Abstract
The maturity principle posits that socially desirable personality traits, such as agreeableness, conscientiousness, and emotional stability, tend to increase across adulthood. This study examined whether this principle extends to social, emotional, and behavioral (SEB) skills by investigating age differences in a representative sample of N = 940 German adults (age range: 18–65, mean age = 43, SD = 14, 50 % female) using moderated non-linear factor analysis models and comparing them to age differences in Big Five traits in a demographically comparable sample. Additionally, we explored age-specific associations between SEB skills and life quality, measured by life satisfaction and self-rated health. Contrary to the widely accepted maturity principle, we found few corresponding age differences in SEB skills, whereas the expected age-related patterns were evident in Big Five traits. These results remained consistent regardless of the level of measurement invariance. Some skills showed lower mean levels in older adults, and skill variances differed with age. In conclusion, these findings suggest that the maturity principle known from the Big Five literature does not fully generalize to SEB skills. This cross-sectional study lays the groundwork for future longitudinal research on SEB skills and highlights the importance of considering individuals within context.
Plain Language Summary
The maturity principle proposes that, on average, people become more emotionally stable, organized and friendlier as they age. This has been studied for Big Five personality traits, but not for social, emotional, and behavioral (SEB) skills–capacities people can draw on when needed to regulate their emotions, maintain positive social relationships, and manage their goals. However, this principle has recently been criticized for being overly simplistic. We investigated whether the maturity principle applies to SEB skills in addition to Big Five traits. For this purpose, we examined age differences in two demographically representative German samples aged 18 to 65: one sample focused on SEB skills, the other on Big Five traits. Surprisingly, we found little support for the maturity principle in SEB skills, whereas it was more clearly observable in Big Five traits. While the desirable personality traits were higher in older than in younger adults, this pattern did not generalize to SEB skills. This divergence suggests that the maturity principle does not hold for SEB skills and they may develop differently from related personality traits, depending on context.
Evidence suggests that older individuals often display higher psychological maturity than their younger counterparts (Bleidorn et al., 2022; Soto et al., 2011). This normative development is characterized by a flourishing of socially desirable personality traits such as increasing emotional stability, conscientiousness, and agreeableness – a pattern often termed the ‘maturity principle’ of personality development (Caspi et al., 2005; Roberts & Nickel, 2021; Roberts et al., 2008). This development across adulthood is often seen as adaptive, as these traits are predictive of important life outcomes (Soto, 2019). Whereas the maturity principle refers to changes in people’s personality traits (i.e., their typical behavior), an open research question centers on how people’s ability to enact corresponding behaviors when a situation calls for it (i.e., their maximum behavior, or put simply, their skills). The present research used a cross-sectional quota-based sample of adults aged 18–65 approximating the German population to examine whether the maturity principle holds for social, emotional, and behavioral (SEB) skills from the BESSI framework (Soto et al., 2022). These are conceptually defined as functional capacities for behaviors when a situation calls for it. For instance, are people more capable of regulating their affect with age due to experience? This assumption is sometimes made because of lower neuroticism with age (Soto et al., 2011). To our knowledge, this is the first study pioneering the investigation of the maturity principle to SEB skills. Given the long time horizon necessary for collection longitudinal data on skills, this study serves as a critical first step in advancing sustained research in this field.
Social, Emotional, and Behavioral Skills
Building on prior research on skills, Soto et al. (2021, 2022) developed a novel framework for SEB skills and designed the Behavioral, Emotional, and Social Skills Inventory (BESSI) to measure them. This BESSI distinguishes five broad skill domains as functional capacities for behaviors: emotional resilience skills to regulate emotions, social engagement skills to actively engage with others, innovation skills to engage with new ideas, cooperation skills to maintain positive social relationships, and self-management skills to effectively pursue goals and complete tasks. Each skill domain comprises several skill facets – 32 in total – with two facets being compound skills (i.e., skills that load on more than one domain in factor analyses). Figure 1 shows the assignment of facets to domains for the German adaptation of the BESSI (BESSI-G) (Table S1 in the Supplemental Materials). Overview of social, emotional, and behavioral skills and their structure in BESSI-G. Note. German factor structure of the BESSI-G (reprinted from Lechner & Urban, 2025, p. 4). There are a few differences compared to the English version (Soto et al., 2022) concerning the assignment of the 32 facets to the five domains. Most importantly, only two instead of three facets are compound skills that load on more than one domain.
Each skill domain aligns closely with one of the Big Five personality traits, although it is argued that skills do not equal personality traits conceptually (Soto et al., 2021). While personality traits encompass typical patterns of behaviors, thoughts and feelings across time and relevant situations (i.e., tendencies), SEB skills characterize how well someone can perform the same in situations as required (i.e., functional capacities). This distinction underscores that skills are learnable and context-sensitive (Kautz et al., 2014; Soto et al., 2021). However, skills and traits might be either congruent or incongruent within an individual: A low trait level does not necessarily mean that an individual cannot exhibit the corresponding behaviors, but rather might feel inhibited or actually perform the behavior poorly (Paulhus & Martin, 1987). We argue that skills and personality traits complement each other instead of being mutually exclusive, with skills potentially capturing additional information to personality traits (Soto et al., 2024). For example, an individual who prefers spending time alone (being introverted) may well be able to behave sociably when faced with a situation that requires making connections with a new team member (i.e., low trait, high skill).
SEB Skills Across Lifespan
While much is known about age differences in personality traits (see following passages), there is less evidence on how skills develop across adolescence (OECD, 2021), and even less is known about age differences in specific SEB skills in adulthood. So far, only one study investigated such differences in individuals aged 12 to 19 (Feraco & Meneghetti, 2023). In the present study, we aim to extend the investigation of age differences in SEB skills to an adult sample. Based on the overlap between skills and traits (Soto et al., 2022), we hypothesized about age differences in SEB skills using findings on Big Five changes across the life span. In other words, our aim was to determine whether age differences in SEB skills align with the maturity principle.
Most studies have found higher levels of agreeableness and conscientiousness in older individuals in cross-sectional studies (Anusic et al., 2012; Soto et al., 2011). In longitudinal studies, these constructs increase across adulthood (Bleidorn et al., 2022). Because of the overlap of cooperation skills with agreeableness and self-management skills with conscientiousness, we expected higher levels of these skills in older adults.
While some cross-sectional studies demonstrated negative relations between neuroticism and age (Lehmann et al., 2013; Soto et al., 2011), another study found no such associations (Allemand et al., 2008). Longitudinal research widely accepts a declining trajectory of neuroticism throughout adulthood (Bleidorn et al., 2022), leading us to expect greater emotional resilience skills in older individuals.
