Structural architecture and brain network efficiency link polygenic scores to intelligence.

Intelligence is highly heritable. Genome-wide association studies (GWAS) have shown that thousands of alleles contribute to variation in intelligence with small effect sizes. Polygenic scores (PGS), which combine these effects into one genetic summary measure, are increasingly used to investigate polygenic effects in independent samples. Whereas PGS explain a considerable amount of variance in intelligence, it is largely unknown how brain structure and function mediate this relationship. Here, we show that individuals with higher PGS for educational attainment and intelligence had higher scores on cognitive tests, larger surface area, and more efficient fiber connectivity derived by graph theory. Fiber network efficiency as well as the surface of brain areas partly located in parieto-frontal regions were found to mediate the relationship between PGS and cognitive performance. These findings are a crucial step forward in decoding the neurogenetic underpinnings of intelligence, as they identify specific regional networks that link polygenic predisposition to intelligence.

The association between history of prenatal loss and maternal psychological state in a subsequent pregnancy: an ecological momentary assessment (EMA) study.

BACKGROUND: Prenatal loss which occurs in approximately 20% of pregnancies represents a well-established risk factor for anxiety and affective disorders. In the current study, we examined whether a history of prenatal loss is associated with a subsequent pregnancy with maternal psychological state using ecological momentary assessment (EMA)-based measures of pregnancy-specific distress and mood in everyday life. METHOD: This study was conducted in a cohort of N = 155 healthy pregnant women, of which N = 40 had a history of prenatal loss. An EMA protocol was used in early and late pregnancy to collect repeated measures of maternal stress and mood, on average eight times per day over a consecutive 4-day period. The association between a history of prenatal loss and psychological state was estimated using linear mixed models. RESULTS: Compared to women who had not experienced a prior prenatal loss, women with a history of prenatal loss reported higher levels of pregnancy-specific distress in early as well as late pregnancy and also were more nervous and tired. Furthermore, in the comparison group pregnancy-specific distress decreased and mood improved from early to late pregnancy, whereas these changes across pregnancy were not evident in women in the prenatal loss group. CONCLUSION: Our findings suggest that prenatal loss in a prior pregnancy is associated with a subsequent pregnancy with significantly higher stress and impaired mood levels in everyday life across gestation. These findings have important implications for designing EMA-based ambulatory, personalized interventions to reduce stress during pregnancy in this high-risk group.

Modeling dynamic personality theories in a continuous-time framework: An illustration.

OBJECTIVE: Personality psychology has traditionally focused on stable between-person differences. Yet, recent theoretical developments and empirical insights have led to a new conceptualization of personality as a dynamic system (e.g., Cybernetic Big Five Theory). Such dynamic systems comprise several components that need to be conceptually distinguished and mapped to a statistical model for estimation. METHOD: In the current work, we illustrate how common components from these new dynamic personality theories may be implemented in a continuous time-modeling framework. RESULTS: As an empirical example, we reanalyze experience sampling data with N = 180 persons (with on average T = 40 [SD = 8] measurement occasions) to investigate four different effects between momentary happiness, momentary extraverted behavior, and the perception of a situation as social: (1) between-person effects, (2) contemporaneous effects, (3) autoregressive effects, and (4) cross-lagged effects. CONCLUSION: We highlight that these four effects must not necessarily point in the same direction, which is in line with assumptions from dynamic personality theories.

A Dynamic Structural Equation Approach to Modeling Wage Dynamics and Cumulative Advantage across the Lifespan.

Wages and wage dynamics directly affect individuals' and families' daily lives. In this article, we show how major theoretical branches of research on wages and inequality-that is, cumulative advantage (CA), human capital theory, and the lifespan perspective-can be integrated into a coherent statistical framework and analyzed with multilevel dynamic structural equation modeling (DSEM). This opens up a new way to empirically investigate the mechanisms that drive growing inequality over time. We demonstrate the new approach by making use of longitudinal, representative U.S. data (NLSY-79). Analyses revealed fundamental between-person differences in both initial wages and autoregressive wage growth rates across the lifespan. Only 0.5% of the sample experienced a "strict" CA and unbounded wage growth, whereas most individuals revealed logarithmic wage growth over time. Adolescent intelligence and adult educational levels explained substantial heterogeneity in both parameters. We discuss how DSEM may help researchers study CA processes and related developmental dynamics, and we highlight the extensions and limitations of the DSEM framework.

