Dedifferentiation and differentiation of intelligence in adults across age and years of education

Modelling nonlinear moderation effects with local structural equation modelling (LSEM): A non-technical introduction

Understanding the differential strength of effects in the presence of a third variable, known as a moderation effect, is a common research goal in many psychological and behavioural science fields. If structural equation modelling is applied to test effects of interest, the investigation of differential strength of effects will typically ask how parameters of a latent variable model are influenced by categorical or continuous moderators, such as age, socio-economic status, personality traits, etc. Traditional approaches to continuous moderators in SEMs predominantly address linear moderation effects, risking the oversight of nonlinear effects. Moreover, some approaches have methodological limitations, for example, the need to categorise moderators or to pre-specify parametric forms of moderation. This tutorial introduces local structural equation modelling (LSEM) in a non-technical way. LSEM is a nonparametric approach that allows the analysis of nonlinear moderation effects without the above-mentioned limitations. Using an empirical dataset, we demonstrate the implementation of LSEM through the R-sirt package, emphasising its versatility in both exploratory analysis of nonlinear moderation without prior knowledge and confirmatory testing of hypothesised moderation functions. The tutorial also addresses common modelling issues and extends the discussion to different application scenarios, demonstrating its flexibility.

Future time perspective and depression, anxiety, and stress in adulthood

BACKGROUND AND OBJECTIVE

Research has shown that perceptions of future time as limited are associated with more depressive symptoms. However, there is limited research on which dimensions of future time perspective (FTP: opportunity, extension, constraint) are associated with depression, anxiety, and stress, and whether these findings vary across age.

DESIGN AND METHODS

Data came from a cross-sectional study in a nonclinical U.S. sample (N = 793, 48.0% male; 48.7% female; age: M = 50 years, range: 19-85 years), and local structural equation modeling was used to examine the moderating role of age as a continuous variable rather than artificial age groups.

RESULTS

For all dimensions of FTP, the perception of the future as limited was moderately to strongly associated with higher depression, anxiety and stress levels. More importantly, the association between the perceived constraint dimension and depression, anxiety, and stress was twice as large at younger ages than at older ages.

CONCLUSION

These findings indicate that perceived constraint is primarily a strong risk factor for or indicator of negative wellbeing in young adulthood, whereas perceived limited opportunity and extension are potential risk factors or indicators across the entire adulthood.

Cross-sectional and Longitudinal Age-related Disintegration in Functional Connectivity: Reference Ability Neural Network Cohort

Some theories of aging have linked age-related cognitive decline to a reduction in distinctiveness of neural processing. Observed age-related correlation increases among disparate cognitive tasks have supported the dedifferentiation hypothesis. We previously showed cross-sectional evidence for age-related correlation decreases instead, supporting an alternative disintegration hypothesis. In the current study, we extended our previous research to a longitudinal sample. We tested 135 participants (20-80 years) at two time points-baseline and 5-year follow-up-on a battery of 12 in-scanner tests, each tapping one of four reference abilities. We performed between-tasks correlations within domain (convergent) and between domain (discriminant) at both the behavioral and neural level, calculating a single measure of construct validity (convergent - discriminant). Cross-sectionally, behavioral construct validity was significantly different from chance at each time point, but longitudinal change was not significant. Analysis by median age split revealed that older adults showed higher behavioral validity, driven by higher discriminant validity (lower between-tasks correlations). Participant-level neural validity decreased over time, with convergent validity consistently greater than discriminant validity; this finding was also observed at the cross-sectional level. In addition, a disproportionate decrease in neural validity with age remained significant after controlling for demographic factors. Factors predicting longitudinal changes in global cognition (mean performance across all 12 tasks) included age, change in neural validity, education, and National Adult Reading Test (premorbid intelligence). Change in neural validity partially mediated the effect of age on change in global cognition. Our findings support the theory of age-related disintegration, linking cognitive decline to changes in neural representations over time.

Understanding divergence: Placing developmental neuroscience in its dynamic context

Neurodevelopment is not merely a process of brain maturation, but an adaptation to constraints unique to each individual and to the environments we co-create. However, our theoretical and methodological toolkits often ignore this reality. There is growing awareness that a shift is needed that allows us to study divergence of brain and behaviour across conventional categorical boundaries. However, we argue that in future our study of divergence must also incorporate the developmental dynamics that capture the emergence of those neurodevelopmental differences. This crucial step will require adjustments in study design and methodology. If our ultimate aim is to incorporate the developmental dynamics that capture how, and ultimately when, divergence takes place then we will need an analytic toolkit equal to these ambitions. We argue that the over reliance on group averages has been a conceptual dead-end with regard to the neurodevelopmental differences. This is in part because any individual differences and developmental dynamics are inevitably lost within the group average. Instead, analytic approaches which are themselves new, or simply newly applied within this context, may allow us to shift our theoretical and methodological frameworks from groups to individuals. Likewise, methods capable of modelling complex dynamic systems may allow us to understand the emergent dynamics only possible at the level of an interacting neural system.

