Social scientists started measuring subjective life-evaluations as well as positive and negative affective experiences in the 1960s. Sixty years of research have established that life-satisfaction judgments and the balance of PA and NA are strongly correlated in Western countries. The choice of affect items has a relatively small effect on the magnitude of the correlation. In contrast, systematic measurement error plays a stronger role. Systematic measurement error can inflate and attenuate true correlations. The existing results suggest that two sources of systematic measurement error have opposite effects. Evaluative bias inflates the observed correlation, but rater-specific measurement error attenuates the true correlation. The latter effect is stronger. As a result, multi-method studies produce stronger correlations. At present, I would interpret the data as evidence that the true correlation is around r =.7 +/- .2. (.5 to .9). This implies that affective balance explains about half of the variance in life-evaluations. Cross-cultural studies suggest that the true correlation might be lower in Asian cultures, but the difference is relatively small (.6 vs. .5, without controlling for systematic measurement error).
The finding that affective balance explains only some of the variance in life-satisfaction judgments raises an interesting new question that has not received much attention. What does lead to positive life-evaluations in addition to pleasure and pain? An exploration of this question requires the measurement of LS, PA and NA, and the specification of causal model with affective balance as a predictor of life-satisfaction. The few studies that have examined this question have found that domain satisfaction (Schimmack et al., 2002), intentional living (Busseri, 2015), and environmental mastery (Payne & Schimmack, 2021) are substantial unique predictors of subjective life-evaluations. These results are preliminary. Existing datasets and new studies can reveal additional predictors. Evidence of cultural variation in the importance of affective experiences needs to be replicated and additional moderators should be explored. Identifying a reliable set of predictors of life-satisfaction judgments can provide insights into individuals implicit definition of the good life. This information may be useful to evaluate objective theories of well-being and to evaluate the validity of life-satisfaction judgments as measures of subjective well-being. The present results are inconsistent with a view of humans as homo hedonimus, who only cares about affective experiences, but the results do suggest that pleasure and pain cannot be ignored in a theory of human well-being.
Positive Affect (PA) and Negative Affect (NA) are scientific constructs. People have expressed their feelings for thousands of years. Across many cultures, some emotion terms have similar meanings and are related to similar antecedents and consequences. However, I am not aware of any everyday expressions of feelings that use the terms Positive Affect or Negative Affect. Yet, the scientific concepts of PA and NA were created to make scientific claims about everyday experiences like happiness, sadness, fear, satisfaction, or frustration. The distinction between PA and NA implies that a major distinction between affects is that some affects are positive and others are negative. Yet, psychologists do not have a consensual definition of Positive Affect and Negative Affect.
While PA and NA were used occasionally in the scientific literature, the terms became popular after Bradburn developed the first measures of PA and NA and reported the results of empirical studies with Bradburn’s PA and NA scales . The first report did not even use the term affect and referred to the sales as measures of positive and negative feelings (Bradburn & Caplovitz, 1965). The terms positive affect and negative affect were introduced in the follow-up report (Bradburn, 1969).
To understand Bradburn’s concepts of PA and NA, it is useful to examine the social and historical context that led to the development of the first PA and NA scales. The scales were developed to “provide periodic inventories of the psychological well-being of the nations’ [USA] psychological well-being” (p. 1). However, the introduction also mentions the goal to “better understand the patterning of psychological adjustment” (p. 2) and “to determine the nature of mental health, as well as to determine the causes of mental illness” (p. 2). This sweeping agenda creates conceptual confusion because it is no longer clear how PA and NA are related to well-being and mental health. Although it is likely that PA and NA are related to some extent to well-being and mental health, it is unlikely that well-being or mental health can be defined in terms of PA and NA. Even if this were possible, it would only clarify the meaning of well-being and mental health, but not the meaning of PA and NA.