Evidence for openness is mixed. While some studies report positive or negative age associations (Donnellan & Lucas, 2008; Soto et al., 2011), meta-analyses and cross-sectional data suggest a curvilinear, inverted U-shaped pattern across adulthood (Anusic et al., 2012; Bleidorn et al., 2022; Roberts et al., 2006). Based on this we hypothesized a similar age pattern for the innovation skills, that is, increases in young adulthood but decreases in later adulthood.
Findings on age differences in extraversion are inconsistent – some studies show positive, others negative, or no associations with age (Donnellan & Lucas, 2008; Srivastava et al., 2003). This discrepancy has been attributed to the differential development of the extraversion facets in longitudinal studies, with social vitality declining and social dominance increasing (Roberts et al., 2006). Given that social engagement skills emphasize socially assertive behaviors (see Table S1), we expected an increase with age. In summary, we hypothesized that most SEB skills would show positive associations with age, with the exception of innovation skills.
While domains are often aggregations of several facets and allow for parsimonious global descriptions of traits and skills, facets can better capture unique information (Danner et al., 2021). Previous research on personality has shown that looking at facets in addition to traits is important to fully understanding psychological constructs (Soto & John, 2012). In our study, examining age differences at the facet level provides a more precise understanding of SEB skills by showing which facets drive or mask patterns within each domain.
Associations With Life Quality
Given that skills are conceptualized as functional capacities, it is essential to examine their role in fundamental dimensions of life quality. In this study, we investigated life satisfaction and self-rated health as the most salient indicators for such an exploration. In addition, we explored how the relationships of SEB skills with life quality may vary with age. Understanding age-specific relations is crucial since the functionality of skills might change across the life span depending on individuals contextual demands (Baltes, 1987). For example, innovation skills might be more relevant for LS in younger adulthood, when career development is central, whereas emotional resilience could become more important in later adulthood due to age-related shifts in priorities and demands.
Life satisfaction (LS), a broad evaluation of one’s life, is the cognitive component of subjective well-being (Diener, 2000). High life satisfaction is linked to various life advantages, such as academic success (Antaramian, 2017), positive social relationships (Oishi et al., 2007), and better health (Steptoe, 2019). Building on evidence that SEB skills offer incremental validity beyond personality traits, particularly emotional resilience, social engagement, and self-management in relations to LS (Soto et al., 2024), we formulated hypotheses linking skills to LS. Additionally, we relied on verified associations between personality traits and LS. A recent meta-analysis reported moderate associations of LS with extraversion and neuroticism, weaker associations with agreeableness and conscientiousness, and nearly zero relations with openness (Anglim et al., 2020). Accordingly, we expected positive associations between all skills and LS, except for innovation.
Self-rated health (SRH) is widely accepted as a valid proxy of actual health status in social science because it robustly predicts mortality (Schnittker & Bacak, 2014) and is associated with several objective health measures (Hamplová et al., 2022). Evidence suggests that SRH is somewhat more crucial for subjective well-being than objective health measures (Ngamaba et al., 2017) and mainly reflects vitality (Au & Johnston, 2014). We hypothesized positive associations between emotional resilience, social engagement, and self-management skills and SRH, given previously established links between SRH and corresponding Big Five (neuroticism, extraversion, and conscientiousness, respectively) (Stephan et al., 2012, 2020). Due to mixed findings for agreeableness and openness (Goodwin & Engstrom, 2002; Löckenhoff et al., 2012), and their alignment with cooperation and innovation skills, we hypothesized these skills to show no significant relation to SRH.
The Present Study
In the present study, we investigated whether the maturity principle holds for SEB skills in adulthood. We used cross-sectional data from a validation process of the German version of the BESSI inventory (Lechner et al., 2022), a large sample with quotas for age, gender, and educational attainment to ensure adequate coverage of the German adult population in terms of these sociodemographic characteristics. Given the wide age range of our sample from 18 to 65 years, we first examined the measurement invariance of SEB skills across age (Meredith, 1993; Widaman & Reise, 1997), then analyzed age differences, and finally explored age-specific relationships of skills with life quality. In addition, we investigated age differences in Big Five traits using a demographically comparable sample collected within a similar time frame (Lechner et al., 2022) to assess whether these age differences align with those observed in SEB skills (not preregistered). Based on the maturity principle, we hypothesized higher levels of self-management, emotional resilience and cooperation and social engagement skills, but lower levels of innovation skills in older adults compared to younger adults.
Our research contributes to the skill literature in several ways. First, while previous research on skill-like constructs has relied on diverse frameworks and trait measures that assess what individuals typically do (Abrahams et al., 2019; OECD, 2021), we applied a specific skill approach, capturing skills as explicitly defined functional capacities (Lechner et al., 2022; Soto et al., 2022). Second, we examined the maturity principle – typically studied within the Big Five – in the context of specific SEB skills as novel constructs. This is particularly interesting given the current controversy surrounding the validity of the maturity principle (Klimstra & McLean, 2024). Third, using a demographically comparable sample to examine age differences in the Big Five allows us to contrast skills with traits and assess whether they show similar age differences or diverge due to their distinct psychological nature. Fourth, we extended previous research focused on adolescence (Feraco & Meneghetti, 2023) by investigating age differences in these skills during adulthood. Finally, we explored age-specific associations of skills with life quality. By analyzing both domains and facets, our study provides a more nuanced perspective than examining domains alone. We preregistered this study on OSF.
Method
Samples
Overall, a sample of N = 1,008 persons from Germany with an age range from 18 to 65 years was surveyed (Lechner et al., 2022). This skill sample had a quota based on age, gender and educational level, such that the sample distribution parallels the distribution of these characteristics in the German adult population. The final sample after screening out low-quality responses (Lechner et al., 2022) consisted of 940 participants (age: M = 43.34, SD = 13.86, 49.79 % female). Note that data on LS and SRH were only available for about half of the sample due to randomization.
To investigate age differences in Big Five traits, we used data from an independent sample aged 14 to 64 from two measurement occasions (N1 = 1,105, N2 = 566) approximately 1.5 months apart (T0 and T2 in Lechner et al., 2022). Importantly, the adult subsample (age: 20 to 64) had the same quota as our current skills sample. After data cleaning (i.e., excluding straightliners), we merged the data from two time points and restricted the age range to 18–64 to maximize comparability with the skill sample. The final trait sample consisted of 870 participants (age: M = 35.44, SD = 15.94, 55 % female). All respondents gave informed consent. Both datasets used in this study were provided by GESIS and are available in our OSF project.
Measures
Social, Emotional, and Behavioral Skills
The five broad SEB skill domains and the skill facets were measured with the German version of the Behavioral, Emotional, and Social Skills Inventory (BESSI-G) (Lechner et al., 2022; Soto et al., 2022). The BESSI-G comprises 192 items, each of which asks respondents to rate how well they can do a certain task or activity (skill approach) instead to give information on the extent to which they agree or disagree with statements (personality approach). Each skill facet is measured by six items, while most skill domains except self-management and social engagement skills are represented by five skill facets (Figure 1). Respondents indicate how well they are capable to perform each tasks or activity on a response scale from not at all well (1) to extremely well (5).