Estimating Local Structural Equation Models

Local structural equation models (LSEM) are structural equation models that study model parameters as a function of a moderator. This article reviews and extends LSEM estimation methods and discusses the implementation in the R package sirt. In previous studies, LSEM was fitted as a sequence of models separately evaluated as each value of the moderator variables. In this article, a joint estimation approach is proposed that is a simultaneous estimation method across all moderator values and also allows some model parameters to be invariant with respect to the moderator. Moreover, sufficient details on the main estimation functions in the R package sirt are provided. The practical implementation of LSEM is demonstrated using illustrative datasets and an empirical example. Moreover, two simulation studies investigate the statistical properties of parameter estimation and significance testing in LSEM.

Structural differences in life satisfaction in a U.S. adult sample across age

OBJECTIVE

Many studies investigating age-related mean differences in life satisfaction disregard potential differences in the structure of the life satisfaction construct. Because developmental tasks at different life stages vary and thus the salience of specific life domains (e.g., health, finances, relationships, etc.) might differ, life satisfaction might differ between age groups in its underlying structure and meaning.

METHOD

To address this issue, we investigated the covariance structure of life satisfaction as measured by the Satisfaction with Life Scale (SWLS) and the domains of health satisfaction and financial satisfaction with local structural equation modeling. We analyzed data from 8341 U.S. citizens between the ages of 30 and 97 who participated in the Panel Study of Income Dynamics. Furthermore, we explored the association of respondents' health and financial status with life satisfaction.

RESULTS

Both the SWLS and domain items were found to be invariant across age. The health and financial status accounted for small proportions of variance in overall life satisfaction and the respective domain satisfactions significantly at all ages.

CONCLUSION

The current analysis indicates that across the adult age range, general life satisfaction is qualitatively the same, and health and financial satisfaction are equally integrated into overall life satisfaction.

Correlated personality change across time and age

The goal of this study was to examine differential and correlated change in personality across the adult lifespan. Studying differential and correlated change can help understand whether intraindividual trait change trajectories deviate from the norm and how these trajectories are coupled with each other. We used data from two large longitudinal panel studies from the United States that covered a total age range of 20 to 95 years on the first measurement occasion. We used correlated factor models and bivariate latent change score models to examine the rank-order stability and correlations between change across three measurement waves covering 18 years ( N = 3250) and four measurement waves covering 12 years ( N = 4145). We examined the moderation effects of continuous age on these model parameters using local structural equation modeling. The results suggest that the test–retest correlations decrease with increasing time between measurements but are unaffected by participants’ age. We found that change processes in Extraversion, Openness, Agreeableness, and Conscientiousness were strongly related, particularly in late adulthood. Correlated change patterns were highly stable across time intervals and similar to the initial cross-sectional Big Five correlations. We discuss potential mechanisms and implications for personality development research.

The Relationship between Intelligence and Divergent Thinking-A Meta-Analytic Update

This paper provides a meta-analytic update on the relationship between intelligence and divergent thinking (DT), as research on this topic has increased, and methods have diversified since Kim’s meta-analysis in 2005. A three-level meta-analysis was used to analyze 849 correlation coefficients from 112 studies with an overall N = 34,610. The overall effect showed a significant positive correlation of r = .25. This increase of the correlation as compared to Kim’s prior meta-analytic findings could be attributed to the correction of attenuation because a difference between effect sizes prior-Kim vs. post-Kim was non-significant. Different moderators such as scoring methods, instructional settings, intelligence facets, and task modality were tested together with theoretically relevant interactions between some of these factors. These moderation analyses showed that the intelligence–DT relationship can be higher (up to r = .31–.37) when employing test-like assessments coupled with be-creative instructions, and considering DT originality scores. The facet of intelligence (g vs. g_f vs. g_c) did not affect the correlation between intelligence and DT. Furthermore, we found two significant sample characteristics: (a) average sample age was positively associated with the intelligence–DT correlation, and (b) the intelligence–DT correlation decreased for samples with increasing percentages of females in the samples. Finally, inter-moderator correlations were checked to take potential confounding into account, and also publication bias was assessed. This meta-analysis provides a comprehensive picture of current research and possible research gaps. Theoretical implications, as well as recommendations for future research, are discussed.