More helpful is Bradburn’s stated objected for developing his PA and NA scales. The goal was to “measure a wide range of pleasurable and unpleasurable experiences apt to be common in a heterogeneous population” (Bradburn & Caplovitz, 1965; p. 16). This statement of the objective makes it clear that Bradburn used the term positive affect to refer to pleasurable experiences and the term negative affect to refer to unpleasant experiences. Bradburn (1969) is even more explicit. His assumption for the validity of the self-report measure was that “people tend to code their experiences in terms of (among other things) their affective tone – positive, neutral, or negative. For our purposes, the particular content of the experience is not important. We are concerned with the pleasurable or unpleasurable character associated with the experience” (p. 54). Other passages also make it clear that Bradburn’s goal was to measure the hedonic tone of everyday experiences. In short, the distinction between PA and NA is based on the hedonic tone of the affective experiences. PA feels good and NA feels bad.
Bradburn’s (1969) final chapter provides the most important information about his sometimes implicit assumptions underlying his approach to the study of psychological well-being, mental health, or happiness. “We are implicitly stating our belief that the modern concept of mental health is really a concerns about the subjective sense of well-being, or what the Greeks called eudaimonia” (p. 225). It is also noteworthy that Bradburn did not reduce happiness to the balance of PA and NA. “By naming our forest “psychological well-being,” we have not meant to imply that concepts such as self-actualization, self-esteem, ego-strength, or autonomy, …., are irrelevant to our study… While we have said relatively little about these particular trees, we do not doubt that they are an integral and important part of the whole” (p. 224). Accordingly, Bradburn rejects the hedonistic idea that well-being can be reduced to the balance of pleasure and pain, but he assumed that PA and NA are important to the conception of a good life.
However, defining well-being in terms of PA, NA, and other good things in life is not a satisfactory definition of well-being. A complete theory of well-being would have to list the additional ingredients and justify their inclusion in a definition of well-being. Philosophers and some psychologists have tried to defend different conceptions of the good life (Sumner, 1996). The main limitation of these proposals is that it is difficult to defend one conception of the good life as superior to another. The key problem is that it is difficult to find a universal, objective criterion that can be used to evaluate individuals’ lives (Sumner, 1996).
One solution to this problem is to take a subjective perspective. Accordingly, individuals can chose their own ideals and evaluate their lives accordingly. In the 1960s, social scientists developed subjective measures of well-being. One of the first measures was Cantril’s ladder that asked respondents to place their actual lives on a ladder from 0 = worst possible life to 10 = best possible life. This measure does not impose any criteria on the life-evaluations. This measure continues to be used to this day. The measure is a subjective measure of well-being because respondents can use any information that they consider to be important to rate their lives. In theory, they could rely exclusively on the hedonic tone of their everyday experiences. In this case, we would expect a strong correlation between affective balance and life-evaluations. However, it is also possible that individuals follow other goals that do not aim to maximize pleasure and to minimize pain. In this case, the correlation between affective balance and life-evaluations would be attenuated. It is therefore interesting to examine empirically how much of the variance in life-evaluations or life-satisfaction judgments is explained by the hedonic tone of everyday experiences. Subsequently, I review the relevant studies that have examined this question over the past 50 years.
Bradburn (1969) simply states that “the difference between the numbers of positive and negative feelings is a good predictor of a person’s overall ratings of his own happiness” (p. 225), but he did not provide quantitative information about the amount of explained versus unexplained variance.
The next milestone in well-being research was Andrews and Whitey’s (1976) examination of the validity of well-being measures. They included Bradburn’s items, but modified the response format from a dichotomous yes/no format to a frequency format. They assumed that this might produce negative correlations between the PA and NA scales, but this expectation was not confirmed. More interesting is how much the balance of PA and NA correlated with subjective well-being ratings. The key finding was that affect balance scores correlated only r = .43 with a 7-point life-satisfaction rating, and r = .47 with a 7-point happiness scale, while the two global ratings correlated r = .63 with each other. Corrected for unreliability, this suggest that affective balance is strongly correlated with global life-evaluations, ((.43 + .47)/2)/sqrt(.63) = .57. Nevertheless, a substantial portion of the variance in global life-satisfaction judgments remains unexplained, 1-.57^2 = 68%. This finding undermines theories of well-being that define well-being exclusively in terms of the amount of PA and NA (Bentham, Kahneman, 1999). However, the evidence is by no means conclusive. Systematic measurement error in the PA and NA scales might severely attenuate the true influence of PA and NA on global life-evaluations, given the low convergent validity between self-ratings and informant ratings of affective experiences (Schneider & Schimmack, 2009).