Life Satisfaction
Life satisfaction (LS) was measured by a German single-item that asks how satisfied one is with his or her life on a scale with 11 answer categories from not at all satisfied (0) to completely satisfied (10) (Beierlein et al., 2015).
Self-Rated Health
As LS, self-rated health (SRH) was assessed with a single-item measure. Participants rated their health on a five-point scale from excellent (1) to very poor (5).
Big Five
The five Big Five personality traits were assessed with the German adaptation of the short Big Five inventory-2 (BFI-2-S, Rammstedt et al., 2020; Soto & John, 2017). In the BFI-2-S, each Big Five domain is represented by three facets, and each facet is assessed with two items (i.e., 30 items in total). Respondents indicate the extent to which each statement apply to them on a 5-point rating scale ranging from strongly disagree (1) to strongly agree (5).
Design and Procedure
SEB Skill Sample
Data on skills was collected in a correlational study design via Respondi AG by GESIS – Leibniz Institute for the Social Sciences. The data collection process took place within a validation study of the refined and final BESSI-G version in November 2021 (Lechner et al., 2022). About half of the original sample was randomly assigned to one of three different versions of the inventory, following an adapted three-form planned missingness design (PMD) (Graham et al., 1996). Each version contained 128 out of 192 items in a way that these participants were surveyed only on some skill facets. The other half of the sample was asked to answer all items of the BESSI-G (Lechner et al., 2022).
Big Five Trait Sample
Data on personality traits was collected using the same platform (Respondi AG) by GESIS in an earlier stage of the validation study on the BESSI-G (Lechner et al., 2022). Each participant answered one half of the BFI-2-S at two time points (January and March 2021). They received one of three versions of the inventory based on the PMD (10 of 15 items per time point; Graham et al., 1996). We merged the datasets from the two time points to examine age differences using the complete BFI-2-S.
Analyses
Our analysis plan consisted of several steps: Graphical analyses and latent structure models preceded our main analyses, which involved moderated non-linear factor analyses.
Graphical and Pre-Analyses
Before testing our RQs with statistical models, we visually examined the data using locally estimated scatterplot smoothing (LOESS) to identify and address non-linear associations between SEB skills, Big Five traits, and age (Cleveland & Devlin, 1988). Additionally, we explored the descriptive associations of SEB skills with LS and SRH using full information maximum likelihood estimation (FIML) and confirmatory factor analysis (CFA) models (Enders & Bandalos, 2001; Kline, 2016), complemented by graphic LOESS curves.
As an initial step prior to the main analyses, we assessed the measurement models of the skill facets and domains fitting single-factor CFA models (Bauer, 2017). Manifest facet scores (means) were used as indicators in the measurement models for the domains. For our additional analyses on the Big Five domains, we fitted single-factor CFA models using BFI items as indicators. Our evaluation relied on comparative fit index (CFI), and the standardized root mean square residual (SRMR) to assess the adequacy of these models (Hu & Bentler, 1999). Acceptable model fits were defined as having a CFI of ≥.90 and SRMR ≤ .10.
Main Analyses
In the main analyses, the research questions were addressed by application of moderated non-linear factor analyses models (MNLFA) to each skill domain and facet in single-factor analysis models (Bauer, 2017; Kolbe et al., 2024). In this model, age is treated as a continuous background variable (x), exerting influence on all the parameters of a measurement model (‘configural model’), instead of making distinct age groups within a multigroup comparison analysis. Subsequent model specifications allow for scenarios where age does not impact factor loadings (λ, metric invariance), indicator intercepts (α, scalar invariance), and residual variance (ε, strict invariance). Note that if parameters of the model indicators are moderated by age, that is, showing non-uniform or uniform differential indicator functioning (DIF; limited metric and scalar invariance, respectively), these age effects were freely estimated (partial invariance) (Byrne et al., 1989). Given that configural invariance is a fundamental assumption in MNLFA models, we initially conducted configural multigroup analyses (MG) per skill construct across three age groups with a robust maximum likelihood estimator (MLR) as a subgroup analysis (Bauer, 2017). Following the procedure described by Kolbe et al. (2024), we then fitted a ‘configural MNLFA model’ (no constraints) based on the results from the MG models. Next, we successively tested increasing invariance models against each other using the likelihood-ratio test (LRT) (i.e., configural, metric, scalar MNLFA models). In cases with significant model comparison results of LRT, we conducted follow-up tests to identify the indicators that function differently by age and modeled DIF effects within the final models (partial invariance). We tested linear and non-linear age effects on the latent means and variances within the final invariance models. The associations of skills with LS and SRH were examined within the same models, respectively. Finally, age was included as moderator into the models to analyze whether these relations vary by age. Additionally, we examined age differences in latent means and variances of skills within fully scalar invariant MNLFA models to check the robustness of our findings from our main analyses. MNLFA allowed us to examine age as a continuous variable, taking measurement invariance into account. As fallback strategy, we planned to conduct MG models across three age groups (Kline, 2016).
Although Wolf et al. (2013) do not address MNLFA directly, our sample size of N = 940 meets general recommendations for structural equation modeling in our analyses. However, the number of model parameters might exceed those of a simple CFA, which may limit their applicability to our results. Based on Molenaar (2021), formal power analyses for MNLFA models are not well established for this complexity, so we did not conduct one. We ran all analyses with R version 4.3.1 (R Core Team, 2023) and have made our analysis scripts available in our OSF project.
Supplementary Analyses: Big Five Traits
We conducted the same analyses as for the SEB skills to investigate age differences in the Big Five domains, using items as indicators. Each facet was measured by only two items; therefore, we used mean scores and conducted regression analyses to explore age differences. These supplementary analyses were not preregistered.