Age and gender differences in socially aversive (“dark”) personality traits

The strong overlap of personality traits discussed under the label of “dark personality” (e.g., psychopathy, spitefulness, moral disengagement) endorses a common framework for socially aversive traits over and beyond the dark triad. Despite the rapidly growing research on socially aversive traits, there is a lack of studies addressing age-associated differences in these traits. In the present study ( N = 12,501), we investigated the structure of the D Factor of Personality across age and gender using local structural equation modeling, thereby expressing the model parameters as a quasi-continuous, nonparametric function of age. Specifically, we evaluated loadings, reliabilities, factor (co-)variances, and means across 35 locally weighted age groups (from 20 to 54 years), separately for females and males. Results indicated that measurement models were highly stable, thereby supporting the conceptualization of the D factor independent of age and gender. Men exhibited uniformly higher latent means than females and all latent means decreased with increasing age. Overall, D and its themes were invariant across age and gender. Therefore, future studies can meaningfully pursue causes of mean differences across age and between genders.

A Reappraisal of the Threshold Hypothesis of Creativity and Intelligence

Intelligence has been declared as a necessary but not sufficient condition for creativity, which was subsequently (erroneously) translated into the so-called threshold hypothesis. This hypothesis predicts a change in the correlation between creativity and intelligence at around 1.33 standard deviations above the population mean. A closer inspection of previous inconclusive results suggests that the heterogeneity is mostly due to the use of suboptimal data analytical procedures. Herein, we applied and compared three methods that allowed us to handle intelligence as a continuous variable. In more detail, we examined the threshold of the creativity-intelligence relation with (a) scatterplots and heteroscedasticity analysis, (b) segmented regression analysis, and (c) local structural equation models in two multivariate studies (N1 = 456; N2 = 438). We found no evidence for the threshold hypothesis of creativity across different analytical procedures in both studies. Given the problematic history of the threshold hypothesis and its unequivocal rejection with appropriate multivariate methods, we recommend the total abandonment of the threshold.

Neurocognitive reorganization between crystallized intelligence, fluid intelligence and white matter microstructure in two age-heterogeneous developmental cohorts

Despite the reliability of intelligence measures in predicting important life outcomes such as educational achievement and mortality, the exact configuration and neural correlates of cognitive abilities remain poorly understood, especially in childhood and adolescence. Therefore, we sought to elucidate the factorial structure and neural substrates of child and adolescent intelligence using two cross-sectional, developmental samples (CALM: N = 551 (N = 165 imaging), age range: 5-18 years, NKI-Rockland: N = 337 (N = 65 imaging), age range: 6-18 years). In a preregistered analysis, we used structural equation modelling (SEM) to examine the neurocognitive architecture of individual differences in childhood and adolescent cognitive ability. In both samples, we found that cognitive ability in lower and typical-ability cohorts is best understood as two separable constructs, crystallized and fluid intelligence, which became more distinct across development, in line with the age differentiation hypothesis. Further analyses revealed that white matter microstructure, most prominently the superior longitudinal fasciculus, was strongly associated with crystallized (gc) and fluid (gf) abilities. Finally, we used SEM trees to demonstrate evidence for developmental reorganization of gc and gf and their white matter substrates such that the relationships among these factors dropped between 7-8 years before increasing around age 10. Together, our results suggest that shortly before puberty marks a pivotal phase of change in the neurocognitive architecture of intelligence.

Neural Dedifferentiation in the Aging Brain

Many cognitive abilities decline with age even in the absence of detectable pathology. Recent evidence indicates that age-related neural dedifferentiation, operationalized in terms of neural selectivity, may contribute to this decline. We review here work exploring the relationship between neural dedifferentiation, cognition, and age. Compelling evidence for age effects on neural selectivity comes from both non-human animal and human research. However, current data suggest that age does not moderate the observed relationships between neural dedifferentiation and cognitive performance. We propose that functionally significant variance in measures of neural dedifferentiation reflects both age-dependent and age-independent factors. We further propose that the effects of age on neural dedifferentiation do not exclusively reflect detrimental consequences of aging.

Creativity Style and Achievements: An Investigation on the Role of Emotional Competence, Individual Differences, and Psychometric Intelligence

Psychometric and emotional intelligence are considered as two separate theoretical constructs, although each one has been found to correlate to a certain degree with measures of creativity. The aim of the present study was to analyze whether individual differences such as age and gender, together with psychometric intelligence and emotional competence (EC) predicted creativity. We selected a sample of 376 participants aged 12-88 (mean age = 30.28 years, SD = 19.09 years; 224 females) to evaluate relationships between these constructs across lifespan. Participants were administered the Kaufman Brief Intelligence Test-2, the Short Profile of EC, the Creativity Style Questionnaire Revised (CSQ-R) and the Creative Achievement Questionnaire (CAQ). T-test on gender differences evidenced that males had higher creativity achievements compared to females. A path analysis was applied to examine the relationships between the CAQ and CSQ-R scores as dependent variables and the potential predictors assessed. Results showed that CSQ-R was significantly predicted by interpersonal emotional competence and marginally by educational level (p = 0.058) and intrapersonal emotional competence (p = 0.051). On the other hand, the CAQ score was significantly predicted by gender, age, and composite IQ. Discussion is focused on possible theoretical implications.