Studying personality stability and change is easy and hard. It is easy because the method is straightforward. Administer a valid measure of personality to a group of participants and repeat the measurement several times. Describing the method takes a sentence or two compared to pages that describe an intricate laboratory experiment with an elaborate deception. It is hard because it requires time and participants may drop out of a study. Meanwhile there is nothing to publish while a researcher is waiting for the next retest. In our fast paced world of academic publishing where researchers are expected to publish 5 or more articles a year, there is no place for slow research. As a result, evidence on personality change is scarce. The best evidence so far comes from a meta-analysis that patched together small studies with different measures, populations, and small samples. Although this meta-analysis is the best evidence available, it cannot be trusted because the evidence is inconclusive.

Psychologists have to thank economists and sociologists who are used to collaborate on big data collections. One of these collaborations is the German Socio-Economic Panel (SOEP). The SOEP is an ongoing longitudinal study with a representative sample that started in 1984. In 2005, the SOEP included the BFI-S; a 15-item personality measure that assesses the Big Five. Since then, the BFI-S has been administered in four-year intervals in 2009, 2013, and 2017. Thus, we now have longitudinal data spanning 12-years with four waves of data. This makes it possible to revisit the question of personality stability with much better data than a meta-analysis of heterogeneous studies can provide. Surely, the results are based on a German sample, but there is little evidence that personality development varies across cultures.

Method

One drawback of the SOEP is that each personality dimension is measured with just three items. This makes scale scores unreliable and scale scores can be contaminated with method variance (e.g., evaluative bias, acquiescence bias). To avoid these problems and to examine measurement invariance, it is better to analyze the data with a measurement model that examines personality change at the level of latent variables that correct for measurement error. I developed a measurement model for the SOEP (Schimmack, 2019a) and I already demonstrated invariance across the first three waves of the SOEP (Schimmack, 2019b). Here I added the fourth wave of data from 2017 to the dataset to produce even better information about long-term changes in personality.

To analyze the data, I first fitted the measurement model for the BFI-S to the data from each wave and imposed equality constraints to ensure measurement invariance. The longitudinal stability of personality was examined using the latent-trait-state (LTS) model that decomposes stability over time into two components; (a) a stable trait component that never changes and (b) a changing state component. The changing state component allows for factors that influence personalty to change over time and to change personality. These changing factors may produce changes that last a long time or changes that are more temporary. The time course of changes in personality is modeled with an autoregressive parameter that reflects how many of the changes at time 1 are still present at time 2.

The LTS model is typically fitted without modeling mean level changes. However, the model can also be used to model the mean structure in the data. In latent variable models, changes in personality are assumed to occur at the level of the latent traits, while item means (intercepts) are assumed to be constant over time. As the latent trait is stable, it cannot be used to model mean-level changes. Thus, one option is to free the means of the state factors. However, the influence of the state factors decreases over time, which is inconsistent with the idea of lasting changes in personality. Thus, a better option is to let the means of the occasion specific factors to vary freely, even if the occasion specific variance is zero. Although this model may lack realism, it would show the pattern of mean level changes in the data without imposing some model on the data (e.g., a linear trend).

The model specification and the complete results can be found on OSF (ttps://osf.io/vpcfd/). The overall model fit was acceptable, CFI = .971, RMSEA = .019, SRMR = .031.

Rank-order Stability and Change

A study of the first three waves in the SOEP replicated earlier findings of high retest stability in personality with stabilities over .9 over a one-year period (Conley, 1984; Schimmack, 2019c). However, three ways are insufficient to separate trait variance from state variance, and few studies with four waves of personality are available. Anusic and Schimmack (2016) used a meta-analytic approach to do so on the basis of smaller studies. Their model suggested that about 70% of the reliable variance in personality is trait variance and that the remaining 30% state variance are rather unstable with a low annual stability of .3. This would suggest that any changes in personality do not last long and individuals quickly revert back to their trait level of personality.

Table 1 shows the results for the SOEP data.

	Trait	Stability	1Y-Stability
Neuroticism	0.67	0.38	0.79
Extraversion	0.74	0.36	0.77
Openness	0.71	0.38	0.79
Agreeableness	0.69	0.18	0.65
Conscientiousness	0.64	0.24	0.70
Halo	0.64	0.31	0.75
Acquiescence	0.32	0.10	0.56

The results show a similar split between trait and state variance as the meta-analysis, with about two-thirds of the variance being trait variance and one-third being state variance. A new finding is that the halo factor, an evaluative bias in personality ratings, also has 60% trait variance. Thus, this response style can also be considered a stable trait. In contrast, acquiescence bias has less trait variance and seems to be more influenced by momentary factors that are inconsistent over time.

