Category Archives: Satisfaction with Life Scale

Construct Validity of the Satisfaction with Life Scale

With close to 10,000 citations in WebofScience, Ed Diener’s article that introduced the “Satisfaction with Life Scale” (SWLS) is a citation classic in well-being science. While single-item measures are used in large national representative surveys (e.g., General Social Survey, German Socio-Economic Panel, World Value Survey), psychologists prefer multi-item scales because they have higher reliability and therewith also higher validity.

Study 1 in Diener et al. (1985) demonstrated that the SWLS shows convergent validity with single-item measures like Cantril’s ladder, r = .62, .66), and Andrews and Withey’s Delighted-Terrible scale, r = .68, .62. Attesting to the higher reliability of the 5-item SWLS is the finding that the internal consistency was .87 and the retest reliability was r = .82. These results suggest that the SWLS and single-item measures measure a single construct with different amounts of random measurement error.

The important question for well-being scientists who use the SWLS and other global well-being measures is whether these items measure what they are intended to measure. To answer this question, we need to know what life-satisfaction measures are intended to measure.

Diener et al. (1985) draw on Andrews and Withey’s (1976) model of well-being perceptions. Accordingly, life-satisfaction judgments are based on subjective evaluations of important concerns.

Judgments of satisfaction are dependent upon a comparison of one’s circumstances with what is thought to be an appropriate standard. It is important to point out that the judgment of how satisfied people are with their present state of affairs is based on a comparison with a standard which each individual sets for him· or herself; it is not externally imposed. It is a hallmark of the subjective well-being area that it centers on the person’s own judgments, not upon some criterion which is judged to be important by the researcher (Diener, 1984).

This definition of life-satisfaction makes two important points. First, it is assumed that respondents are thinking about their circumstances when they judge their life-satisfaction. That is, we we can think about life-satisfaction as an attitude with an individual’s life as the attitude object. Just like individuals are assumed to think about the important features of Coca Cola when they are asked to report their attitudes towards Coca Cola, respondents are assumed to think about the important features of their lives, when they report their attitudes towards their lives.

The second part of the definition makes it clear that attitudes towards lives are based on subjectively chosen criteria to evaluate lives. Just like individuals may like the taste of Coke or dislike the taste of Coke, the same life circumstance can be evaluated differently by different individuals. Some may be extremely satisfied with an income of $100,000 and some may be extremely dissatisfied with the same income. For students, some students may be happy with a GPA of 2.9, others may be unhappy with the same GPA. The reason is that the evaluation criteria or standards can very across individuals and that there is no objective criterion that is used to evaluate life circumstances. This makes life-satisfaction judgments an indicator of subjective well-being.

The reliance on subjective evaluation criteria also implies that individuals can give different weights to different life domains. For some people, family life may be the most important domain, for others it may be work (Andrews & Withey, 1976). The same point is made by Diener et al. (1985).

For example, although health, energy, and so forth may be desirable, particular individuals may place different values on them. It is for this reason that ,we need to ask the person for their overall evaluation of their life, rather than summing across their satisfaction with specific domains, to obtain a measure of overall life-satisfaction (p. 71).

This point makes sense. If life-satisfaction judgments on evaluations of life circumstances and individuals place different emphasis on different life domains, more important domains should have a stronger influence on global life-satisfaction judgments (Schimmack, Diener, & Oishi, 2002). However, starting with Andrews and Withey (1976), empirical tests of this prediction have failed to confirm it. When individuals are asked to rate the importance of life domains, and these weights are used to compute a weighted average, the weighted average is not a better predictor of global judgments than a simple unweighted average (Rohrer & Schmukle, 2018).

Although this fact has been known since 1974, its theoretical significance has been ignored. There are two possible interpretations of this finding. On the one hand, it could be that importance ratings are invalid. That is, people don’t really know what is important to them and the actual importance is best revealed by the regression weights when global life-satisfaction ratings are regressed on domain satisfaction either across participants or within-participants over time. The alternative explanation is more troubling. In this case, global life-satisfaction judgments are invalid. Maybe these judgments are not based on subjective evaluations of life-circumstances.