Results
Graphical and Pre-Analyses
In the first step, we graphically inspected age curves of the SEB skills and Big Five traits with LOESS smoothing using the mean score as criterion. Figure 2 directly contrasts each skill domain (left) with its corresponding Big Five trait (right). Self-management skills showed no age differences, whereas conscientiousness was greater among older adults. For social engagement skills and the extraversion domain, no substantial age differences were visible. Cooperation skills and agreeableness showed flat trends until about age 40, after which cooperation declined slightly while agreeableness increased. Emotional resilience skills decreased with age, in contrast to emotional stability, which increased. Finally, openness showed a smaller age-related decline than the more pronounced decrease in innovation skills. Age differences in most skill facets were inconsistent and rarely followed the patterns of their respective skill domains (Figure 3), whereas most Big Five facets demonstrated similar age curves to their respective domains (Figure 4). Age differences in social, emotional, and behavioral skills and the corresponding Big Five traits. Note. These plots served as a preliminary visual exploration of age trends. Plots generated using LOESS smoothing (span = .80). Skills and traits similar in content are presented side by side. Age differences in social, emotional, and behavioral skill facets. Note. Plots generated using LOESS smoothing (span = .80). In grayscale: rows 1–2 = self-management; 3 = cooperation; 4 = emotional resilience; 5 = innovation; 6 = social engagement; 7 = compound skills. Cap. for = Capacity for; manag. = management. Age differences in Big Five facets. Note. Plots generated using LOESS smoothing (span = .80). In grayscale: first 3 facets = conscientiousness; next 3 = agreeableness; next 3 = negative emotional stability; next 3 = openness; next 3 = extraversion.
Before estimating MNLFA models, we fitted single-factor CFA models to check the factor structure of each skill, Big Five domain, and skill facet. Tables S3a and S3b present the results for the SEB skill and Big Five domains, respectively. Results for the skill facets aligned with those in Lechner et al. (2022, Table 3). The model fits of skills were generally acceptable (CFI ≥ .93, SRMR ≥ .03), except for the facet time management (CFI = .81, SRMR = .08), which we resolved by introducing a residual correlation for one item pair (‘Show up for things on time’ and ‘Get to appoints on time’). The model fits for conscientiousness, emotional stability, extraversion, and openness became acceptable after introducing at least one residual correlation in each model (CFI = .90–.96, SRMR = .04–.05), reflecting shared facet-specific variance or similarities in item content. These models served as the baseline for pretesting configural invariance with an MG approach.
For each skill domain and facet, we conducted single-factor MG analyses to assess configural invariance across three age groups with approximately equal sample sizes (skill sample: 17–35: n = 298; 36–50: n = 305; 51–56: n = 337). Configurally invariant MG models displayed good model fits (CFI = .91–.98, SRMR = .03–.065), except for the facets capacity for trust and self-reflection (Table S4a), which we resolved by introducing residual correlations that can be attributed to common grammatical constructions or words (Lechner et al., 2022). We tested increasing invariance before investigating latent mean differences in skills and variances within each age group in final MG models (Tables S5 and S6).
After establishing configural invariance for the SEB skills, we tested configural invariance in the Big Five domains across three age groups with roughly equal sample sizes (trait sample: 17–24: n = 337, 25–45: n = 244, 46–64: n = 289). We found configural measurement invariance for agreeableness, emotional stability, and openness with good model fits (CFI = .95–1.00, SRMR = .05–.07). To achieve acceptable fits for conscientiousness and extraversion, introducing a residual correlation for one item pair in each model was necessary (Table S4b).
Main Analyses
Following the pre-analyses, we conducted MNLFA single-factor models per skill domain and facet to test our hypotheses. Facet scores (i.e., the within-person average across the items belonging to a facet) served as indicators for the corresponding skill domain in the domain models, and items served as indicators for skill facets in the facet models. We fitted the same models for Big Five domains using items as indicators in the additional analyses. All steps to test the measurement invariance of SEB skills and Big Five domains across age are thoroughly described in the Supplemental Material.
Measurement Invariance of SEB Skills and Big Five Traits Across Age
For nearly all skill domains, except innovation, metric invariance was given, whereas none of the domains exhibited full scalar invariance. Of the 32 skill facets, 14 were fully scalar invariant across age, whereas 16 facets demonstrated partial scalar invariance, and 2 facets did not meet the criteria for metric invariance. Therefore, the null hypothesis of scalar invariance concerning age was rejected for all skill domains and almost half of the skill facets. Our analyses revealed that 1 to 2 indicators per skill domain were moderated by age (20–50%), while 6 out of 11 indicators of self-management exhibited DIF (54.5%). Mostly, 1 or 2 indicators of the skill facets exhibited DIF (in 17% and 34%, respectively). In our Big Five analyses, indicators of emotional stability (50%) and openness to experience (16.6%) exhibited DIF. An overview of indicators with age-moderated intercepts and loadings is provided in the Supplemental Material (skill domain indicators: Table S7d; skill facet items: Table S8d; Big Five trait items: Table S11d). These skill and trait indicators were allowed to vary by age within final invariant models, which served as baselines for examining age differences in latent means and variances. We used the unadjusted p-values and the highest χ2-values to detect indicators with DIF (Tables S7a–S8c, and S11a–S11c).
Summary of age differences in SEB skills within the final invariance models
Note. LS = life satisfaction; SRH = self-rated health; x-age = moderation of the association by age; quad. = quadratic effect; MI = percent of indicators within each final model that were s scalar or m metric invariant. Effects are standardized. Confidence intervals and exact p-values are reported in the supplementary materials.
+p < .10, *p < .05, **p < .01.
aThis linear age effect within the MNLFA did not align with the plot. A subsequent multiple regression with manifest variables indicated no linear (β = −.04, p = .276) but a quadratic negative age effect (β = −.15, p ≤ .001).
Summary of age differences in Big Five domains within the final invariance models
Note. MI = percent of indicators within each final model that were s scalar or m metric invariant. Effects are standardized. Confidence intervals and exact p-values are reported in the supplemental material.
+p < .10, *p < .05, **p < .01.
Age Differences in SEB Skills
The final detected invariance models were used to examine age differences in latent skill levels and variances. The mean levels of emotional resilience and innovation domains were significantly lower in older individuals. We observed no age differences in the social engagement domain, and only a marginally significant positive age effect on cooperation. The self-management domain was lower in older adults, which was the only result that was not confirmed in the robustness analysis (Tables S9a and S9b). No quadratic age effects on latent means of the domains were observed, but some were identified in the latent variances (Table 1). We observed more linear age effects on latent means in the facets. Overall, older adults scored higher in the five skill facets detail and responsibility management, capacity for optimism, task- and time management. In contrast, the following 14 skill facets were lower in older adults: capacity for consistency, rule following, leadership skill, persuasion skill, capacity for trust, perspective taking skill, stress regulation, anger management, impulse regulation, creative skill, abstract thinking skill, information processing skill, cultural competence, artistic skill. In one case, the significant negative linear age effect for capacity for consistency did not correspond with the visual plot. A post-hoc multiple regression using manifest variables indicated a non-significant linear age effect (β = −.04, p = .276) and a significant negative quadratic age effect (β = −.15, p ≤ .001) aligning with the observed age curves. The results for facets were often inconsistent with those of the corresponding domain. Thus, we found only a few systematic age differences.