Nearly a decade later, Diener (1984) published a highly influential review article on the field of subjective well-being research. In this article, he coined the term subjective well-being (SWB) for research on global life-satisfaction judgments and affective balance. SWB was defined as high life-satisfaction, high PA and low NA. Diener noted that the relationship among the three components of his SWB construct is an empirical question. He also pointed out that the relationship between PA and NA had received a lot of attention, whereas the relationship between affective balance and life-satisfaction “has not been as thoroughly researched” (p. 547). Surprisingly, this statement still rings true nearly 40 years later, despite a few attempts by Diener and his students, including myself, to study this relationship.
For the next twenty years, the relationship between PA and NA became the focus of attention and fueled a heated debate with proponents of independence (Watson, Clark, & Tellegen, 1988), bipolarity (Russell, 1980), and models of separate, yet negatively correlated dimensions (Diener, Smith, & Fujita, 1995). A general agreement is that time frame, response formats, and item selection influences the correlations among PA and NA measures (Watson, 1988). This raises a question about the validity of different PA and NA scales. If different scales produce different correlations between PA and NA, different scales may also produce different correlations between life-evaluations and affective balance. However, this question has not been systematically examined to this day.
To make matters worse, the debate about the structure of affect also led to confusion about the meaning of the terms PA and NA. Starting in the 1980s, Watson and colleagues started to use the terms as labels for the VARIMAX rotated first-two factors in exploratory factor analyses of correlations among affect ratings (Watson & Tellegen, 1985). They also used these labels for their Positive Affect and Negative Affect scales that were designed to measure these two factors (Watson, Clark, & Tellegen, 1988). They defined Positive Affect as a state of high energy, full concentration, and pleasurable engagement and Negative Affect as a state of subjective distress and unpleasurable engagement. An alternative model based on the unrotated factors, however, identifies a first factor that distinguishes affects based on their hedonic tone. Watson et al. (1988) refer to this factor as pleasantness-unpleasantness factor. Thus, PA is no longer equivalent with pleasant affect, and NA is no longer equivalent with unpleasant affect.
To avoid conceptual confusion, different labels have been proposed for measures that focus on hedonic tone and measures that focus on the PANAS dimensions. Some researchers have suggested to use pleasant affect and unpleasant affect for measures of hedonic tone. Others have proposed to label Watson and Tellegen factors Positive Activation and Negative Activation. In the broader context of research on well-being, PA and NA are often used in Bradburn’s tradition to refer to the hedonic tone of affective experiences, and I will follow in this tradition. I will refer to the PANAS scales as measures of Positive Activation and Negative Activation.
While it is self-evident that the PANAS scales are different from measures of hedonic tone, it is still possible that the difference between Positive Activation and Negative Activation is a good measure of affective balance. That is, individuals who often experience positive activation and rarely experience negative activation are in a pleasant affective state most of the time. In contrast, individuals who experience a lot of Negative Activation and rarely experience Positive Activation are expected to feel bad most of the time. Whether the PANAS scales are capable of measuring hedonic tone as well as other measures is an empirical question that has not been examined.
The next important article was published by Lucas, Diener, and Suh (1996). The authors aimed to examine the relationship between the cognitive component of SWB (i.e., life-satisfaction) and the affective component of SWB (i.e., PA and NA) using a multi-trait-multi-method approach (Campbell & Fiske, 1959). Study 1 used self-ratings and informant ratings of life-satisfaction on the Satisfaction with Life Scale and PANAS scores to examine this question. The key finding was that same-construct correlations were higher (i.e., LS r = .48, PA r = .43, NA r = .26) than different-construct correlations (i.e., LS-PA rs = .28, .31, LS-NA r = -.16, -.21, PA-NA r = -.02, -.14). This finding was interpreted as evidence that “life satisfaction is discriminable from positive and negative affect” (p. 616). The main problem with this conclusion is that the results do not directly examine the discriminant validity of life-satisfaction and affective balance. As affective balance is made up of two distinct components, PA and NA, it is self-evident that LS cannot be reduced to PA or NA alone. However, it is possible that life-satisfaction is strongly related to the balance of PA and NA. To examine this question it would have been necessary to compute an affective balance score or to use a latent variable model to regress life-satisfaction onto PA and NA. The latter approach can be applied to the published correlation matrix. I conducted a multiverse analysis with five different models that make different assumptions about the validity of self-ratings and informant ratings. The results were very similar and suggested that affective balance explains about half of the variance in life-satisfaction judgments, rs = .68 to .75. The higher amount of explained variance is partially explained by the lower validity of Bradburn’s scales (Watson, 1988) and partially due to the use of a multi-method approach as mono-method relationships were only r = .6, for self-ratings at Time 1, and r = .5, for self-ratings at time 2 (Lucas et al., 1996). In conclusion, Lucas et al.’s study provided evidence that life-satisfaction judgments are not redundant with affective balance when affective balance is measured with the PANAS scales. However, it is possible that other measures of PA and NA might be more valid and explain more variance in life-evaluations.