Immediate impact of child maltreatment on mental, developmental, and physical health trajectories.

OBJECTIVE: The immediate impact of child maltreatment on health and developmental trajectories over time is unknown. Longitudinal studies starting in the direct aftermath of exposure with repeated follow-up are needed. METHOD: We assessed health and developmental outcomes in 6-month intervals over 2 years in 173 children, aged 3-5 years at study entry, including 86 children with exposure to emotional and physical abuse or neglect within 6 months and 87 nonmaltreated children. Assessments included clinician-administered, self- and parent-report measures of psychiatric and behavioral symptoms, development, and physical health. Linear mixed models and latent growth curve analyses were used to contrast trajectories between groups and to investigate the impact of maltreatment features on trajectories. RESULTS: Maltreated children exhibited greater numbers of psychiatric diagnoses (b = 1.998, p < .001), externalizing (b = 13.29, p < .001) and internalizing (b = 11.70, p < .001) symptoms, impairments in cognitive (b = -11.586, p < .001), verbal (b = -10.687, p < .001), and motor development (b = -7.904, p = .006), and greater numbers of medical symptoms (b = 1.021, p < .001) compared to nonmaltreated children across all time-points. Lifetime maltreatment severity and/or age at earliest maltreatment exposure predicted adverse outcomes over time. CONCLUSION: The profound, immediate, and stable impact of maltreatment on health and developmental trajectories supports a biological embedding model and provides foundation to scrutinize the precise underlying mechanisms. Such knowledge will enable the development of early risk markers and mechanism-driven interventions that mitigate adverse trajectories in maltreated children.

Resource-Building Processes Across Life Domains: Father-Child Interactions as Starting Points for Resource Caravans.

In two studies, we examined preconditions of resource-building processes between family and work. Focusing on positive father-child interactions, we investigated positive mood states as links between the two life domains. Fathers employed in information technology (N 1 = 59) and the retail sector (N 2 = 75) participated in micro-longitudinal studies, both for eight consecutive workdays. Study 1 revealed that fathers with more positive interactions with a child also reported more positive mood states and fathers with more positive mood states perceived more social resources from their supervisor during the week. The indirect effect was small but significant. In Study 2, multilevel structural-equation models did not find indirect effects at the within-person level but did show that positive father-child interactions after work were related to fathers' positive mood states before going to bed and positive mood in the morning predicted perceived social resources from supervisors (but not from coworkers) in the forenoon. There were also positive effects of perceived social resources from supervisors on positive mood states, after work. But these did not translate into an increase in positive father-child interactions, in the evening. Hence, only single elements were supported but not the overall resource caravan. Supplementary Information: The online version contains supplementary material available at 10.1007/s10902-022-00523-4.

Estimating Reliability of Within-Person Couplings in a Multilevel Framework.

Within-person couplings play a prominent role in psychological research and previous studies have shown that interindividual differences in within-person couplings predict future behavior. For example, stress reactivity-operationalized as the within-person coupling of stress and positive or negative affect-is an important predictor of various (mental) health outcomes and has often been assumed to be a more or less stable personality trait. However, issues of reliability of these couplings have been largely neglected so far. In this work, we present an estimate for the reliability of within-person couplings that can be easily obtained using the user-modifiable R code accompanying this work. Results of a simulation study show that this index performs well even in the context of unbalanced data due to missing values. We demonstrate the application of this index in a measurement burst study targeting the reliability and test-retest correlation of stress reactivity estimates operationalized as within-person couplings in a daily diary design. Reliability and test-retest correlations of stress reactivity estimates were rather low, challenging the implicit assumption of stress reactivity as a stable person-level variable. We highlight key factors that researchers planning studies targeting interindividual differences in within-person couplings should consider to maximize reliability.

Maternal pro-inflammatory state during pregnancy and newborn leukocyte telomere length: A prospective investigation.