The results for the stability of the state variance are different from the meta-analysis. The SOEP data suggest that changes in personality are more persistent than the meta-analysis suggested. The annual stability estimates are around .7. Thus, any changes that are evident at time 2 would still be evident over the next years. The stability over 4-years is around .3. These results are more encouraging for researchers who are interested in personality change than the meta-analytic results in Anusic and Schimmack, 2016). Nevertheless, the relatively small amount of state variance and the high stability of the state variance imply that it takes time to find even small changes in personality. Not surprisingly, it has been difficult to uncover predictors of personality change even in large samples like the SOEP (Specht et al., 2011).

In sum, the results confirm that personality ratings are highly stable over extended periods of time and that a large portion of this stability is caused by stable factors that ensure persistent individual differences in personality over the life span.

Mean Levels

Table 2 shows the results for the mean levels. Means in the first year, 2005, are used as the reference group. The results provide little evidence for personalty change in adulthood. None of the Big Five dimensions shows a consistent trend over time. The results for conscientiousness are most important because a meta-analysis suggested that conscientiousness increases substantially throughout adulthood. There is no evidence for such a trend in the SOEP.

	N	E	O	A	C
2005	0.00	0.00	0.00	0.00	0.00
2009	-0.13	-0.12	-0.16	-0.18	-0.07
2013	-0.18	-0.03	-0.04	-0.08	-0.06
2017	-0.16	-0.06	-0.05	-0.11	-0.26

The general pattern of decreases for all five dimensions suggests that acquiescence bias might have changed over time. Thus, I also fitted a model with free means for acquiescence bias but the results did not change. Thus, it does not account for the small decrease in the Big Five. Adding means for the halo factor, instead, reduces changes for most scales, but would suggest a stronger decrease in neuroticism. However, the pattern is never a gradual change, but a drop from time 1 to time 2 with no major changes afterwards. This suggests that some panel effect or period effects have small effects on personality ratings, but there is no evidence to support the claim that personality systematically changes throughout adulthood.

Conclusion

Personality research was attacked by situationists who claimed that personality is a mere social construction. In the 1980s, personality researchers had presented evidence that personality traits are real and stable using twin studies, multi-rater studies, and longitudinal studies. However, two meta-analysis by Roberts and colleagues suggested that personality exists but is less stable than personality psychologists assumed. These meta-analysis had a strong influence on personality psychology in the 2000s. They are featured in personality textbooks and often cited as evidence that personality still develops throughout adulthood. However, more recent evidence are more consistent with the view of personality as mostly stable throughout adulthood. Costa and McCrae famously compared personality to plaster. While it can be shaped and molded early on, it finally sets into a shape that can not be altered. Yes, there may be cracks here and there, but the overall shape is set. While this image may be too rigid, it is consistent with the evidence that even major life-events that occur during adulthood seem to have very little influence on personality (Specht et al., 2011).

The idea of personalty change is often coupled with the notion that personality develops and that there can be personal growth in adulthood. The problem with these notions is that it implies that there is a normative or desirable direction of personality change. For example, an increase in conscientiousness is seen as evidence of growing maturity. However, the measurement model that I used distinguishes between the denotative and connotative aspects of personality. Lazy is both descriptive and evaluative. However, evaluations are rooted in cultural norms and values. Why is it good to work as much as possible, to avoid mistakes at any costs? Should education and policies try to increase conscientiousness levels? Is there an optimal level? These are all very difficult questions that go well beyond the existing science of personality. Once we focus on the denotative aspect of personality, we see that some people work harder than others or that some people are more creative than others, and that these differences are fairly stable, without any evidence what causes this stability. Just like people differ in personality, they differ in other characteristics that have received more attention. Current culture aims towards greater acceptance of differences in sexual orientation, gender identity, body types, religion, etc. Maybe we should also include personalty traits there and let introverts be proud introverts and disagreeable people be proud disagreeable people. Maybe personality differences only exist because they were not a problem during human evolution or diversity is even an advantage that allows humans as a group to adapt to different circumstances. Thus, the strong evidence of personality stability is not necessary a problem that needs to be solved because there is normal personality. There is only normal variation in personality.