Schwarz and Strack (1999) made the point that global life-satisfaction judgments are based on quick heuristics that produce invalid information. The problem of their criticism is that they focused on unstable sources such as mood or temporarily accessible information as the main sources of life-satisfaction judgments. This model fails to explain the high temporal stability of life-satisfaction judgments. (Schimmack & Oishi, 2005).

However, it is possible that stable factors produce systematic method variance in life-satisfaction judgments. For example, Andrews and Withey (1976) suggested that halo bias could influence ratings of domain satisfaction and life-satisfaction. They used informant ratings to rule out this possibility, but their test of this hypothesis was statistically flawed (Schimmack, 2019). Thus, it is possible that a substantial portion of the reliable variance in SWLS scores is halo bias.

Diener et al. (1985) tried to address the problem of systematic measurement error in two ways. First, they included the Marlowe-Crowne Social Desirability (MCSD) scale to measure social desirable responding and found no correlation with SWLS scores, r = .02. The problem is that the MCSD is not a valid measure of socially desriable responding or halo bias, but rather a measure of agreeableness and conscientiousness. Thus, the correlation is better interpreted as evidence that life-satisfaction is fairly independent of these personality traits. Second, Study 3 with 53 elderly residents of Urbana-Champaign included an interview with two trained interviewers. Afterwards, the interviewers made ratings of the interviewees’ well-being. The averaged interviewer’ ratings correlated r = .43 with the self-ratings of well-being. The problem here is that individuals who are motivated to present a positive image in their SWLS ratings are also likely to present a positive image in an interview. Moreover, the conveyed sense of well-being could reflect individuals’ personality more than their life-circumstances. Thus, it is not clear how much of the agreement between self-ratings and interviewer-ratings reflects evaluations of actual life-circumstances.

The most recent review article by Ed Diener was published last year; “Advances and Open Questions in the Science of Subjective Well-Being” (Diener, Lucas, & Oishi, 2018). The article makes it clear that the construct has not changed since 1985.

Subjective well-being (SWB) reflects an overall evaluation of the quality of a person’s life from her or his own perspective” (p. 1).

As the term implies, SWB refers to the extent to which a person believes or feels that his or her life is going well. The descriptor “subjective” serves to define and limit the scope of the construct: SWB researchers are interested in evaluations of the quality of a person’s life from that person’s own perspective.” (p. 2)

The authors also explicitly state that subjective well-being measures are subjective because individuals can focus on different aspects of their lives depending on their importance to them.

it is the subjective nature of the construct that gives it its power. This is due to the fact that different people likely weight different objective circumstances differently depending on their goals, their values, and even their culture” (p. 3).

The fact that global measures allow individuals to assign different weights to different domains is seen as a strength.

Presumably, subjective evaluations of quality of life reflect these idiosyncratic reactions to objective life circumstances in ways that alternative approaches (such as the objective list
approach) cannot. Thus, when evaluating the impact of events, interventions, or public-policy decisions on quality of life, subjective evaluations may provide a better mechanism for assessment than alternative, objective approaches
(p. 3).

The problem is that this claim requires empirical evidence to show that global life-satisfaction judgments are indeed more valid measures of subjective well-being than simple averages because they properly weigh information in accordance with individuals’ subjective preferences, and since 1976 this evidence has been lacking.

Diener et al.’s (2018) review glosses over this glaring problem for the construct validity of the SWLS and other global well-being measures.

Because most measures are simple self-reports, considerable research addresses the psychometric properties of these types of assessments. This research consistently shows that existing self-report measures exhibit strong psychometric properties including high internal consistency when multiple-item measures are used; moderately strong test-retest reliability, especially over short periods of time; reasonable convergence with alternative measures (especially those that have also been shown to have high levels of reliability and validity); and theoretically meaningful patterns of associations with other constructs and criteria (see Diener et al., 2009, and Diener, Inglehart, & Tay, 2013, for reviews). There is little debate about the quality of SWB measures when evaluated using these traditional criteria.

