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Panel on Measuring Subjective Well-Being in a Policy-Relevant Framework; Committee on National Statistics; Division on Behavioral and Social Sciences and Education; National Research Council; Stone AA, Mackie C, editors. Subjective Well-Being: Measuring Happiness, Suffering, and Other Dimensions of Experience [Internet]. Washington (DC): National Academies Press (US); 2013 Dec 18.

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Subjective Well-Being: Measuring Happiness, Suffering, and Other Dimensions of Experience [Internet].

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Subjective well-being (SWB) refers to how people experience and evaluate their lives and specific domains and activities in their lives. Over the past decade, interest in information about SWB (also called “self-reported wellbeing”) has increased markedly among researchers, politicians, national statistical offices, the media, and the public.1 The value of this information lies in its potential contribution to monitoring the economic, social, and health conditions of populations and in potentially informing policy decisions across these domains (Krueger et al., 2009; Layard, 2006).

Economists, psychologists, and sociologists have found a number of distinct components of SWB to coexist but which are not entirely independent—they do overlap. These measurement constructs may be thought of in terms of a continuum, with essentially real-time assessments of experience, emotional state, or sensations at one end (associated with the shortest time unit) and overall evaluations of life satisfaction, purpose, or suffering at the other end (the longest reference periods or no particular reference period).

These temporal overlaps notwithstanding, the components of SWB display distinct characteristics, often correlate with different sets of variables, and capture unique aspects of the construct that for various purposes are each worth monitoring. The terms used to describe SWB have often been ambiguously applied, which has muddled discussion and possibly slowed progress in the field. For example, the term “happiness” has been used to refer to momentary assessments of affect as well as to overall life evaluations. This absence of precision precludes understanding of the complexities known to coexist. For example, a person who is engaged in stressful or difficult activities, such as working toward an education or a job promotion, may find substantial meaning or satisfaction with life overall; a person who is generally suffering or lacking hope may experience temporary reprieve in an enjoyable moment.

The nature of the policy or research question being asked dictates the appropriate construct to measure SWB and may suggest an approach to data collection. For example, if the dimension of interest is known to be sensitive on a very short time frame and responds to daily activities and events but is somewhat stable over long periods, a cross-sectional data collection conducted every 2 years may not be useful. In such cases, a high-frequency approach (even if it involves a much smaller sample) might be most informative.2 Similarly, if a measure varies a great deal from individual to individual on a given day but does not react very much to exogenous events (financial shocks, changes in employment rates, etc.) and tends to wash out at high aggregate levels, it may not be a particularly insightful construct to track at national levels over time.

The following sections briefly identify the distinct components that must be measured in order to produce a full and clear accounting of SWB. Chapter 2 discusses these components and the interactions among them in greater detail.

1.1.1. Evaluative Well-Being

Measures of evaluative well-being are designed to capture judgments of overall life satisfaction or fulfillment; these judgments may be applied to specific aspects of life, such as relationships, community, health, or occupation, as well as to overall evaluations. An example of a question phrased to measure evaluative well-being—one recommended by OECD (2013, p. 253) and based on the World Values Survey—is “Overall, how satisfied are you with life as a whole these days?” Although OECD has proposed a scale from 0 to 10 for this question (OECD, 2013, p. 254), different scales have been used for versions of the question by other surveys, including the UK Office for National Statistics (ONS), the French national statistics office, the British Household Panel Study, the Canadian General Social Survey, the German Socioeconomic Panel, and the European Social Survey.

Alternative measures of evaluative well-being exist, such as the CASP-19, a quality-of-life scale for older people that is often used in research on aging (Hyde et al., 2003), the Cantril Self-Anchoring Striving Scale (Cantril, 1965), and the five-item scale designed by Diener et al. (1985) to measure global cognitive judgments of life satisfaction. The Cantril Scale is the instrument for measuring evaluative well-being used in several Gallup initiatives, including the World Poll.3 Research (e.g., Fredrickson et al., 2013) suggests that different aspects of well-being may have distinct physiological correlates. Longitudinal studies indicate moderate stability of life satisfaction over time; the variation that has been observed suggests there are potentially modifiable contextual factors that influence judgments about some aspects of evaluative well-being.