Age-Specific Associations of SEB Skills With Life Quality
The final models were used to examine the associations with life satisfaction (LS) and self-rated health (SRH), and their moderation by age. All skills, including innovation skills, were positively linked to LS and SRH. Correlation coefficients for skill associations with LS ranged from r = .13 to .41, and with SRH from r = .10 to .43, with emotional resilience showing the strongest associations (r = .41 and r = .43, respectively). Almost all facets assigned to the emotional resilience domain correlated with the indicators at r ≥ 0.30. The social engagement skill domain showed a positive association with LS (r = .31), with the expression skill facet demonstrating the highest correlation (r = .30). Within the self-management skill domain, the energy regulation facet showed the strongest associations with LS (r = .37) and SRH (r = .41). Similarly, the information processing facet within the innovation skill domain had the highest associations with LS (r = .36) and SRH (r = .33). Associations between cooperation skills and both LS and SRH were mostly below .30. Finally, the compound adaptability skill showed correlations above .30 with LS (r = .36) and SRH (r = .33).
Six skill facets showed significant age-specific associations with life quality (Table 1, Table S10a). Age negatively moderated the associations of rule following and information processing skills with LS (both −.09). In contrast, age positively moderated the associations of SRH with the skill facets organization (.10), impulse regulation (.09), and self-reflection, while it negatively moderated the association with the capacity for trust facet (−.09). These findings were robust (Table S10b). A transparent comparison of preregistered and conducted analyses is provided in Table S14.
Age Differences in Big Five Traits
The final Big Five MNLFA models were the baseline to investigate age differences in Big Five domains as we did for SEB skills (Table 2). Conscientiousness and emotional stability were greater among older adults than younger ones; extraversion was lower. We found no linear age effect on the latent mean of agreeableness, but a marginally significant positive quadratic effect (p = .056). Further, we observed significant age effects on the variances of extraversion and openness. In our robustness analyses, we found the same pattern of results for age differences in latent means (Table S12b).
In the regression analyses (Table S13), the emotional stability and conscientiousness facets showed consistent results with their domains (anxiety: β = −.17, SE = .04, p < .001; depressiveness: β = −.20, SE = .04, p < .001; emotional volatility: β = −.14, SE = .04, p < .001; organization: β = .13, SE = .04, p < .001; productiveness: β = .20, SE = .04, p < .001; responsibility: β = .15, SE = .04, p < .001). Within the extraversion domain, we found a negative linear age effect on assertiveness (β = −.09, SE = .04, p = .027), and within the openness domain, a negative linear age effect on aesthetic sensitivity (β = −.10, SE = .04, p = .014). We observed a quadratic age effect on the respectfulness facet of agreeableness (β = .13, SE = .06, p = .024) but no linear one. For the remaining facets, we did not find age effects.
Discussion
The present research investigated whether the maturity principle applies to social, emotional, and behavioral (SEB) skills by examining age differences in a large German adult sample, and whether similar age patterns occur in Big Five traits in a comparable sample with the same age range. Additionally, the study analyzed associations of these skills with life satisfaction (LS) and self-rated health (SRH), and how these associations are moderated by age.
Notably, our findings challenge the maturity principle as applied to SEB skills, whereas the well-known maturity-related age patterns emerged mostly as expected for the Big Five traits. Importantly, the observed age differences in SEB skills and Big Five traits across two comparable German samples cannot be attributed to cultural specificity or methodological biases of the panel provider, reinforcing that the divergence between SEB skills and Big Five traits is substantive. According to the maturity principle, one would expect older adults to exhibit higher levels of self-management (corresponding to conscientiousness in the Big Five), emotional resilience (similar to emotional stability), and cooperation skills (similar to agreeableness). However, our results suggest that this normative principle may not generalize from personality traits to SEB skills, as age differences in most skill domains and facets did not follow this pattern. In fact, the emotional resilience domain was lower among older adults, and the cooperation domain showed only marginally significant age differences. While older adults did display higher levels of self-management, this finding was not confirmed in the robustness analysis. However, in this domain, the majority of skill facets followed the pattern suggested by the maturity principle. Innovation skills (aligning with openness) tended to decline with age, whereas the social engagement domain (overlapping with extraversion) remained stable across age. More nuanced age differences were found in the skill facets, sometimes deviating from domain-level results, offering a more precise understanding of individual differences. These varying patterns echo earlier findings in personality research (Soto et al., 2011; Soto & John, 2012), suggesting that specific skill facets, like trait facets, may be in dissimilar demand at different ages.
All skill domains and facets were positively associated with LS and SRH, with emotional resilience skills emerging as the most important. Only a few age-specific associations were detected, pointing to different relevance of some skill facets – rule following, information processing, organization, impulse regulation, self-reflection, and capacity for trust – for life quality. Below we discuss the results, contrasting them with findings on personality traits.
Measurement Invariance Across Age
Prior to analyzing age differences in SEB skills and Big Five domains, we tested for measurement invariance across age using MNLFA because it has traditionally been considered a precondition for group comparison (Widaman & Reise, 1997). Metric invariance was not established for the innovation domain and two skill facets (non-uniform DIF). Full scalar invariance only held for a subset of the skill facets (44%) and three Big Five domains (60%), suggesting that some BESSI and BFI items might function differently across age. However, we do not consider this a major issue, as our robustness analyses imposing full invariance yielded the same substantive findings in nearly all cases. The only exception was the self-management domain, where results differed in the robustness analysis – and which is also the broadest and most heterogenous skill domain.
From a theoretical perspective, DIF effects may reflect actual and valid age differences, for example, in life priorities (Karwetzky et al., 2021), which could lead to age-specific patterns of item endorsement. However, the necessity of full measurement invariance is under current debate (Fischer & Rudnev, 2024; Funder & Gardiner, 2024; Robitzsch & Lüdtke, 2023). For example, Robitzsch and Lüdtke (2023) argue that DIF might be a part of construct validity rather than a major threat to group comparisons (see the section on age differences in skill and trait indicators). Our robustness analyses made this issue less pressing, showing that observed age differences in skills remained mostly consistent with those observed in the final invariance models, regardless of whether DIF was modeled or full scalar invariance was imposed. Thus, we interpret the observed age differences in skills as valid, supported by both theoretical considerations and robustness analyses.
Age Differences in SEB Skills
Age differences in SEB skills stand in contrast to age differences and developmental trajectories in personality traits, highlighting that the maturity principle may not generalize from personality traits to SEB skills completely. These concerns become more tangible at the skill facet level, where age differences did not consistently align with their respective domains, whereas in the Big Five, facet-level age differences matched the domain-level trends more often. This divergence is theoretically noteworthy in the context of personality development, a topic of current discussion (Klimstra & McLean, 2024).