While it is true that there is little debate, this does not mean that there is strong evidence for the construct validity of the SWLS. The open question is how much respondents are really conducting a memory search for information about important life domains, evaluate these domains based on subjective criteria, and then report an overall summary of these evaluations. If so, subjective importance weights should improve predictions, but they often do not. Moreover, in regression models individual life domains often contribute small amounts of unique variance (Andrews & Withey, 1976), and some important aspects like health often account for close to zero percent of the variance in life-satisfaction judgments.

Convergent Validity

One key feature of construct validity is convergent validity between two independent methods that measure the same construct (Campbell & Fiske, 1959). Ideally, multiple methods are used and it is possible to examine whether the pattern of correlations matches theoretical predictions (Cronbach & Meehl, 1955; Schimmack, 2019). Diener et al. (2018) mention some evidence of convergent validity.

For example, Schneider and Schimmack (2009) conducted a meta-analysis of the correlation between self and informant reports, and they found that there is reasonable agreement (r = .42) between these two methods of assessing SWB.

The problem with this evidence is that the correlation between two measures only shows that both methods are valid, but it is not possible to quantify the amount of valid variance in self-ratings or informant ratings, which requires at least three methods (Andrews & Withey, 1976; Zou, Schimmack, & Gere, 2013). Theoretically, it would be possible that most of the variance in self-ratings is valid and that informant ratings are rather invalid. This is what Andrews and Withey (1976) claimed with estimates of 65% valid variance in self-ratings and 15% valid variance in informant ratings, with a correlation of r = .32. However, their model was incorrect and allowed for method variance in self-ratings to inflate the factor loading of self-ratings.

Zou et al. (2013) avoided this problem by using self-ratings and ratings by two informants as independent methods and found no evidence that self-ratings are more valid than informant ratings; a finding that is mirrored in ratings of personality traits (Anusic et al., 2009). Thus, a correlation of r = .3, implies that 30% of the variance in self-ratings is valid and 30% of the variance in informant ratings is valid.

While this evidence shows that self-ratings of life-satisfaction show convergent validity with informant ratings, it also shows that a substantial portion of the reliable variance in self-ratings is not shared with informants. Moreover, it is not clear what information produces agreement between self-ratings and informant ratings. This question has received surprisingly little attention, although it is critical for the construct validity of life-satisfaction judgments. Two articles have examined this question with opposite conclusions. Schneider and Schimmack (2010) found some evidence that satisfaction in important life domains contributed to self-informant agreement. This finding would support the bottom-up model of well-being judgments that raters are actually considering life circumstances when they make well-being judgments. In contrast, Dobewall, Realo, Allik, Esko, andMetspalu (2013) proposed that personality traits like depression and cheerfulness accounted for self-informant agreement. In this case, informants do not need ot know anything about life circumstances. All they need to know is whether an individual has a positive or negative lens to evaluate their lives. If informants are not using information about life circumstances, they cannot be used to validate self-ratings to show that self-ratings are based on evaluations of life circumstances.

Diener et al. (2018) cite a number of additional findings as evidence of convergent validity.

Physiological measures, including brain activity (Davidson, 2004) and hormones (Buchanan, al’Absi, & Lovallo, 1999), along with behavioral measures such as the amount of smiling (e.g., Oettingen & Seligman, 1990; Seder & Oishi, 2012) and patterns of online behaviors (Schwartz, Eichstaedt, Kern, Dziurzynski, Agrawal et al., 2013) have also been used to assess SWB. (p. 7).

This evidence has several limitations. First, hormones do not reflect evaluations and are at best indirectly related to life-evaluations. Asymmetries in prefrontal brain activity (Davidson, 2004) have been shown to reflect approach and avoidance motivation more than pleasure and displeasure, and brain activity is a better measure of momentary states than the evaluation of fairly stable life circumstances. Finally, they also may reflect individuals’ personality more than their life circumstances. The same is true for the behavioral measures. Most important, correlations with a single indicators do not provide information about the amount of valid variance in life-satisfaction judgments. To quantify validity it is necessary to examine these findings within a causal network (Schimmack, 2019).