1.1.2. Experienced Well-Being

Experienced well-being (ExWB)—the focus of this report—is closely related to the oft-used term “hedonic well-being,”4 which Christodoulou et al. (2013, p. 2) characterized as referring to:

the frequency and intensity of emotional experiences such as happiness, joy, stress, and worry that make a person's life pleasant or unpleasant (Kahneman and Deaton, 2010). A variety of disciplines have shown increasing interest in the accurate assessment of HWB [hedonic well-being], especially positive aspects of well-being (Seligman and Csikszentmihalyi, 2000; Kahneman and Krueger, 2006; Huppert et al., 2004; Krueger et al., 2009). Research has begun to delineate the neurobiological foundations of [hedonic well-being] (Davidson, 2004) and to discern broad and important implications in areas such as health and society. In health research, positive affect has been found to predict response to illness (Cohen et al., 2003) and even survival among older men and women (Steptoe and Wardle, 2011). In the economic and social arenas, there is a realization that traditional economic measures such as income provide an incomplete explanation of societal wellbeing (Easterlin, 2001; Kahneman and Deaton, 2010) and that appropriate measurement of [hedonic well-being] could serve as a useful complement to traditional economic indicators (Kahneman et al., 2004; Seaford, 2011).

Thus, measures of ExWB are designed to reflect some combination of “positives,” such as pleasure, joy, contentment, or happiness, and “negatives,” such as suffering, distress, sadness, stress, or worry. These measures are obtained from personal (subjective) reports that are made either in real time or shortly after an event has occurred.

The distinction between positive and negative emotions (or affect) is essential, as evidence is conclusive that one is not simply the inverse of the other. And there is little doubt that positive and negative dimensions track at least partially independently of life satisfaction and of each other. Additionally, other dimensions of ExWB, such as anger or arousal, which relate to positive and negative emotions in a range of ways, are important. Sensations such as pain may also figure into emotional states and into hedonic assessment of those states. Finally, cognitive appraisals of the meaning, purpose, or worthwhileness of current activities may also be included in the ExWB construct.

Examples of techniques for measuring ExWB, discussed in detail in Chapter 3, include applications of the Positive and Negative Affect Schedule (Watson et al., 1988) and a range of approaches involving Ecological Momentary Assessment (Stone and Shiffman, 1994). Data on ExWB have been collected less frequently in large surveys than have data on life evaluations, and methods for collecting data on hedonic experience in real time—experience sampling—have rarely been applied to a representative population sample because they are burdensome. Less intense methods, such as the Day Reconstruction Method (Kahneman et al., 2004), designed to help individuals recover their experiences and associated emotions of the day before (described in detail below), have been implemented through representative samples. Another class of single-day measurement approaches for ExWB, such as that used in the Gallup-Healthways Well-Being Index, asks about the presence of a range of emotions the previous day; others ask about emotional experience at the end of the reference day.

Along with the life-evaluation questions, the OECD Guidelines recommend a global-yesterday question for use in a module designed to include a minimal set of measures for use in government household surveys. Derived from the Gallup World Poll and European Social Survey, the recommended questions are phrased as follows (OECD, 2013, p. 253):

The following question asks about how you felt yesterday on a scale from 0 to 10. Zero means you did not experience the feeling “at all” yesterday while 10 means you experienced the feeling “all of the time” yesterday. I will now read out a list of ways you might have felt yesterday.

A3. How about happy?

A4. How about worried?

A5. How about depressed?

Other surveys with components to measure ExWB use different (sometimes very different) emotion or affect adjectives.5

1.1.3. Eudaimonic Well-Being

Eudaimonic well-being refers to people's perceptions of the meaningfulness (or pointlessness), sense of purpose, and value of their life—a very broad set of considerations. The ancient Greek concept of eudaimonia implies a premise that people achieve happiness if they experience life purpose, challenges, and growth. “Flourishing” is a term that has been suggested (Keyes, 2002) as capturing the essence of this dimension of well-being. An example of a eudaimonic question—developed by ONS for the Annual Population Survey—asks respondents, “Overall, to what extent do you feel the things you do in your life are worthwhile?” In this case, a 0 to 10 scale is used, where 0 means the respondent feels the things they do in their life “are not at all worthwhile” and 10 means “completely worthwhile” (OECD, 2013, p. 253).