Self-Management Skills
Self-management skills involve capacities to pursue goals and complete tasks effectively, and represent a behavioral referent of conscientiousness (Lechner et al., 2022; Soto et al., 2022). In the final invariance model, the skill domain level was higher in older adults, aligning with the expectations of the maturity principle. However, we believe this result may be influenced by the composition of the domain, which includes eleven skill facets. This likely explains the single non-robust result observed in the full scalar model, where no age difference was found at the domain level. Unlike the domain level, several age differences in skill facets remained robust across models, suggesting that the broad aggregation at the domain level may obscure meaningful variation.
Interestingly, rule following was negatively associated with age, and its relevance for LS was weaker in older adults. This result, which initially appears to contradict the maturity principle, may reflect that in older adults, LS tends to rely less on meeting others’ expectations and more on personal autonomy (Deci & Ryan, 2000). In this sense, a weaker tendency to follow rules could actually reflect a nuanced aspect of maturity, aligning with the idea that it peaks in late adolescence (Feraco & Meneghetti, 2023) and shifts towards increasing autonomy after transition into adulthood (Arnett, 2015). This shift toward autonomy might explain why the facet capacity for independence was higher among older adults in our study.
Capacity for consistency showed an inverted U-shaped association with age, evidenced by its plot combined with statistical results, peaking in established adulthood (30–45 years). This may point to the maintenance of social roles in family and working life, which is typically viewed as characteristic of this period of life (Mehta et al., 2020). In our study, older adults showed several stronger self-management skill facets, which might reflect the increasing complexity of life contexts with age, requiring enhanced self-management skills. We hypothesize that capacity for consistency may act as an investment factor, supporting further refinement of detail, task, and time management skills beyond adolescence (Feraco & Meneghetti, 2023). Interestingly, other facets, like organization or goal regulation, showed no age differences although the corresponding Big Five facet, organization, did. Overall, some age differences in skills, though not all, resemble developmental trends observed in conscientiousness (Roberts & Nickel, 2021). However, the age differences in conscientiousness observed in the Big Five sample aligned more strongly with the maturity principle.
Social Engagement Skills
Social engagement skills, closely related with extraversion, involve capacities for active interaction with others and encompass four facets in the German BESSI structure (Lechner et al., 2022). At the domain level, there were no age differences, corresponding to findings on the absence of age trends in extraversion (Bleidorn et al., 2022; Soto et al., 2011). Still, in the Big Five sample, older adults showed lower extraversion levels and greater interindividual differences. This contradicts our hypothesis that social engagement could increase with age and contrasts with results observed during adolescence (Feraco & Meneghetti, 2023). The lower skill level in early adolescence might be caused by reduced confidence in new social situations (e.g., changing relationships), a challenge that might be mastered in later stages of adolescence. Our findings possibly imply that skills in this domain stabilize in young adulthood.
At the facet level, our findings on age differences differ from the previously reported increase in social dominance, a subcomponent of extraversion (Roberts et al., 2006), which we had hypothesized to be similar to social engagement. We observed age differences in two of the four skill facets. First, the persuasion skill was less pronounced in older adults. Second, the leadership skill of asserting one’s position and making decisions for a group as well as the aligned assertiveness facet of extraversion were lower in older adults. These results are consistent with the idea that older adults prioritize social harmony and cooperative tactics over confrontation as they age. Moreover, shifting life priorities with age – such as a growing emphasis on social relationships and a reduced focus on career ambitions (Charles & Carstensen, 2010; Karwetzky et al., 2021), including fewer opportunities to practice leadership skills – may further explain these results. In contrast, the conversational and expressive skills might reflect more context-independent capacities, learned during late adolescence (Feraco & Meneghetti, 2023). Taken together, our findings suggest that the content of social engagement skills does not fully align with the developmental concept of social dominance (Roberts et al., 2006). Future research could explore the role of individuals’ contexts and life experiences in shaping these social engagement skills as well as extraversion.
Cooperation Skills
Cooperation skills are capacities to maintain positive social relationships and are closely related to agreeableness (Soto et al., 2022). According to the maturity principle, agreeableness increases across lifespan (Roberts & Nickel, 2021). Contrary to our hypothesis, cooperation skills were marginally significant associated with age. Agreeableness was slightly higher in older adulthood, as reflected by a significant quadratic age effect, consistent with the maturity principle. Since cooperation skills likely increase before adulthood (Feraco & Meneghetti, 2023), we speculate that they might naturally support the development of agreeableness (Matthews, 2018). For example, individuals who take on responsibilities to maintain positive relationships during adolescence may have more opportunities to practice cooperative behaviors, which could foster more general agreeable tendencies over time. However, the observed divergence in age differences between cooperation skills and agreeableness may reflect that the expression of these skills depends on current social available contexts.
Three cooperation skill facets – ethical competence, social warmth, and teamwork skill – showed no age differences. The two other skill facets were lower in older adults. First, the level of the capacity for trust was lower in older adults, which contrasts with the traditional view of interpersonal trust as inherently beneficial. However, its relationship with adaptability follows an inverse U-shaped pattern (Rothberg, 2019), meaning that lower trust with increasing age may be an adaptive response to individual contexts. This may explain why the relevance of this skill for SRH was weaker at higher ages in our study. Since the level of capacity for trust appears to remain stable during adolescence (Feraco & Meneghetti, 2023), its decline might begin in adulthood as individuals encounter increasingly diverse contexts and experiences that challenge their capacity for trust in different ways. This could account for greater interindividual differences in the capacity for trust facet observed with age.
Second, adolescents tended to show higher levels of perspective taking, possibly attributable to advanced cognitive abilities compared to their younger peers (Feraco & Meneghetti, 2023; Hollarek & Lee, 2022). However, in our study, older adults scored lower on this facet compared to younger individuals. This aligns with previous research that observed lower self-reported empathy in older adults in cross-sectional studies, despite a lack of longitudinal decline (Grühn et al., 2008). Grühn et al. speculated that this might reflect generational differences, such as greater openness to discuss personal and others’ feelings among younger adults. We suggest that, beyond possible generational differences, age-related contextual factors present at a given time may also contribute to these observed skill differences. In sum, age differences in cooperation skills do not conform to the normative expectation – as suggested for the related trait agreeableness by the maturity principle.
Emotional Resilience Skills
Emotional resilience skills, encompassing five facets, are capacities for affect regulation (Lechner et al., 2022). Interestingly, the domain level was lower in older adults, driven by lower stress regulation, anger management, and impulse regulation, that is, capacities for coping with unpleasant affect. This contradicts previous findings on emotion regulation strategies and the closely related trait emotional stability, which suggest the opposite trend of increases with age (Bleidorn et al., 2022; Gross et al., 1997; Mather & Carstensen, 2005; Soto et al., 2011; Urry & Gross, 2010). In contrast to these skill patterns, emotional stability was higher among older adults in the Big Five sample. In adolescence, cross-sectional findings showed a positive association of age and this skill domain (Feraco & Meneghetti, 2023), suggesting a rise into young adulthood. The lower emotional resilience skills observed in older adults may therefore indicate a non-linear trajectory – potentially involving an increase during adolescence followed by a subsequent decrease in adulthood. No age differences emerged in capacity for optimism and the confidence regulation skill.