Diener et al. (2019) agree with my assessment in their final conclusions about measurement of subjective well-being.

The first (and perhaps least controversial) is that many open questions remain
regarding the associations among different SWB measures and the extent to which these measures map on to theoretical expectations; therefore, understanding how the measures relate and how they diverge will continue to be one of the most important goals of research in the area of SWB. Although different camps have emerged that advocate for one set of measures over others, we believe that such advocacy is premature. More research is needed about the strengths, weaknesses, and relative merits of the various approaches to measurement that we have documented in this review
(p. 7).

The problem is that well-being scientists have made no progress on this front since Andrews and Withey (1976) conducted the first thorough construct validation studies. The reason is that social and personality psychology suffers from a validation crisis (Schimmack, 2019). Researchers simply assume that measures are valid rather than testing it or they use necessary, but insufficient criteria like internal consistency (alpha), retest reliability as evidence. Moreover, there is a tendency to ignore inconvenient findings. As a result, 40 years after Andrews and Withey’s (1976) seminal article was published, it remains unclear (a) whether respondents aggregate information about important life domains to make global judgments, (b) how much of the variance in life-satisfaction judgments is valid, and (c) which factors produce systematic biases in life-satisfaction judgments that may lead to false conclusions about the causes of life-satisfaction and to false policy recommendations.

Health is probably the best example to illustrate the importance of valid measurement of subjective well-being. It makes intuitive sense that health has an influence on well-being. Illness often disables individuals from pursuing their goals and enjoying life as everybody who had the flu knows. Diener et al. (2018) agree.

“One life circumstance that might play a prominent role in subjective well-being is a person’s health” (p. 15).

It is also difficult to see how there could be dramatic individual differences in the criteria that are used to evaluate health. Sure, fitness levels may be a matter of personal preference, but nobody is enjoying a stroke, heart attack, or cancer, or even having the flu.

Thus, it was a surprising finding that health seemed to have a small influence on global well-being judgments.

“Initial research on the topic of health conditions often concluded that health played only a minor role in wellbeing judgments (Diener et al., 1999; Okun, Stock, Haring,
& Witter, 1984).”

More problematic was the finding that subjective evaluations of health seemed to play no role in these judgments in multivariate analyses that controlled for shared variance among ratings of several life domains. For example, in Andrews and Withey’s (1976) studies satisfaction with health contributed only 1% unique variance in the global measure.

In contrast, direct importance ratings show that health is rated as the second most important domain (Rohrer & Schmukle, 2018).

Thus, we have to conclude that health doesn’t seem to matter for people’s subjective well-being. Or we can conclude that global measures are (partially) invalid measures because respondents do not weigh life domains in accordance with their importance. This question clearly has policy relevance as health care costs are a large part of wealthy nations’ GDP and financing health care is a controversial political issue, especially in the United States. Why would this be the case, if health is actually not important for well-being. We could argue that it is important for life expectancy (Veenhoven’s happy life-years) or that it matters for objective well-being, but not for subjective well-being, but clearly the question why health satisfaction plays a small role in global measures of subjective well-being is an important one. The problem is that 40 years of well-being science have passed without addressing this important question. But as they say, better late than never. So, let’s get on with it and figure out how responses to global well-being questions are made and whether these cognitive processes are in line with the theoretical model of subjective well-being.

Thinking Too Fast About Life-Satisfaction Judgments

In 2002, Daniel Kahneman was awarded the Nobel Prize for Economics.   He received the award for his groundbreaking work on human irrationality in collaboration with Amos Tversky in the 1970s. 

In 1999, Daniel Kahneman was the lead editor of the book “Well-Being: The foundations of Hedonic Psychology.”   Subsequently, Daniel Kahneman conducted several influential studies on well-being. 

The aim of the book was to draw attention to hedonic or affective experiences as an important, if not the sole, contributor to human happiness.  He called for a return to Bentham’s definition of a good life as a life filled with pleasure and devoid of pain a.k.a displeasure. 

The book was co-edited by Norbert Schwarz and Ed Diener, who both contributed chapters to the book.  These chapters make contradictory claims about the usefulness of life-satisfaction judgments as an alternative measure of a good life. 