There has been less research into eudaimonic well-being than into either evaluative or ExWB; consequently, its role in explaining behavior is less well understood. For some questions, such as the “worthwhileness” of specific activities or the role of purpose in a person's assessment of overall satisfaction with life, eudaimonic sentiments may figure into emotional states or into evaluations of life satisfaction. All subjective reports involve either evaluations or experiences, or both. However, concepts of “worthwhileness” or purpose appear crucial for understanding (or predicting) why and when people engage in various activities during the day or choose various life courses. White and Dolan (2009) have measured the worthwhileness (reward) associated with activities using day reconstructions of time and activities. They find discrepancies between those activities that people find “pleasurable” as compared to “rewarding” or meaningful. For example, time spent with children is relatively more rewarding than pleasurable, whereas time spent watching television is relatively more pleasurable than rewarding.


The objective of this report is to:

  • Review the current state of research and evaluate methods for measuring self-reported hedonic (or experienced) well-being that are useful for monitoring, informing, and policy analysis purposes. Although the emphasis of this report is on ExWB and time-based approaches, their relationships with measures of evaluative wellbeing are considered. The report does not assess the value of evaluative well-being measures.
  • Assess whether research on, and the methods to study, ExWB have advanced to a point that warrants the federal government collecting data in surveys and constructing indicators, accounts, or other statistics to inform social and economic policies—recognizing that the UK and U.S. statistics agencies are at different stages of development with regard to measurement constructs for SWB and operate within very different systems. In assessing the reliability and value of data on ExWB, the point of comparison should be other measures that are routinely collected; otherwise the comparison may be with a perfect world, not the real one.
  • Recommend strategies for implementing data collection on ExWB, or, if premature, outline work that needs to be done before moving measurement of ExWB to statistical agency agendas.

The panel charge, verbatim, is reproduced in Box 1-1.

Box Icon

BOX 1-1

Panel Charge. An ad hoc panel will review the current state of research and evaluate methods for the measurement of subjective well-being (SWB) in population surveys. On the basis of this evaluation, the panel will offer guidance about adopting SWB measures (more...)

The value of research on SWB and the insights it has produced have been well established in the literature over recent decades. Much of this research has relied on nongovernment data collections, such as those conducted by the Gallup Organization. A central task of this study is to assess and provide guidance about the optimal role that statistical agencies might play in collecting, coordinating, and publishing data needed to advance the field further and potentially to inform policy discussions.

It should be made explicit here that the panel's interpretation of its charge was to provide guidance primarily for the measurement and data collection in the area of experienced (hedonic) well-being. In line with this emphasis, this report partially sets aside a substantial body of work on policy-relevant measures of evaluative well-being.6 Guides to this work may be found in the 2009 report by Stiglitz, Sen, and Fitoussi, the recently released OECD Guidelines on Measuring Subjective Well-being (OECD, 2013) or the World Happiness Report (Helliwell et al., 2012), to name just a few. Additionally, the sponsors of this study (the U.S. National Institute on Aging and the UK Economic and Social Research Council)—which are keenly interested in the development and refinement of measures and concepts covering the full range of well-being—have noted that the measures of well-being used in aging research have focused almost exclusively on life satisfaction addressing many questions, which they rightfully argue is not sufficient. Our understanding of ExWB is more incomplete, yet its measurement may be equally valuable in that it likely taps somewhat different domains of psychological functioning. Indeed many of the concerns related to an aging population center around quality of life, well-being, and the reduction of suffering on a day-to-day basis.


Data collections on SWB and related constructs have already proven to be highly valuable to researchers, producing insights into the emotional states and self-evaluated life satisfaction of people belonging to different groups, engaged in different activities, at different points in the life course, and involved in different family and community structures. Research has also shown how these subjectively assessed states of individuals relate to their behavior and decisions. Additionally, the media, politicians, and the general public have shown a strong interest in the information portrayed in these data and statistics.