INTRODUCTION: Telomere biology plays a fundamental role in maintaining the integrity of the genome and cell, and shortened telomeres have been linked to several age-related diseases. The initial (newborn) telomere length (TL) represents a critically important feature of the telomere biology system. Exposure to a variety of adverse prenatal conditions such as maternal stress, suboptimal diet, obesity, and obstetric complications, is associated with shorter offspring TL at birth and in adult life. Many, if not all, of these exposures are believed to have an inflammatory component. In this context, stress-related immunological processes during pregnancy may constitute a potential additional biological pathway because they can affect telomere length and telomerase activity via transcriptions factors such as cyclic adenosine monophosphate-dependent transcription factor (ATF7) and nuclear factor-kappa B (NF-κB). Thus, in the present study we examined the hypothesis that maternal pro-inflammatory state across pregnancy, operationalized as the balance between tumor necrosis factor (TNF)-α, a major pro-inflammatory cytokine, and interleukin-10 (IL-10), the major anti-inflammatory cytokine, is associated with newborn leukocyte telomere length (LTL) at birth. METHODS AND MATERIALS: Participants were healthy women (N = 112) recruited in early pregnancy. Concentrations of TNF- α and IL-10 were quantified in early, mid and late pregnancy from maternal blood samples. Telomere length was assessed in newborn blood samples soon after birth. RESULTS: After adjusting for maternal age, maternal pre-pregnancy BMI, birth weight percentile, and infant sex, a higher mean TNF-α/IL-10 ratio across pregnancy was significantly associated with shorter newborn TL (ß = -.205, p = .030). Newborn TL was, on average, 10% shorter in offspring of women in the upper compared to lower quartile of the TNF-α/IL-10 ratio during pregnancy. DISCUSSION: These findings provide new evidence in humans for a potential "programming" mechanism linking maternal systemic pro-inflammatory processes during pregnancy with the initial (newborn) setting of her offspring's telomere system.

General self-efficacy as a driving factor of post-stroke depression: A longitudinal study.

Post-stroke depression (PSD) is the most common psychiatric condition after stroke, affecting one third of survivors. Despite identification of meaningful predictors, knowledge about the interplay between these factors remains fragmentary. General self-efficacy (GSE) is closely linked to PSD, yet direction and magnitude of this relationship remains unclear. The authors assessed the relationship between GSE and depression during the first two years post-stroke while controlling for stable inter-individual differences using continuous time (CT) structural equation modelling (SEM). Patients of two German rehabilitation centres (N = 294, mean age = 63.78 years, SD = 10.83) were assessed six weeks after ischemic stroke and at four follow-ups covering two years. GSE Scale and Geriatric Depression Scale (GDS) were used to assess GSE and depression. CT-analysis revealed significantly higher within-person cross-effects of GSE on GDS (a21 = -.29) than vice versa (a12 = -.17). Maximal cross-lagged effects emerged six months post-stroke. Our results show that decreasing GSE led to increasing depressiveness, and only to a smaller extent vice versa. This suggests that fostering GSE by strengthening perceived control after stroke can counter PSD emersion and exacerbation. Six months post-stroke, when patients face social re-integration, programmes focusing on GSE could potentially help to prevent later PSD.

Fluid intelligence and gross structural properties of the cerebral cortex in middle-aged and older adults: A multi-occasion longitudinal study.

According to Parieto-Frontal Integration Theory (P-FIT, Jung and Haier, 2007), individual differences in a circumscribed set of brain regions account for variations in general intelligence (g). The components of g, fluid (Gf) and crystallized (Gc) reasoning, exhibit distinct trajectories of age-related change. Because the brain also ages differentially, we hypothesized that age-related cognitive and neural changes would be coupled. In a sample of healthy middle-aged and older adults, we examined changes in Gf (operationalized by Cattell Culture Fair Test) and Gc (indexed by two vocabulary tests) as well as in structural properties of 19 brain regions. We fitted linear mixed models to the data collected on 73 healthy adults who participated in baseline assessment, with 43 returning for at least one follow-up, and 16 of them contributing four repeated assessments over seven years. We observed age differences as well as longitudinal decline in Gf, contrasted to a lack of age differences and stability in Gc. Cortical thickness and cortical volume exhibited significant age differences and longitudinal declines, which were accelerated in P-FIT regions. Gf (but not Gc) was associated with cortical thickness, but no such relationship was found for cortical volume. Uniformity of cognitive change (lack of reliable individual differences) precluded examination of the coupling between cognitive and brain changes. Cortical shrinkage was greater in high-Gc individuals, whereas in participants with higher Gf cortical volume slower volume shrinkage was observed.