In addition to life experiences and changing socioemotional goals, which likely shape emotion regulation before an event (i.e., situation selection), age-related changes in cognitive resources, arousal duration, and physiological flexibility may reduce the effectiveness of affect regulation during high-intensity contexts (Riediger & Bellingtier, 2022). This could explain lower self-reported capacities to manage negative affect in older adults. As a compensatory strategy, older individuals could select less stressful situations (Charles & Carstensen, 2010), which may help understand their greater emotional stability trait.
Beyond mean-level differences, variability of most skill facets across age, except anger management, provides important insights. We found several inverted U-shaped associations of skills variances with age, suggesting that interindividual differences in these skills might increase, peak, and decline across adulthood. The greater variability in these skills might also be explained by differences in emotional contexts (Riediger & Bellingtier, 2022), supporting the idea that individuals must be understood in their unique contexts (Klimstra & McLean, 2024; Matthews, 2018). Overall, our findings suggest that emotional resilience skills and emotional stability clearly diverge with respect to the maturity principle.
Innovation Skills
Innovation skills, encompassing the facets abstract thinking, information processing, cultural competence, artistic, and creative skills, reflect capacities to engage with novel and creative ideas. This skill domain is closely related to the trait openness (Lechner et al., 2022; Soto et al., 2022). Contrary to our assumption of an inverted U-shaped age association, older adults reported lower innovation skills than younger adults. Previous longitudinal studies have shown an increase in the related openness trait during young adulthood, followed by a decrease (Bleidorn et al., 2022). Increases in innovation skills may occur in late adolescence (Feraco & Meneghetti, 2023) but were not captured in our sample due to the minimum age of 18 years. Interestingly, variance was higher with age in all innovation skills, peaking in some facets, before declining (e.g., the innovation domain, information processing, cultural competence, and artistic skill). In addition, we did not find age differences in the openness trait in the Big Five sample but observed greater variance with increasing age. This suggests less similar age patterns in openness and innovation than originally expected. While the aligned trait refers to the extent of being generally open, the BESSI assesses specific openness-related and intellectual behaviors.
Feraco and Meneghetti (2023) argue that the increase in the innovation skills level found in older youths (15 to 17 years) may result from the secondary school context fostering abstract and complex thinking. Similarly, the average lower innovation skills in adulthood in our study might be explained by contextual changes, such as shifts in cognitive job demands, as well as age-related declines in cognitive resources. For example, innovation skills resemble processing speed as well as general fluid intelligence in content (e.g., understanding abstract ideas) and may reflect individuals’ subjective judgments of such. Both fluid intelligence and processing speed typically peak in early adulthood before they decrease over the life course (Cattell, 1963; Deary et al., 2009). It is likely that the lower self-reported innovation skills with age reflect an actual decline in fluid abilities, although only a few facets demonstrated associations above r = .10 with fluid abilities in a previous study (Lechner et al., 2022).
The larger differences in innovation skills among older adults might represent the differences in age-related declines in fluid ability (Deary et al., 2009) or general differences in life contexts. For example, adults of the same age require different levels of innovation skills depending on the cognitive demands of their occupation (Hunt & Madhyastha, 2012), although these differences appear to narrow in later adulthood.
Age Differences in Skill and Trait Indicators
To understand potential developmental changes in how skills and traits manifest in behavior, we conducted follow-up tests within the final analysis models focusing on age-related moderation of indicator loadings and intercepts. Such differences may provide some insight into maturational shifts in construct meaning and construct-relevant behaviors. Overall, only 3 out of 192 skill factor loadings were moderated by age (decision making and conversational skill facets). In addition, age moderated one facet-level loading of the innovation skills domain and one indicator loading of the trait openness to experience. These limited effects suggest only minor age-related changes in construct meanings.
The 28 out of 192 age differences in skill item intercepts indicate that, beyond differences in latent mean levels, some behavioral manifestations of skills vary in magnitude with age. For example, behaviors reflecting submissive obedience within the rule-following facet were less pronounced in older adults, whereas confident – but not dominant – behaviors within the persuasion facet were more pronounced with age. In the Big Five, we found five out of 30 possible intercept differences. These indicate that older adults reported lower interest in abstract ideas, art, or music (openness to experience), and were less likely to agree with emotionally stable statements, while no age differences were found in emotionally labile statements (emotional stability). From a theoretical perspective, shifts in the expression of skills and traits may precede changes at the latent construct level. However, longitudinal research is required to determine whether such behavioral shifts translate into changes in the underlying constructs.
Associations With Life Quality
We investigated how SEB skills relate to two life quality indicators: life satisfaction (LS) and self-rated health (SRH). All skills were beneficial for LS and SRH, with emotional resilience skills standing out. We classified effect sizes as ‘relatively small’ (|.10|), ‘typical’ (|.20|), and ‘relatively large’ (|.30|) (Gignac & Szodorai, 2016).
Among all skill domains, emotional resilience skills appeared to be most closely related to a healthy and satisfying life. Notably, impulse regulation showed a positive age-specific association, possibly acting as a protective factor for SRH in older adults. However, the associations of emotional resilience skills with life quality might partly reflect conceptual closeness to well-being measures, as these skills are directly linked to emotional experiences (i.e., staying in a positive mood).
Social engagement skills predominantly displayed typical associations with life quality. Within this domain, expressive skill emerged as particularly relevant, supporting evidence that expressing one’s thoughts and feelings – an aspect of quality in social interactions – is linked to well-being (Sun et al., 2020). Within the cooperation skills, the facet capacity for trust was most beneficial for SRH, although this advantage was weaker in older adults. As noted earlier, a balanced level of interpersonal appears to be important for maintaining well-being (Rothberg, 2019).
Self-management skills showed small-to-typical associations with both LS and SRH. The energy regulation skill was particularly important, showing stronger relations than other facets, possibly due to its role in successful goal pursuit for well-being (Klug & Maier, 2015). In older adults, rule following was less relevant for LS possibly due to increased autonomy, whereas organization skill showed stronger associations with SRH.
Contrary to our hypothesis, innovation skills were positively associated with life quality, with information processing showing notable effect sizes. Nevertheless, the association of information processing with LS was weaker in older adults, suggesting that social aspects may become relatively more important sources of life quality in later adulthood (Charles & Carstensen, 2010).
Finally, the compound skills self-reflection and adaptability showed mostly large associations with life quality. The self-reflection skill may play a protective role for SRH in older adults. Overall, these findings are consistent with prior research on personality traits and well-being (Anglim et al., 2020; Soto et al., 2022, 2024; Stephan et al., 2012, 2020), highlighting the value of SEB skills for life quality and how their importance may differ across age.