The case for policy relevance is still developing but is well in motion. In the broadest sense, the promise of studying self-reported well-being rests in its capacity to enhance measures of (1) suffering (particularly long-term suffering) in a way that provides insights into its reduction, and (2) positive experiences in a way that informs efforts to increase or enhance them. A reasonable analogy can be drawn with poverty. Once poverty reduction emerged as a policy priority, a need to define and measure it (i.e., to design a poverty measure) was created. And to be most useful, information needed to be simultaneously collected on variables, such as education, health, economic mobility, and other factors that relate to poverty, whether as a cause, as a result, or in a circular fashion. This analogy also highlights the need to embed measurement of SWB in the most useful contexts. For example, if long-term unemployment, depression, lack of income, or lack of social connectedness prove to be drivers of long-term suffering, appropriate datasets are those that include covariate information on employment status (e.g., Current Population Survey's American Time Use Survey [ATUS]), mental health (e.g., National Health Interview Survey), income (e.g., Survey of Income and Program Participation), and social capital (e.g., American Housing Survey's Neighborhood Social Capital module). Likewise, promising data collection vehicles would be implied if positive affect were shown to have a measurable impact on health or workforce productivity.

In Chapter 5, the panel cites several policy applications or potential applications, ranging from assessment of end-of-life treatment options, cost-benefit studies of health care delivery (particularly where dimensions not captured by longevity or quality-adjusted life year metrics are present), and commuting and transportation planning, to environmental valuation and outdoor recreation resource monitoring. Beyond cases where SWB data may allow for fuller cost-benefit analyses of policy options, there may also be reverse cases, where measures of people's SWB are indicative of a factor driving outcomes; the impact of positive affect on resistance to or ability to recover from illness is an actively researched example. As is true for most measures, even those viewed as “objective,” the goal is not to have a perfect measure of SWB but to generate data that can be usefully combined with other information and incorporated in a range of policy applications.

Spurred by the types of questions described above—along with an increasing desire by policy makers, researchers, and the public for a richer concept of progress and well-being than can be provided by traditional market-based measures on their own—research on SWB has recently accelerated and calls for data collection by statistical offices have been invigorated. Pointed impetus to the movement was provided by the Commission on the Measurement of Economic Performance and Social Progress, established by French President Nicolas Sarkozy and chaired by Joseph Stiglitz, which argued that governments and population surveys should measure people's well-being as a way of assessing societal progress (Stiglitz et al., 2009). The Commission included a working group that analyzed new measures of quality of life, including subjective ones, and its report emphasized that economic growth alone (as measured, for example, by growth in gross domestic product [GDP]) is not a satisfactory measure of the standard of living. The Commission recommended a shift in the focus of economic measurement from production toward people's well-being (Stiglitz et al., 2009). The underlying argument is that, at least in developed nations, per capita GDP is high (some argue that societies now over-consume) and the focus of national policies should shift to issues of inequality (even with high per capita GDP, those at the bottom of the economic ladder still suffer), sustainability, and nonmarket dimensions of well-being that cannot all be well captured by conventional, “objective” measures of well-being.

Emerging and ongoing efforts around the world to establish measures of and statistics on SWB also provide a strong impetus for this report. Initiatives by national statistical offices and international organizations are very much in their experimental phases, so this is the time to contribute input to them. The panel sees a clear need emerging to provide guidance for next steps to advance data, surveys, and research on the subject. An overarching part of such guidance is the need for clarification and a better understanding of the different dimensions of SWB, the specific information added by data on measures of ExWB, and the kinds of policy-relevant questions such data would inform.

In the United States, ATUS has, since 2010, included a module asking respondents about feelings (pain, happiness, stress, sadness, tiredness) during specific episodes of the day. Given the extensive and rapidly growing academic literature on time use and SWB (see references at front of chapter), this is an appropriate time to assess that literature and to determine whether and how to apply it in the statistical policies of the U.S. government. Appendix B to this report provides support for and guidance on the continuation and development of the ATUS module on SWB.