SEM Based CARMA Time Series Modeling for Arbitrary N.

This article explains in detail the state space specification and estimation of first and higher-order autoregressive moving-average models in continuous time (CARMA) in an extended structural equation modeling (SEM) context for N = 1 as well as N > 1. To illustrate the approach, simulations will be presented in which a single panel model (T = 41 time points) is estimated for a sample of N = 1,000 individuals as well as for samples of N = 100 and N = 50 individuals, followed by estimating 100 separate models for each of the one-hundred N = 1 cases in the N = 100 sample. Furthermore, we will demonstrate how to test the difference between the full panel model and each N = 1 model by means of a subject-group-reproducibility test. Finally, the proposed analyses will be applied in an empirical example, in which the relationships between mood at work and mood at home are studied in a sample of N = 55 women. All analyses are carried out by ctsem, an R-package for continuous time modeling, interfacing to OpenMx.

The Role of Time in the Quest for Understanding Psychological Mechanisms.

The lead-lag structure of multivariate time-ordered observations and the possibility to disentangle between-person (BP) from within-person (WP) sources of variance are major assets of longitudinal (panel) data. Hence, psychologists are making increasing use of such data, often with the intent to delineate the dynamic properties of psychological mechanisms, understood as a sequence of causal effects that govern psychological functioning. However, even with longitudinal data, psychological mechanisms are not easily identified. In this article, we show how an adequate representation of time may enhance the tenability of causal interpretations in the context of multivariate longitudinal data analysis. We anchor our considerations with an example that illustrates some of the main problems and questions faced by applied researchers and practitioners. We distinguish between static versus dynamic and discrete versus continuous time modeling approaches and discuss their advantages and disadvantages. We place particular emphasis on different ways of addressing BP differences and stress their dual role as potential confounds versus valuable sources of information for improving estimation and aiding causal inference. We conclude by outlining an approach that offers the potential of better integration of information on BP differences and WP changes in the search for causal mechanisms along with a discussion of current problems and limitations.

Capturing Context-Related Change in Emotional Dynamics via Fixed Moderated Time Series Analysis.

Much of recent affect research relies on intensive longitudinal studies to assess daily emotional experiences. The resulting data are analyzed with dynamic models to capture regulatory processes involved in emotional functioning. Daily contexts, however, are commonly ignored. This may not only result in biased parameter estimates and wrong conclusions, but also ignores the opportunity to investigate contextual effects on emotional dynamics. With fixed moderated time series analysis, we present an approach that resolves this problem by estimating context-dependent change in dynamic parameters in single-subject time series models. The approach examines parameter changes of known shape and thus addresses the problem of observed intra-individual heterogeneity (e.g., changes in emotional dynamics due to observed changes in daily stress). In comparison to existing approaches to unobserved heterogeneity, model estimation is facilitated and different forms of change can readily be accommodated. We demonstrate the approach's viability given relatively short time series by means of a simulation study. In addition, we present an empirical application, targeting the joint dynamics of affect and stress and how these co-vary with daily events. We discuss potentials and limitations of the approach and close with an outlook on the broader implications for understanding emotional adaption and development.

The Subjective Health Horizon Questionnaire (SHH-Q): Assessing Future Time Perspectives for Facets of an Active Lifestyle.