Ed Diener is famous for his conception of wellbeing in terms of a positive hedonic balance (lot’s of pleasure, little pain) and high life-satisfaction.   In contrast, Schwarz is known as a critic of life-satisfaction judgments.  In fact, Schwarz and Strack’s contribution to the book ended with the claim that “most readers have probably concluded that there is little to be learned from self-reports of global well-being” (p. 80).   

To a large part, Schwarz and Strack’s pessimistic view is based on their own studies that seemed to show that life-satisfaction judgments are influenced by transient factors such as current mood or priming effects.

the obtained reports of SWB are subject to pronounced question-order- effects because the content of preceding questions influences the temporary accessibility of relevant information” (Schwarz & Strack, p. 79). 

There is only one problem with this claim; it is only true for a few studies conducted by Schwarz and Strack.  Studies by other researchers have produced much weaker and often not statistically reliable context effects (see Schimmack & Oishi, 2005, for a meta-analysis). 
In fact, a recent attempt to replicate Schwarz and Strack’s results in a large sample of over 7,000 participants failed to show the effect and even found a small, but statistically significant effect in the opposite direction (ManyLabs2).   

Figure 1 summarizes the results of the meta-analysis from Schimmack and Oishi 2005), but it is enhanced by new developments in meta-analysis. The blue line in the graph regresses effect sizes (converted into Fisher-z scores) onto sampling error (1/sqrt(N -3). Publication bias and other statistical tricks produce a correlation between effect size and sampling error. The slope of the blue line shows clear evidence of publication bias, z = 3.85, p = .0001. The intercept (where the line meets zero on the x-axis) can be interpreted as a bias-corrected estimate of the real effect size. The value is close to zero and not statistically significant, z = 1.70, p = .088. The green line shows the effect size in the replication study, which was also close to zero, but statistically significant in the opposite direction. The orange vertical red line shows the average effect size without controlling for publication bias. We see that this naive meta-analysis overestimates the effect size and falsely suggests that item-order effects are a robust phenomenon. Finally, the graph highlights the three results from studies by Strack and Schwarz. These results are clear outliers and even above the biased blue regression line. The biggest outlier was obtained by Strack et al. (1991) and this is the finding that is featured in Kahneman’s book, even though it is not reproducible and clearly inflated by sampling error. Interestingly, sampling error is also called noise and Kahneman wrote a whole new book about the problems of noise in human judgments.

While the figure is new, the findings were published in 2005, several years before Kahneman wrote his book “Thinking Fast and Slow). He was simply to lazy to use the slow process of a thorough literature research to write about life-satisfaction judgments. Instead, he relied on a fast memory search that retrieved a study by his buddy. Thus, while the chapter is a good example of biases that result from fast information processing, it is not a good chapter to tell readers about life-satisfaction judgments.

To be fair, Kahneman did inform his readers that he is biased against life-satisfaction judgments.  Having come to the topic of well-being from the study of the mistaken memories of colonoscopies and painfully cold hands, I was naturally suspicious of global satisfaction with life as a valid measure of well-being (Kindle Locations 6796-6798). Later on, he even admits to his mistake.  Life satisfaction is not a flawed measure of their experienced well-being, as I thought some years ago. It is something else entirely (Kindle Location 6911-6912)

However, insight into his bias was not enough to motivate him to search for evidence that may contradict his bias. This is known as confirmation bias. Even ideal-prototypes of scientists like Nobel Laureates are not immune to this fallacy. Thus, this example shows that we cannot rely on simple cues like “professor at Ivy League,” “respected scientists,” or “published in prestigious journals.” to trust scientific claims. Scientific claims need to be backed up by credible evidence. Unfortunately, social psychology has produced a literature that is not trustworthy because studies were only published if they confirmed theories. It will take time to correct these mistakes of the past by carefully controlling for publication bias in meta-analyses and by conducting pre-registered studies that are published even if they falsify theoretical predictions. Until then, readers should be skeptical about claims based on psychological ‘science,’ even if they are made by a Nobel Laureate.