Among efforts currently under way that are attempting to advance measurement of SWB among national statistical offices, perhaps the most prominent is the recently developed and published OECD Guidelines on Measuring Subjective Well-being (2013). The Guidelines are intended to:

Improve the quality of subjective well-being measures collected by national statistical offices, by providing best practice in terms of question wording and survey design; improve the usefulness of the data collected by setting out guidelines on the appropriate frequency, survey vehicles, and covariates when collecting subjective well-being data; improve cross-country comparability of subjective well-being measures by establishing common concepts, classifications, and methods that national statistical agencies could use; and provide advice and assistance to data users when analyzing subjective well-being data. (OECD, 2013, p. 9)

National statistical offices are now being called upon to begin systematically gathering and publishing information on subjective measures of well-being. ONS now includes a set of four questions on the core of its Integrated Household Survey covering three aspects of SWB: life evaluation, momentary emotional state, and worthwhileness. Beginning in April 2011, ONS included the following questions on its Annual Population Survey and Opinions and Lifestyle Survey:

  • Overall, how satisfied are you with your life nowadays? [evaluative well-being]
  • Overall, to what extent do you feel the things you do in your life are worthwhile? [eudaimonic well-being]
  • Overall, how happy did you feel yesterday? [experienced well-being]
  • Overall, how anxious did you feel yesterday? [experienced well-being]

All were answered on a scale of 0 to 10 where 0 is “not at all” and 10 is “completely.”7

Elsewhere, the French national statistical office has collected information on SWB, and on ExWB specifically, in the Enquete Emploi du Temps 2009–2010. Plans are in motion to collect data on SWB by the statistical systems in a number of other European nations and beyond, including South Korea and Japan. Chile now has a life satisfaction question in its annual National Socioeconomic Survey, which produces high-quality, annual poverty information at the household level. Other countries have long collected information on SWB: Canada has done so in the General Social Survey since 1985; New Zealand collects data on life satisfaction through its General Social Survey; and Australia has collected information on SWB in its Household, Income and Labour Dynamics in Australia Survey. In addition to several new initiatives, the Japanese government has collected data on SWB continuously since 1958 in its Life in Nation Surveys (Stevenson and Wolfers, 2008). Eurostat began developing a module on SWB for the European System of Social Surveys. Some international agencies, such as the World Health Organization, have long worked with quality-of-life measures; typically these have been assessments of evaluative, as opposed to experienced, well-being.

Although a few national statistical offices are in the forefront of obtaining regular measures of well-being, most (including the United States) have played only a limited role in this regard. Indeed, some of the most prominent surveys measuring SWB and comparing countries' performance are undertaken by commercial and academic organizations. The most widely used (and largest) datasets on SWB are the Gallup Organization's World Poll—begun in 2005 and covering 160 countries—and Gallup World Values Survey. The Gallup World Poll is a repeated annual cross-sectional survey that includes life evaluation and ExWB questions, as well as many factors beyond self-reported well-being, such as perceptions of work, social, financial, physical, and community well-being; perception of leadership; basic access to food, shelter, safety; and others. In 2008, Gallup instituted a daily poll of 1,000 individuals in the United States that includes evaluative and ExWB. The World Values Survey, which is also cross-sectional, collects information on life evaluation and overall happiness and has sometimes also included questions asking about more focused measures of experienced emotion and mood.

A number of national surveys conducted by academic institutions, often funded by governmental organizations, include assessments of SWB as a component of their standard questionnaire/interview protocol. These are usually very brief assessments composed of just a few questions, because interview time is at a premium. One example of this in the United States is the Health and Retirement Study funded by the National Institute on Aging, which has a goal of understanding and monitoring the impact of retirement on health and well-being. It is a large-scale, prospective survey of individuals over age 50 and has included several questions to evaluate SWB. The Behavioral Risk Factor Surveillance System, which is a very large cross-sectional telephone survey designed for investigating behavioral risk factors, includes a life-satisfaction question that has been used by researchers (e.g., Oswald and Wu, 2009). It is government-run (by the U.S. Centers for Disease Control and Prevention) and conducted by individual state health departments. The Survey of Health, Ageing and Retirement in Europe, conducted by a consortium of European investigators, has been used to compare eudaimonic and hedonic ratings with each other and across countries (Vanhoutte et al., 2012). The German Socioeconomic Panel and the British Household Panel Study (recently integrated into the UK Household Longitudinal Study) include brief questions on evaluative well-being of the form “How happy are you at present with your life as a whole?” The Health and Retirement Study has been working on developing survey-friendly versions of short hedonic assessments and piloting them in subsamples of the larger data collection. The panel discusses these efforts further in later parts of the report.