A couple of years later, Diener and colleagues presented the first article that focused on the influence of affective balance on life-satisfaction judgments (Suh, Diener, Oishi, & Triandis, 1998). The main focus of the article was cultural variation in the relationship between life-satisfaction and affective balance. Study 1 examined correlations in the World Value Survey that used Bradburn’s scales. Correlations with a single-item life-satisfaction judgment ranged from a maximum of r = .57 in West Germany to a minimum of r = .20 in Nigeria. The correlation for the US sample was r = .48, which closely replicates Andrews and Whitey’s results. Study 2 used the more reliable Satisfaction with Life Scale and hedonic items with an amount of time response format. This produced stronger correlations. The correlation for the US sample was r = .64. This is consistent with Lucas et al.’s (1996) mono-method results. This article suggested that affect contributes to subjective well-being, but does not determine it, and that culture moderates the use of affect in life-evaluations.
Diener and colleagues followed up on this finding, by suggesting that the influence of neuroticism and extraversion on subjective well-being is mediated by affective balance (Schimmack, Diener, & Oishi, 2002). The article also explored whether domain satisfaction might explain additional variance in life-satisfaction judgments. The key finding was that affective balance made a unique contribution to life-satisfaction judgments (b = .45), but two life-domains also made unique contributions (i.e., academic satisfaction, b = .27, romantic satisfaction, r = .23). Affective balance mediated the effects of extraversion and neuroticism. Schimmack et al. (2002) followed up on these findings by examining the mediating role of affective balance across cultures. They replicated Suh et al.’s (1998) finding that culture moderates the relationship between affective balance and life-satisfaction and found a strong relationship in the two Western cultures (US, German) in a structural equation model that controlled for random measurement error, r = .76. The stronger relationship might be due to the use of affect items that focus on hedonic tone.
The next big development in well-being research was the creation of Positive Psychology; the study of all things positive. Positive psychology promoted eudaimonic conceptions of well-being that are rooted in objective theories of well-being (Sumner, 1996). These theories clash with subjective theories of well-being that leave it to individuals to choose how they want to live their lives. An influential article by Keyes, Shmotkin, & Ryff (2002) pitted these two conceptions of well-being against each other, using the Midlife in the U.S. (MIDUS) sample (N = 3,032). The life-satisfaction item was Cantril’s ladder. The PA and NA items were ad-hoc items with an amount of time response format. This explains why the MIDUS PA and NA scales are strongly negatively correlated, r = -.62. PA and NA were also strongly correlated with LS, PA r = .52, NA r = -.46. The article did not examine the relationship between life-satisfaction and affective balance because the authors treated LS, PA, and NA as indicators of a latent variable. According to this model, neither life-satisfaction nor affective balance measure well-being. Instead, well-being is an unobserved construct that is reflected in the shared variance among LS, PA, and NA. Using the published correlations and assuming a reliability of .7 for the single-item life-satisfaction item (Busseri, 2015), I obtained a correlation of r = .66 between life-satisfaction and affective balance. This correlation is stronger than the correlation with the PANAS scales in Lucas et al.’s (1996) study, suggesting that hedonic PA and NA scales are more valid measures of hedonic tone of everyday experiences and produce correlations around r = .7 with life-satisfaction judgments in the United States.