BACKGROUND: A wider subjective time horizon is assumed to be positively associated with longevity and vitality. In particular, a lifestyle with exposure to novel and varied information is considered beneficial for healthy cognitive aging. At present, measures that specifically assess individuals' perceived temporal extension to engage in active lifestyles in the future are not available. OBJECTIVES: We introduce and validate a new self-report measure, the Subjective Health Horizon Questionnaire (SHH-Q). The SHH-Q assesses individuals' future time perspectives in relation to four interrelated but distinct lifestyle dimensions: (1) novelty-oriented exploration (Novelty), (2) bodily fitness (Body), (3) work goals (Work), and (4) goals in life (Life Goals). The present study aims at: (a) validating the hypothesized factor structure of the SHH-Q, according to which the SHH-Q consists of four interrelated but distinct subscales, and (b) testing the hypothesis that the Novelty and Body subscales of the SHH-Q show positive and selective associations with markers of cognition and somatic health, respectively. METHODS: Using structural equation modeling, we analyzed data from 1,371 healthy individuals (51% women) with a mean age of 70.1 years (SD = 3.6) who participated in the Berlin Aging Study II (BASE-II) and completed the SHH-Q. RESULTS: As predicted, the SHH-Q formed four correlated but distinct subscales: (1) Novelty, (2) Body, (3) Work, and (4) Life Goals. Greater self-reported future novelty orientation was associated with higher current memory performance, and greater future expectations regarding bodily fitness with better current metabolic status. CONCLUSION: The SHH-Q reliably assesses individual differences in four distinct dimensions of future time perspective. Two of these dimensions, Novelty and Body, show differential associations with cognitive status and somatic health. The SHH-Q may serve as a tool to assess how different facets of future time perspective relate to somatic health, cognition, motivation, and affect, and may help to identify the socioeconomic and individual antecedents, correlates, and consequences of an active lifestyle.

Toward a Unified Framework for the Study of Between-Person and Within-Person Structures: Building a Bridge Between Two Research Paradigms.

The vast majority of empirical research in the behavioral sciences is based on the analysis of between-person variation. In contrast, much of applied psychology is concerned with the analysis of variation within individuals. Furthermore, the mechanisms specified by psychological theories generally operate within, rather than across, individuals. This disconnect between research practice, applied demands, and psychological theories constitutes a major threat to the conceptual integrity of the field. Following groundbreaking earlier work, we propose a conceptual framework that distinguishes within-person (WP) and between-person (BP) sources of variation in psychological constructs. By simultaneously considering both sources of variation, it is shown how to identify possible reasons for nonequivalence of BP and WP structures as well as establishing areas of convergence. For this purpose, we first introduce the concept of conditional equivalence as a way to study partial structural equivalence of BP and WP structures in the presence of unconditional nonequivalence. Second, we demonstrate the construction of likelihood planes to explore the causes of structural nonequivalence. Third, we examine 4 common causes for unconditional nonequivalence-autoregression, subgroup differences, linear trends, and cyclic trends-and demonstrate how to account for them. Fourth, we provide an empirical example on BP and WP differences in attentiveness.

Reducing neuroendocrine psychosocial stress response through socio-emotional dyadic but not mindfulness online training.

Introduction: Stress-related diseases pose significant health risks and show wide prevalence. Empirical evidence suggests that contemplative practices, such as socio-emotional dyadic mental exercises, hold promise in mitigating the adverse effects of stress and promoting psychosocial well-being. This study aimed to investigate the differential effects of two online contemplative mental training programs on the psychosocial stress response: the first involved classic mindfulness practices, while the second incorporated a socio-emotional dyadic approach known as Affect Dyad. Methods: The study was conducted as part of the longitudinal CovSocial project's phase 2 in the context of the COVID-19 pandemic. 140 individuals participated in the Trier Social Stress Task (TSST), where the psychosocial stress response was assessed with cortisol saliva samples and subjective stress questionnaires in a cross-sectional design after the active training groups finished their intervention period. Participants were randomly assigned to the socio-emotional training group, mindfulness-based training group, or a control group that did not receive any training. Both training programs consisted of a ten-week intervention period with a daily 12-minute app-based mental training practice and weekly 2-hour online coaching sessions led by mental training teachers. Results: Results showed that the socio-emotional Dyad group but not the mindfulness-based group exhibited significantly lower cortisol levels at 10, 20, 30, and 40 minutes after the stressor as well as lower total cortisol output compared to the control group during the TSST, indicating a reduced hormonal stress response to a social stressor. Subjective markers did not show differences between the three groups. Discussion: These findings indicate that the daily socio-emotional dyadic practice, which emphasizes non-judgmental and empathic listening as well as the acceptance of challenging emotions in the presence of others within one's daily life context, may serve as a protective factor against the adverse effects of psychosocial stress triggered by the fear of negative social judgments. Given the high prevalence of stress-related diseases, such online mental training programs based on dyadic practices may thus represent an efficient and scalable approach for stress reduction.

Reducing Loneliness through the Power of Practicing Together: A Randomized Controlled Trial of Online Dyadic Socio-Emotional vs. Mindfulness-Based Training.

