral economics has encouraged growth in the design of technology that persuades, influences, or helps people to change their behavior. It is self-evident that work in the area of behavior change is highly relevant to positive computing since some improvements to wellbeing will involve supporting this change. Behavior change technology (BCT) (also referred to as “persuasive technology,” “captology,” and “behavior design”) in no way prescribes wellbeing intentions and is applied broadly from advertising to business and politics. However, a large percentage of research in BCT aims to improve wellbeing (often physical aspects) and sustainability.

Researchers focusing on using technology for wellbeing-related behavior change draw on various behavior theories and models including nudge theory, the Transtheoretical Model, the Theory of Planned Behavior, and SDT among others (see Hekler, Klasnja, Froehlich, & Buman, [2013] for a review of behavior theories and models in HCI).

Some work in this area, especially within the category of persuasive technology, can slide into a rhetoric of designer-control and is happily applied by business to increase profitable behavior. Thus, implications for unethical use follow closely behind any discussion of these methods. As such, researchers are working to outline ethical guidelines (Atkinson, 2006, Spahn, 2011, Davis 2010). For positive computing, part of addressing misuse will emerge from the field's definitive aim to support psychological wellbeing, and the imperative to provide evidence (via established multidimensional measures) for that claim in practice.

In addition to ethical concerns and issues of user autonomy, we will need to join those researchers in BCT who are challenging the quick-fix thinking that neglects complex, difficult, and long-term change. Martin A. Siegel and Jordan Beck (2014) discuss behavior change technology for quality-of-life improvement advocating for greater acknowledgement that much change is slow and occurs within systems that are complex. They provide the groundwork for an ongoing theory and practice of interaction design for slow changes that they define as “attitudinal and behavioral changes that are difficult to initiate and sustain,” bringing to light ethical dilemmas, impacts of timescale, and the value of systems thinking inherent to slow change problems.

Values-Sensitive Design: Acknowledging the Role of Values

Technology may be able to influence people, but should it? If it's going to be impacting people's lives, shouldn't they be involved in deciding how it will do so? Whose values are embedded into every design? Batya Friedman and Peter Kahn (1992) brought long-awaited attention to an elephant that had found a home in the computer science room: values. What is responsible computing, and how can it be promoted among technology designers?

One argument for bringing attention to values is that although “humans are capable of being moral agents and computational systems are not” (Friedman & Kahn, 1992), computers can distort moral agency in two ways: first, when a human's sense of moral agency is undermined by the computer system (as when a human's role becomes secondary and causes him to loose connection to the purpose or meaning of his actions); second, when the computer system projects “intentions, desires and volitions,” so that the human makes the computer responsible for his actions.

For more than two decades, the VSD community has asked what computers ought to do (rather than what they can do) as part of HCI (Friedman, 1996, 1997; Sellen, Rogers, Harper, & Rodden, 2009; Yarosh, Radu, Hunter, & Rosenbaum, 2011). VSD reminds those developing technology that it is impossible to do so without making decisions based on implicit and explicit values and that the values of both designers and users should be accounted for.

VSD literature has been shaped largely by the moral domain of social knowledge (Friedman, 1997). This moral domain considers views and values on justice, fairness, and human welfare. Value-sensitive designers address conflicts between the individual and society, and they investigate values such as privacy, trust, ownership, and health.

Friedman and colleagues (Friedman, Kahn, & Borning, 2006) suggest a series of guidelines for designing computer systems:

• Start with what is most important to you: value or technology or context.
• Identify those who will use the system (direct stakeholders) and others who will be affected by it (indirect stakeholders).
• Identify how your system will benefit or harm each stakeholder.
• Map each benefit and harm onto a list of values.
• Learn about your key values. (VSD recommends reading the philosophical-ontological literature that may provide a definition and ways of assessing it empirically.)
• Identify conflicting values?for example, trust versus security, environmental sustainability versus economic development, privacy versus security, and hierarchical control versus democratization.
• Incorporate values into the organizational structure so that your company can support such initiatives.

