Science is self-correcting: JPSP-PPID is not

With over 7,000 citations at the end of 2021, Ryff and Keyes (1995) article is one of the most highly cited articles in the Journal of Personality and Social Psychology. A trend analysis shows that citations are still increasing with over 800 citations in the past two years.

Most of these citations are reference to the use of Ryff’s measure of psychological well-being that uncritically accept Ryff’s assertion that her PWB measure is a valid measure of psychological well-being. The abstract implies that the authors provided empirical support for Ryff’s theory of psychological well-being.

Contemporary psychologists contrast Ryff’s psychological well-being (PWB) with Diener’s (1984) subjective well-being (SWB). In an article with over 1,000 citations, Ryff and Keyes (2002) tried to examine how PWB and SWB are empirically related. This attempt resulted in a two-factor model that postulates that SWB and PWB are related, but distinct forms of well-being.

The general acceptance of this model shows that most psychologists lack proper training in the interpretation of structural equation models (Borsboom, 2006), although graphic representations of these models make SEM accessible to readers who are not familiar with matrix algebra. To interpret an SEM model, it is only necessary to know that boxes represent measured variables, ovals represent unmeasured constructs, directed straight arrows represent an assumption that one construct has a causal influence on another construct, and curved bidrectional arrows imply an unmeasured common cause.

Starting from the top, we see that the model implies that an unmeasured common cause produces a strong correlation between two unmeasured variables that are labelled Psychological Well-Being and Subjective Well-Being. These labels imply that the constructs PWB and SWB are represented by unmeasured variables. The direct causal arrows from these unmeasured variables to the measured variables imply that PWB and SWB can be measured because the measured variables reflect the unmeasured variables to some extent. This is called a reflective measurement model (Borsboom et al., 2003). For example, autonomy is a measure of PWB because .38^2 = 14% of the variance in autonomy scores reflect PWB. Of course, this makes autonomy a poor indicator of PWB because the remaining 86% of the variance do not reflect the influence of PWB. This variance in autonomy is caused by other unmeasured influences and is called unique variance, residual variance, or disturbance. It is often omitted from SEM figures because it is assumed that this variance is simply irrelevant measurement error. I added it here because Ryff and users of her measure clearly do not think that 86% of the variance in the autonomy scale is just measurement error. In fact, the scale scores of autonomy are often used as if they are a 100% valid measure of autonomy. The proper interpretation of the model is therefore that autonomy is measured with high validity, but that variation in autonomy is only a poor indicator of psychological well-being.

Examination of the factor loadings (i.e., the numbers next to the arrows from PWB to the six indicators) shows that personal relationships has the highest validity as a measure of PWB, but even for personal relationships, the amount of PWB variance is only .66^2 = 44%.

In a manuscript (doc) that was desk-rejected by JPSP, we challenged this widely accepted model of PWB. We argued that the reflective model does not fit Ryff’s own theory of PWB. In a nutshell, Ryff’s theory of PWB is one of many list-theories of well-being (Sumner, 1996). The theory lists a number of attributes that are assumed to be necessary and sufficient for high well-being.

This theory of well-being implies a different measurement model in which arrows point from the measured variables to the construct of PWB. In psychometrics, these models are called formative measurement models. There is nothing unobserved about formative constructs. They are merely a combination of the measured constructs. The simplest way to integrate information about the components of PWB is to average them. If assumptions about importance are added, the construct could be a weighted average. This model is shown in Figure 2.

The key problem for this model is that it makes no predictions about the pattern of correlations among the measured variables. For example, Ryff’s theory does not postulate whether an increase in autonomy produces an increase in personal growth or a decrease in personal relations. At best, the distinction between PWB and SWB might imply that changes in PWB components are independent of changes in SWB components, but this assumption is highly questionable. For example, some studies suggest that positive relationships improve subjective well-being (Schimmack & Lucas, 2010).

To conclude, JPSP has published two highly cited articles that fitted a reflective measurement model to PWB indicators. In the desk-rejected manuscript, Jason Payne and I presented a new model that is grounded in theories of well-being and that treats PWB dimensions like autonomy and positive relations as possible components of a good life. Our model also clarified the confusion about Diener’s (1984) model of subjective well-being.