In the 21st century, psychologists’ interest in the determinants of life-satisfaction judgments decreased for a number of reasons. Positive psychologists were more interested in exploring eudaimonic conceptions of well-being. They also treated life-satisfaction judgments as indicators of hedonic well-being and treated life-satisfaction judgments and affective measures as interchangeable indicators of hedonic well-being. Another blow to research on life-satisfaction was Kahneman’s suggestion that life-satisfaction judgments are unreliable and invalid (Kahneman, 1999; Schwarz & Strack, 1999) and his suggestion to focus on affective balance as the only criterion for well-being. Kahneman et al. (2006) reported that income predicted life-satisfaction judgments, but not measures of affective balance. However, this finding was not interpreted as a discovery that income influences well-being independently of affect, but rather as evidence that life-satisfaction judgments are invalid measures of well-being.
In contrast, sociologists continued to focus on subjective well-being and used life-satisfaction judgments as key indicators of well-being in important panel studies such as the General Social Survey, the German Socio-Economic Panel (SOEP), and the World Value Survey. Economists rediscovered happiness, but relied on life-satisfaction judgments to make policy recommendations (Diener, Lucas, Schimmack, & Helliwell, 2008). Although Gallup measures all three components of SWB, it relies exclusively on life-satisfaction judgments to rank nations in terms of happiness (World Happiness Reports, https://worldhappiness.report).
In 2008, I used data from a pilot study for the SOEP to replicate the finding that affective balance mediated the effects of extraversion and neuroticism (Schimmack, Schupp, & Wagner, 2008). The study also controlled for evaluative biases in self-ratings. In addition, unemployment and regional differences between former East and West Germany were unique predictors of life-satisfaction judgments. The unique effect of affective balance on life-satisfaction was r = .50. One reason for the weaker relationship is that the model controlled for shared method variance among life-satisfaction and affect ratings.
Kuppens, Realo, and Diener (2008) followed up on Suh et al.’s (1996) finding that culture moderates the relationship between affective balance and life-satisfaction. While they replicated that culture moderates the relationship, the use of a multi-level model with unstandardized scores made it difficult to assess the magnitude of these moderator effects. Furthermore, the authors examined moderation for the effects of PA and NA separately rather than evaluating cultural variation in the relationship between affective balance and life-satisfaction. Finally, the use of PA and NA scales makes it impossible to evaluate measurement equivalence across nations. Using the same data, I examined the relationship between affective balance and life-satisfaction using a multi-group structural equation model with a largely equivalent measurement model across 7 world regions (Northern Europe/Anglo, Southern Europe, Eastern Europe, East Asia, South Asia, Latin America, and Africa). I replicated that the correlation in Western countries is around r = .6 (Northern Europe/Anglo, r = .64, Southern Europe, r = .59). The weakest relationships were found in East Asia (r = .52) and South Asia (r = .51). While this difference was statistically significant, the effect size is rather small and suggests that affective balance contributes to life-satisfaction judgments in all cultures. A main limitation of this study is that it is unclear how much cultural differences in response styles contribute to the moderator effect. A comparison of the intercept of life-satisfaction (i.e., mean difference after controlling for mean differences in PA and NA) showed that all regions had lower life-satisfaction intercepts than the North-American/Anglo comparison group. This shows that factors unrelated to PA and NA (e.g., income, Kahneman et al., 2006) produce cultural variation in life-satisfaction judgments.
Zou, Schimmack, and Gere (2013) published a replication study of Lucas et al.’s sole multi-method study. The study was not a direct replication. Instead, it addressed several limitations in Lucas et al.’s study. Most importantly, it directly examined the relationship between life-satisfaction and affective balance. It also ensured that correlations are not attenuated by biases in life-satisfaction judgments by adding averaged domain satisfaction judgments as a predictor. The study also used hedonic indicators to measure PA and NA rather than assuming that the rotated Positive Activation and Negative Activation factors fully capture hedonic tone. Finally, the sample size was five times larger than in Lucas et al.’s study and included students and middle aged individuals (i.e., their parents). The results showed convergent and discriminant validity for life evaluations (global & averaged domain satisfaction), PA, and NA. Most important, the correlation between the life-evaluation factor and the affective balance factor was r = .90. While this correlation still leaves 20% unexplained variance in life-evaluations, it does suggest that the hedonic tone of life experiences strongly influences subjective life-evaluations. However, there are reasonable concerns that this correlation overestimates the importance of hedonic experiences. One problem is that judgments of hedonic tone over an extended period of time may be biased by life-evaluations. To address this concern it would be necessary to demonstrate that affect ratings are based on actual affective experiences rather than being inferred from life-evaluations.