Loneliness has become a pressing topic, especially among young adults and during the COVID-19 pandemic. In a randomized controlled trial with 253 healthy adults, we evaluated the differential efficacy of two 10-week app-delivered mental training programs: one based on classic mindfulness and one on an innovative partner-based socio-emotional practice (Affect Dyad). We show that the partner-based training resulted in greater reductions in loneliness than the mindfulness-based training. This effect was shown on three measures of loneliness: general loneliness assessed with the 20-item UCLA Loneliness Scale, state loneliness queried over an 8-day ecological momentary assessment in participants' daily lives, and loneliness ratings required before and after daily practice. Our study provides evidence for the higher efficacy of a mental training approach based on a 12 min practice conducted with a partner in reducing loneliness and provides a novel, scalable online approach to reduce the increasing problem of loneliness in society.

Reliability, validity, and measurement invariance of the German version of the physical activity enjoyment scale.

OBJECTIVE: The purpose of this work is to examine reliability, factorial- and criterion-related validity, and measurement invariance across age and gender of the Physical Activity Enjoyment Scale for children and adolescents in the German-speaking population. METHODS: Confirmatory factor analysis was applied to questionnaire responses obtained from a cross-sectional sample (Study 1) of 250 girls and 254 boys and a longitudinal sample (Study 2) of 109 boys and 87 girls aged 9 to 17 years. RESULTS: Results indicated sufficient test-retest reliability (ICC = 0.76), internal consistency (α = 0.89), and criterion-related validity (r = 0.42 with a physical activity diary; r = 0.16 with accelerometry data). Confirmatory factor analyses partially supported the factorial validity and invariance. CONCLUSIONS: The German version of the Physical Activity Enjoyment Scale is sufficiently reliable and valid to be used for German-speaking children and adolescents. Further research examining the invariance over a longer period is warranted.

Regularized continuous time structural equation models: A network perspective.

Regularized continuous time structural equation models are proposed to address two recent challenges in longitudinal research: Unequally spaced measurement occasions and high model complexity. Unequally spaced measurement occasions are part of most longitudinal studies, sometimes intentionally (e.g., in experience sampling methods) sometimes unintentionally (e.g., due to missing data). Yet, prominent dynamic models, such as the autoregressive cross-lagged model, assume equally spaced measurement occasions. If this assumption is violated parameter estimates can be biased, potentially leading to false conclusions. Continuous time structural equation models (CTSEM) resolve this problem by taking the exact time point of a measurement into account. This allows for any arbitrary measurement scheme. We combine CTSEM with LASSO and adaptive LASSO regularization. Such regularization techniques are especially promising for the increasingly complex models in psychological research, the most prominent example being network models with often dozens or hundreds of parameters. Here, LASSO regularization can reduce the risk of overfitting and simplify the model interpretation. In this article we highlight unique challenges in regularizing continuous time dynamic models, such as standardization or the optimization of the objective function, and offer different solutions. Our approach is implemented in the R (R Core Team, 2022) package regCtsem. We demonstrate the use of regCtsem in a simulation study, showing that the proposed regularization improves the parameter estimates, especially in small samples. The approach correctly eliminates true-zero parameters while retaining true-nonzero parameters. We present two empirical examples and end with a discussion on current limitations and future research directions. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Intra-Subject Variability, Intelligence, and ADHD Traits in a Community-Based Sample.

OBJECTIVE: The present study investigates the predictive validity of intra-subject variability (ISV) for ADHD traits in a community-based sample and the stability of the relationship between ISV and fluid intelligence (gf) across the continuum of ADHD traits. METHOD: Age-residualized data from 426 participants (8-18 years, 6% ADHD) was used to investigate whether ex-Gaussian and DDM parameters derived from simple choice-reaction-time tasks can predict continuously assessed ADHD traits. Multiple-Group-Analyses and Latent-Moderated-Structural-Equations were used to test whether ADHD traits moderate the relationship between ISV and gf. RESULTS: σ and µ of the ex-Gaussian model as well as DDM parameters drift rate (v) and boundary separation (a) significantly predicted general ADHD traits, while τ predicted attention difficulties specifically. Across the ADHD continuum, σ and v were significant predictors of gf. CONCLUSION: The results confirm the link between ISV and ADHD. The relationship between ISV and gf appears stable across the ADHD continuum.