Ryff et al.’s (2002) two-factor model of well-being was influenced by Ryan and Deci’s (2001) distinction between two broad traditions in well-being research. “one dealing with happiness (hedonic well-being), and one dealing with human potential (eudaimonic well-being; Ryan &
Deci, 2001; see also Waterman, 1993)” (Ryff et al., 2002, p. 1007). We argued that this dichotomy overlooks another important distinction between well-being theories, namely the distinction between subjective and objective theories of well-being (Sumner, 1996). The key difference between objective and subjective theories of well-being is that objective theories aim to specify universal aspects of a good life that are based on philosophical analyses of the good life. In contrast, subjective theories reject the notion that universal criteria of a good life exist and leave it to individuals to create their own evaluation standards of a good life (Cantril., 1965). Unfortunately, Diener’s tripartite model of SWB is difficult to classify because it combines objective and subjective indicators. Whereas life-evaluations like life-satisfaction judgments are clearly subjective indicators, the amount of positive affect and negative affect implies a hedonistic conception of well-being. Diener never resolved this contradiction (Busseri & Sadava, 2011), but his writing made it clear that Diener stressed subjectivity as an essential component of well-being.

It is therefore incorrect to characterize Diener’s concept of SWB as a hedonic or hedonistic conception of well-being. The key contribution of Diener was to introduce psychologists to subjective conceptions of well-being and to publish the most widely used subjective measure of well-being, namely the Satisfaction with Life Scale. In my opinion, the inclusion of PA and NA in the tripartite model was a mistake because it does not allow individuals to choose what they want to do with their lives. Even Diener himself published articles that suggested positive affect and negative affect are not essential for all people (Suh, Diener, Oishi, & Triandis, 1998). At the very least, it remains an empirical question how important positive affect and negative affect are for subjective life evaluations and whether other aspects of a good life are even more important. At least, this question can be empirically tested by examining how much eudaimonic and hedonic measures of well-being contribute to variation in subjective measures of well-being. This question leads to a model in which life-satisfaction judgments are a criterion variable and the other variables are predictor variables.

The most surprising finding was that environmental mastery was a strong unique predictor and a much stronger predictor than positive affect or negative affect (direct effect, b = .66).

In our model, we also allowed for the possibility that PWB attributes influence subjective well-being by increasing positive affect or decreasing negative affect. The total effect is a very strong relationship, b = .78, with more than 50% of the variance in life-satisfaction being explained by a single PWB dimension, namely environmental mastery.

Other noteworthy findings were that none of the other PWB attribute made a positive (direct or indirect) contribution to life-satisfaction judgments. Autonomy even was a negative predictor. The effects of positive affect and negative affect were statistically significant, but small. This suggests that PA and NA are meaningful indicators of subjective well-being because the reflect a good life, but provide no evidence for hedonic theories of well-being that suggest positive affect increases well-being no matter how it is elicited.

These results are dramatically different from the published model in JPSP. In that model an unmeasured construct, SWB, causes variation in Environmental Mastery. In our model, environmental mastery is a strong cause of the only subjective indicator of well-being, namely life-satisfaction judgments. Whereas the published model implies that feeling good makes people have environmental mastery, our model suggests that having control over one’s life increases well-being. Call us crazy, but we think the latter model makes more sense.

So, why was our ms. desk rejected without peer-review from experts in well-being research? I post the full decision letter below, but I want to highlight the only comment about our actual work.

A related concern has to do with a noticeable gap between your research question, theoretical framework, and research design. The introduction paints your question in broad strokes only, but my understanding is that you attempt to refine our understanding of the structure of well-being, which could be an important contribution to the literature. However, the introduction does not provide a clear rationale for the alternative model presented. Perhaps even more important, the cross-sectional correlational study of one U.S. sample is not suited to provide strong conclusions about the structure of well-being. At the very least, I would have expected to see model comparison tests to compare the fit of the presented model with those of alternative models. In addition, I would have liked to see a replication in an independent sample as well as more critical tests of the discriminant validity and links between these factors, perhaps in longitudinal data, through the prediction of critical outcomes, or by using behavioral genetic data to establish the genetic and environmental architecture of these factors. Put another way, independent of the validity of the Ryff / Keyes model, the presented theory and data did not convince me that your model is a better presentation of the structure of well-being.

Bleidorn’s comments show that even prominent personality researchers lack basic understanding of psychometrics and construct validation. For example, it is not clear how longitudinal data can provide answers to questions about construct validity. Examining change is of course useful, but without a valid measure of a construct it is not clear what change in scale scores means. Construct validation precedes studies of stability and change. Similarly, it is only relevant to examine nature and nurture questions with a clear phenotype. Bleidorn completely ignores our distinction between hedonic and subjective well-being and the fact that we are the first to examine the relationship between PWB attributes and life-satisfaction.

As psychometricians have pointed out, personality psychologists often ignore measurement questions and are often content with averaged self-report ratings as operationalized constructs that do not require further validation. We think that this blind empiricism is preventing personality psychology from making real progress. It is depressing to see that even the new generation of personality psychologists shows no interest in improving construct validity of foundational constructs. Fortunately, JPSP-PPID publishes only about 50 articles a year and there are other outlets to publish our work. Unfortunately, JPSP has a reputation to publish only the best work, but this is prestige is not warranted by the actual quality of published articles. For example, the obsession with longitudinal data is not warranted given evidence that about 80% of the variance in personality measures is stable trait variance that does not change. Repeatedly measuring this trait variance does not add to our understanding of stable traits.