Following a critical discussion of Diener’s SWB concept (Busseri & Sadava, 2011), Busseri tackled the issue empirically using the MIDUS data. To do so, Busseri (2015) examined how LS, PA, and NA are related to predictors of SWB. He explicitly examined which predictors may have a unique influence on life-satisfaction judgments above and beyond the influence of PA and NA. The main problem was that the chosen predictors had weak relationships with the well-being components. The main exception was the Intentional Living scale; that is, an average of ratings of how much effort respondents invest into work, finances, relationships, health, and life overall. This scale had a strong unique relationship with life-evaluations, b = .44, that was as strong as the unique effect of PA, b = .42, and stronger than the unique effect of NA, b = -.16. The study also replicated Kahneman et al.’s (2006) finding that income is a unique predictor of LS and unrelated to PA and NA, but even the effect of income is statistically small, b = .05. Using the published correlation matrix and correcting LS for unreliability, I found a correlation of r = .58 for LS and affective balance. The unique relationship after controlling for other predictors was r = .52, suggesting that most of the relationship between affective balance and life-satisfaction is direct and not spurious due to third variables that influence affective balance and life-satisfaction.
Payne and Schimmack (2022) followed up on Zou et al.’s (2013) study with a multiverse analysis. PA and NA were measured with different sets of items ranging from pure hedonic items (good, bad), happiness and sadness items, to models of PA and NA as higher order factors of several positive (joy, love, gratitude) and negative (anger, fear, sadness) affects (Diener et al., 1995). They also compared results for mono-method (only self-ratings) and multi-method (ratings by all three family members) measurement models. Finally, results were analyzed separately for students, mothers, and fathers as targets. They key finding was that item selection had a very small influence, whereas the comparison of mono-method and multi-method studies made a bigger difference. The mono-method results ranged from r = .64, 95%CI = .58 to .71 to r = .69, 95%CI = .63 to .75. The multi-method results ranged from r = .71, 95%CI = .62 to .81, to r = .86, 95%CI = .80 to .92. These estimates are somewhat lower than Zou et al.’s (2013) results and suggest that the true relationship is less than r = .9.
In Study 2, Payne and Schimmack (2022) conducted the first direct comparison of PANAS items with hedonic tone items using an online sample. They found that PANAS NA was virtually identical with other NA measures. This refutes the interpretation of PANAS NA as a measure of negative activation that is distinct from hedonic tone. However, PANAS PA was distinct from other PA measures and was a weaker predictor of life-evaluations. A latent variable model with the PANAS items produced a correlation of r = .78, 95%CI = .73 to .82. An alternative measure that focusses on hedonic tone, the Scale of Positive and Negative Experiences (SPANE, Diener & Bieswas-Diener, 2009) yielded a slightly stronger correlation, r = .83, 95% .79 to .86. In a combined model, the SPANE PA factor was a stronger predictor than the PANAS PA factor. Thus, PANAS scales are likely to underestimate the contribution of affect to life-evaluations, but the difference is small. The correlations might be stronger than in other studies due to the use of an online sample.
To summarize, correlations between affective balance and life-evaluations range from r = .5 to r = .9. Several methodological factors contribute to this variation, and studies that use more valid PA and NA scales and control for measurement error produce stronger correlations. In addition, culture can moderate this relationship but it is not clear whether culture influences response styles or actual differences in the contribution of affect to life-evaluations. A reasonable estimate of the true correlation is r = .7 (+/- .2), which suggests that about 50% of the variance in life-evaluations is accounted for by variation in the hedonic tone of everyday experiences. An important direction of future research is to identify the unique predictors of life-evaluations that explain the remaining variance in life-evaluations. Hopefully, it will not take another 60 years to get a better understanding of the determinants of individuals’ life-evaluations. A better understanding of life-satisfaction judgments is crucial for the construct validation of life-satisfaction judgments before they can be used to make claims about nations’ well-being and to make public policy recommendations.