These authors also list a set of human values that can be taken into account in system design, including ownership and property, privacy, trust, usability, human welfare, and autonomy. Friedman (1996) has also paid significant attention to autonomy, a topic central to some models of wellbeing that we come back to in part II.

As one might expect, many of the values held by communities are strongly related to wellbeing; however, a link to psychological wellbeing is not required for values to be held. On the flip side, some aspects of psychological wellbeing are not explicitly included in societal or individual values (both mindfulness and resilience, for example, are causally related to psychological wellbeing but are not necessarily conscious core values in most cultures or within common user groups such as teenagers and company employees). The starting point for VSD researchers is moral philosophy and ethics (Friedman et al., 2006), and the sociocultural approach used in VSD can effectively function independently of psychological drivers. For example, Roberto Verganti's (2008) design-driven innovation is based on the capacity to “understand, anticipate and influence emergence of new product meanings.” These sociocultural perspectives as well as others, including user-centered design, will continue to provide valuable pieces of the wellbeing puzzle. Clearly there is considerable promise in a future industry that employs both VSD and positive-computing approaches from their complimentary perspectives toward human-centeredness.

Innovations and inspiration for work in wellness and wellbeing emerge daily from across the many varied technology fields. This chapter was by necessity more of a sample plate than a comprehensive handbook on all that might inform positive-computing work, but to keep informed, you can drop by the website positivecomputing.org to read about or share new examples as they emerge. Now, with a solid grasp of the foundational literature under our belts, in the next chapter we get to the nitty-gritty and look at how all the psychology research on wellbeing might be operationalized into a research and practice framework for future work in positive computing.

Expert Perspective -- Technology Research and Wellbeing

~~REFNOTES~~

References

Abowd, G. D., & Mynatt, E. D. (2000). Charting past, present, and future research in ubiquitous computing. ACM Transactions on Computer-Human Interaction, 7(1), 29-58.