Conclusion

To conclude, JPSP has published two cross-sectional articles of the structure of well-being that continue to be highly cited. We find major problems with the models in these articles, but JPSP is not interested in publishing a criticism of these articles. To reiterate, the main problem is that Diener’s SWB model is treated as if it is an objective hedonic theory of well-being, when the core aspect of the model is that well-being is subjective and not objective. We thought at least the main editor Rich Lucas, a former Diener student, would understand this point, but expectations are the mother of disappointment. Of course, we could be wrong about some minor or major issues, but the lack of interest in these foundational questions shows just how far psychology is from being a real science. A real science develops valid measures before it examines real questions. Psychologists invent measures and study their measures without evidence that their measures reflect important constructs like well-being. Not surprisingly, psychology has produced no consensual theory of well-being that could help people live better lives. This does not stop psychologists from making proclamations about ways to lead a happy or good life. The problem is that these recommendations are all contingent on researchers’ preferred definition of well-being and the measures associated with that tradition/camp/belief system. In this way, psychology is more like (other) religions and less like a science.

Decision Letter

I am writing about your manuscript “Two Concepts of Wellbeing: The Relation Between Psychological and Subjective Wellbeing”, submitted for publication in the Journal of Personality and Social Psychology (JPSP). I have read the manuscript carefully myself, as has the lead Editor at JPSP, Rich Lucas. We read the manuscript independently and then consulted with each other about whether the manuscript meets the threshold for full review. Based on our joint consultation, I have made the decision to reject your paper without sending it for external review. The Editor and I shared a number of concerns about the manuscript that make it unlikely to be accepted for publication and that reduce its potential contribution to the literature. I will elaborate on these concerns below. Due to the high volume of submissions and limited pages available to JPSP, we must limit our acceptances to manuscripts for which there is a general consensus that the contribution is of an important and highly significant level. 
 

  1. Most importantly, papers that rely solely on cross-sectional designs and self-report questionnaire techniques are less and less likely to be accepted here as the number of submissions increases. In fact, such papers are almost always rejected without review at this journal. Although such studies provide an important first step in the understanding of a construct or phenomenon, they have some important limitations. Therefore, we have somewhat higher expectations regarding the size and the novelty of the contribution that such studies can make. To pass threshold at JPSP, I think you would need to expand this work in some way, either by using longitudinal data or or by going further in your investigation of the processes underlying these associations. I want to be clear; I agree that studies like this have value (and I also conduct studies using these methods myself), it is just that many submissions now go beyond these approaches in some way, and because competition for space here is so high, those submissions are prioritized.
  2. A related concern has to do with a noticeable gap between your research question, theoretical framework, and research design. The introduction paints your question in broad strokes only, but my understanding is that you attempt to refine our understanding of the structure of well-being, which could be an important contribution to the literature. However, the introduction does not provide a clear rationale for the alternative model presented. Perhaps even more important, the cross-sectional correlational study of one U.S. sample is not suited to provide strong conclusions about the structure of well-being. At the very least, I would have expected to see model comparison tests to compare the fit of the presented model with those of alternative models. In addition, I would have liked to see a replication in an independent sample as well as more critical tests of the discriminant validity and links between these factors, perhaps in longitudinal data, through the prediction of critical outcomes, or by using behavioral genetic data to establish the genetic and environmental architecture of these factors. Put another way, independent of the validity of the Ryff / Keyes model, the presented theory and data did not convince me that your model is a better presentation of the structure of well-being.
  3. The use of a selected set of items rather than the full questionnaires raises concerns about over-fitting and complicate comparisons with other studies in this area. I recommend using complete questionnaires and – should you decide to collect more data – additional measures of well-being to capture the universe of well-being content as best as you can. 
  4. I noticed that you tend to use causal language in the description of correlations, e.g. between personality traits and well-being measures. As you certainly know, the data presented here do not permit conclusions about the temporal or causal influence of e.g., neuroticism on negative affect or vice versa and I recommend changing this language to better reflect the correlational nature of your data.     

In closing, I am sorry that I cannot be more positive about the current submission. I hope my comments prove helpful to you in your future research efforts. I wish you the very best of luck in your continuing scholarly endeavors and hope that you will continue to consider JPSP as an outlet for your work.


Sincerely,
Wiebke Bleidorn, PhD
Associate Editor
Journal of Personality and Social Psychology: Personality Processes and Individual Differences

1 thought on “Science is self-correcting: JPSP-PPID is not

  1. These editors and reviewers think their shit doesn’t smell.any more pompous and they’d be walking around in togas with tiaras made of ivy.

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