The audience for this report includes statistical agencies, research funding agencies, policy makers, researchers, and the general public. Most of the recommendations in this report are directed toward U.S. statistical agencies that either are already engaged in collection of self-reported well-being information or may do so in the future. However, the report also presents guidance for a research program that is relevant to science and health funding agencies. Additionally, the panel hopes that the report will prove useful to researchers and others interested in the multidimensional nature of moment-to-moment and reflected well-being—something that is much more nuanced and difficult to measure than can be understood simply by asking people if they are happy.

The remainder of the report is structured as follows: Chapter 2 sketches a brief history of measurements of self-reported well-being and their inclusion in survey development; it also defines more technically the evaluative, experienced, and eudaimonic approaches introduced above. Objectives of this careful definition are to clarify the distinctiveness of experienced (and hedonic) well-being from evaluative well-being (life satisfaction) and to assess the relationships among these different dimensions, including the extent to which each measures something unique. The panel also begins its exploration of the implications of this multidimensionality for policy application.

Chapter 3 delves more deeply into ExWB, identifying in greater detail its dimensions and the alternative techniques for measuring them. The panel assesses the state of research on methods for measuring its many dimensions, positive and negative, as well as related sensations such as pain, anger, arousal, etc., across different reference periods, from the momentary to day-long assessments and reconstructions.

Chapter 4 addresses a series of conceptual and measurement issues ranging from cultural and aging effects to survey ordering, context, and mode effects. In the process of discussing difficult survey issues, various types of self-reported bias are identified, along with other aspects of the science that are not well understood. These points in turn suggest a number of research needs, stated throughout the chapter.

Chapter 5 focuses on the potential of measures of self-reported wellbeing, and particularly measures of ExWB, to inform policy decisions. It identifies what is known about the predictive capacity of these measurement constructs, which in turn suggests what questions can be informed by the data. The panel evaluates current policy uses of the data and promising directions, and it discusses the value of data on these constructs beyond policy (for example, as a general informing and monitoring tool).

Chapter 6 focuses on data collection strategies. It presents an overall approach that involves leveraging existing datasets and modifying ongoing data collection efforts. The panel notes the important role of smaller-scale studies, the use of nontraditional surveys, and new technologies to address specific questions.

Appendixes to the report provide details on some of the key ExWB questions and modules currently in place, such as those in the ONS Annual Population Survey, the HWB-12 Survey, and the Gallup World Survey. Also included as Appendix B is a separate report produced in mid-project by the panel, which was written to assess and provide guidance specifically on the ATUS.



OECD (2013) notes that, just in economics, a search of the Econlit database for a recent year (2008 is cited) returns more than 50 articles per year on SWB whereas, for the 1990s, the same search returns fewer than 5 per year, on average.


Consumer confidence, for example, can display this kind of pattern, which may be a reason that the survey on which the University of Michigan Consumer Sentiment Index is based is designed as it is—with fairly small samples but ongoing data collection.


The Cantril Self-Anchoring Scale asks respondents to imagine a ladder with steps numbered from 0 at the bottom to 10 at the top, in which the top of the ladder represents the best possible life for them and the bottom of the ladder represents the worst possible life. They are asked which step of the ladder they personally feel they stand on at this time (for a present assessment). For a good description and discussion of the Cantril Scale, see Diener et al. (2009).


The terms “hedonic well-being” and “experienced well-being” are often used interchangeably in the literature. Interpreted more precisely, the latter is a somewhat broader concept in that hedonic well-being refers specifically to moment-to-moment emotional states, while experienced well-being may be extended to include sensations (e.g., pain, arousal) or other factors beyond emotions. However, the two terms are very closely related, especially because the additional “experience” dimensions of the latter concept may directly impact the individual's emotional states.


See Appendix A for a more extensive sample of questions currently in use to evaluate self-reported well-being.


We qualify with “partially” because the relationships between experienced and evaluative well-being are described in some detail in section 2.1.


For more information on the ONS program, see Measuring Subjective Well-being in the UK on the ONS website: http://www​ [October 2013].

Copyright 2013 by the National Academy of Sciences. All rights reserved.
Bookshelf ID: NBK179225


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