• Atkinson, B. M. C. (2006). Captology: A critical review. In IJsselsteijn, W., de Kort, Y., Midden, C., Eggen, B., & van den Hoven, E. (Eds.) Persuasive technology. Proceedings of the 1st international conference on persuasive technology, pp 171-182. Berlin Heidelberg: Springer.
• Calvo, R. A. (2014). Affect-aware reflective writing studios. In R. A. Calvo, S. K. D'Mello, J. Gratch, & A. Kappas (Eds.). Oxford handbook of affective computing. New York: Oxford University Press.
• Calvo, R. A., & D'Mello, S. K. (2010). Affect detection: An interdisciplinary review of models, methods, and their applications. IEEE Transactions on Affective Computing, 1(1), 18-37.
• Calvo, R. A., D'Mello, S. K., Gratch, J., & Kappas, A. (Eds.). (2014). Oxford handbook of affective computing. New York: Oxford University Press.
• Calvo, R. A., & Ellis, R. A. (2010). Student conceptions of tutor and automated feedback in professional writing. Journal of Engineering Education, 99(4), 427-438.
• Davis, J. (2010). Generating directions for persuasive technology design with the inspiration card workshop. In T. Ploug, P. Hasle, & H. Oinas-Kukkonen (Eds.), Proceedings of the 5th International Conference on Persuasive technology, PERSUASIVE 2010 (pp. 262-273). Berlin: Springer.
• Ekman, P. (1992). An argument for basic emotions. Cognition and Emotion, 6(3-4), 169-200.
• Estrin, D., Govindan, R., Heidemann, J., & Kumar, S. (1999). Next century challenges: Scalable coordination in sensor networks. In Proceedings of the 5th annual ACM/IEEE International Conference on Mobile Computing and Networking (pp. 263-270). New York: ACM.
• Friedman, B. (1996). Value-sensitive design. Interaction, 3(6), 16-23.
• Friedman, B. (Ed.). (1997). Human values and the design of computer technology (p. 320). Cambridge, UK: Cambridge University Press.
• Friedman, B., & Kahn, P. H. (1992). Human agency and responsible computing: Implications for computer system design. Journal of Systems and Software, 17(1), 7-14.
• Friedman, B., Kahn, P. H., Jr., & Borning, A. (2006). Value sensitive design and information systems: Human-computer interaction in management information systems. Foundations, 5, 348-372.
• Grassi, A., Gaggioli, A., & Riva, G. (2009). The green valley: The use of mobile narratives for reducing stress in commuters. Cyberpsychology & Behavior, 12(2), 155-161.
• Hekler, E. B., Klasnja, P., Froehlich, J. E., & Buman, M. P. (2013) Mind the Theoretical Gap: Interpreting, Using, and Developing Behavioral Theory in HCI Research. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems 3307-3316, New York: ACM.
• King, L. A., & Miner, K. N. (2000). Writing about the perceived benefits of traumatic events: Implications for physical health. Personality and Social Psychology Bulletin, 26(2), 220-230.
• Li, I., Dey, A., & Forlizzi, J. (2010). A stage-based model of personal informatics systems. In Proceedings of the 28th International Conference on Human Factors in Computing Systems (pp. 557-566). New York: ACM.
• Li, I., Dey, A., Forlizzi, J., Hook, K., & Medynskiy, Y. (2011). Personal informatics and HCI: Design, theory, and social implications. In Proceedings of the 2011 annual conference: Extended abstracts on human factors in computing systems (pp. 2417-2420). New York: ACM.
• Lupton, D. (2012). M-health and health promotion: The digital cyborg and surveillance society. Social Theory & Health, 10(3), 229-244. doi:10.1057/sth.2012.6.
• Pennebaker, J. W. (1997). Opening up: The healing power of expressing emotions (p. 249). New York: Guilford Press.
• Pennebaker, J. W. (2004). Writing to heal: A guided journal for recovering from trauma and emotional upheaval. Oakland, CA: New Harbinger.
• Picard, R. W. (1997). Affective computing (p. 275). Cambridge, MA: MIT Press.
• Preziosa, A., Grassi, A., Gaggioli, A., & Riva, G. (2009). Therapeutic applications of the mobile phone. British Journal of Guidance & Counselling, 37(3), 313-325.
• Riva, G. (2005). Virtual reality in psychotherapy (review). Cyberpsychology & Behavior, 8(3), 220-230.
• Sellen, A., Rogers, Y., Harper, R., & Rodden, T. (2009). Reflecting human values in the digital age. Communications of the ACM, 52(3), 58-66.
• Siegel, M. A., & Beck, J. (2014). Slow change interaction design. Interactions of the ACM, 21(1), 28-35.
• Spahn, A. (2011). And lead us (not) into persuasion…- Persuasive technology and the ethics of communication. Science and Engineering Ethics, 18(4), 633-650.
• Verganti, R. (2008). Design, meanings, and radical innovation: A metamodel and a research agenda. Journal of Product Innovation Management, 25, 436-456.
• Vertegaal, R. (2003). Attentive user interfaces. Communications of the ACM, 46(3), 30-33.
• Villalon, J., Kearney, P., Calvo, R. A., & Reimann, P. (2008). Glosser: Enhanced feedback for student writing tasks. In Eighth IEEE International Conference on Advanced Learning Technologies (pp. 454-458). Santander, ES: IEEE.
• Weiser, M. (1991). The computer for the 21st century. Scientific American, 265(3), 94-104.
• Yarosh, S., Radu, I., Hunter, S., & Rosenbaum, E. (2011). Examining values: An analysis of nine years of IDC research. In 10th International Conference on Interaction Design and Children. IDC 2011 (pp. 136-144). Ann Arbor: University of Michigan.
• Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer Networks, 52(12), 2292-2330.
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