Maturity Principle Revisited
The maturity principle is a widely accepted explanation for personality development (Roberts & Nickel, 2021), but it has recently faced criticism (Klimstra & McLean, 2024). A common assumption is that normative contexts and social roles drive personality changes in socially desirable directions, suggesting that individuals face similar situations and experiences. Another implication of the maturity principle is the implicit assumption that personality development starts from an immature point, moves in a socially desirable direction, and reaches an irreversible endpoint. Such generalizations ignore context-dependencies of individual development.
Our findings on age differences suggest that the maturity principle may not generalize from personality traits to SEB skills. Some skill levels were lower in older adults, and variances differed by age. In contrast, emotional stability and conscientiousness were greater, and agreeableness tended to be higher in older adults, consistent with the idea of the maturity principle. These patterns suggest that the maturity principle may apply, on average, more strongly to traits than to skills. These findings are surprising for two main reasons: First, SEB skills and Big Five traits are strongly correlated (Lechner et al., 2022; Soto et al., 2022), which would suggest similar age patterns. Second, it has been assumed that practicing skills fosters coherent trait changes, and that both constructs develop reciprocally (Matthews, 2018; Roberts et al., 2017; Soto et al., 2022).
Skills, however, represent context-sensitive capacities that require opportunities to learn and practice, whereas traits represent general tendencies (Soto et al., 2021). At a higher age, situations that evoke certain skill demands may become less frequent. Reduced opportunities for skill enactment may therefore explain lower skill levels in older adults, despite greater trait levels. We further assume that acquired skills in late adolescence (Feraco & Meneghetti, 2023) may feed into subsequent trait development, thereby contributing to the emergence of maturity-related trait patterns. However, these considerations call for longitudinal examination.
The present results have three implications. First, being older does not necessarily imply improvement in the performance of socially desirable behaviors; older individuals might exhibit behaviors considered as less socially desirable but may nonetheless be interpreted as a nuanced aspect of maturity (e.g., capacity for trust). Second, we claim that integrating contextual factors and their interaction with the individual may refine our understanding of individual differences (e.g., age differences in skill and trait variances). For SEB skills in particular, the interaction with context is relevant, as these skills, by definition, address capacities for behaviors when situations, contexts, or life circumstances call for them. This supports the notion that SEB skills are not equivalent to universal personality traits representing more general tendencies (Soto et al., 2021, 2022). Third, skills and traits may increasingly diverge over the course of personality development as certain situational demands diminish in adulthood, possibly because reduced opportunities to practice skills lead to a parting of the ways between skills and traits. These hypotheses warrant further examination in future research. Taken together with Klimstra and McLean’s (2024) critique of the maturity principle as a normative concept in personality psychology, our study extends this discussion to SEB skills, thereby opening new avenues for future research.
Limitations and Future research
Our study comes with some limitations. First, as with all cross-sectional studies, observed age differences may reflect cohort differences rather than (or in addition to) age-related developmental effects. At least, our samples were age-heterogeneous and approximately representative of the adult German population, with quotas for age, sex, and education. Therefore, our findings provide a starting point for understanding how SEB skills may develop across the lifespan. It may take years or even decades before meaningful longitudinal data is collected. Similar pioneering work has been done in the past, for example, when researchers began to investigate age differences in the Big Five (McCrae et al., 1999, 2005). An accelerated cohort design (Galbraith et al., 2017) could provide a clearer picture into whether cross-sectional age differences reflect developmental trajectories and/or which are attributable to cohort differences.
Second, self-reported skills as measured by BESSI reflect skill self-concepts rather than actual skills (Breil et al., 2022). To date, no objective assessments of all SEB skills are available, and existing validated tools do not cover the full range of 32 skill facets across five domains (Linzarini & Catarino da Silva, 2024). Despite this, self-reports remain a practical and economical way for assessing a broad range of skills (Lechner & Urban, 2025). Moreover, self-reports still demonstrate good predictive and incremental validity beyond cognitive abilities (Iliescu et al., 2023; Roemer et al., 2022), and a medium-to-high skill self-concept might motivate corresponding behavior, as shown by relations of academic self-concept and achievement (see Lechner & Urban, 2025; Möller et al., 2020; Wu et al., 2021). Still, including reports of significant others may provide complementary insights across different contexts (cf., OECD, 2021). Future research may explore how self- and other-reported skills interact with contexts, such as life circumstances and situational demands.
Third, the causal relationship between skills and life quality remains unclear. Skills might support investments in health and life satisfaction. Conversely, they might provide skill development, as reciprocal relationships between personality and well-being have been observed over time (Soto, 2015). Additionally, since both skills and life quality are self-reported, their associations might be subject to common method bias (Podsakoff et al., 2003). Intensive longitudinal and multi-method studies could help clarify the direction of causality.
Fourth, we compared age differences in skills to those in traits in two German samples. While SEB skills overlap with Big Five traits (Soto et al., 2022), we observed important divergences in age trends. It remains unclear whether these patterns generalize to other samples or non-WEIRD cultures. Lastly, we did not address other implications of the age-related non-invariance. Future research could clarify under which conditions DIF can be treated as construct-relevant rather than bias, and how such considerations could inform anchor choices. Nonetheless, our robustness analyses showed DIF did not affect our results essentially.
Conclusion
Contrary to the proposed maturity principle in personality development, our study found fewer systematic age differences in SEB skills, whereas expected age differences were observed in Big Five traits. This divergence suggests that skills might follow distinct developmental trajectories from those of the corresponding traits. It challenges the idea that the maturity principle is a general rule across different constructs, particularly in the context of SEB skills. Aligning with critical voices in the field (Klimstra & McLean, 2024), we echo calls for a more nuanced understanding of development. Future research should examine SEB skills and Big Five traits jointly in longitudinal designs and explore individual-context-interactions, recognizing that psychological constructs are contextualized adaptions (Matthews, 2018).
Supplemental Material
Supplemental Material - Does the ‘Maturity Principle’ Hold for Social, Emotional, and Behavioral Skills? A Study on Age Differences From 18 to 65
Supplemental Material for Does the ‘Maturity Principle’ Hold for Social, Emotional, and Behavioral Skills? A Study on Age Differences From 18 to 65 by Maria Jalynskij, Franz J. Neyer, Clemens M. Lechner in European Journal of Personality.
Footnotes
Ethical Considerations
Original data collection complied with the Helsinki declaration and the European Union’s General Data Protection Regulation (GDPR); no additional ethics review was necessary.
Consent to Participate
Participants gave informed consent.
Funding
This research was partly funded by a grant from the Bertelsmann Stiftung to C.M.L.
Declaration of Conflicting Interests
The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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References
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