The General Psychopathology Factor: Structural Stability and Generalizability to Within-Individual Changes

Associations between Computationally Derived Parent Emotional Sentiment Scores and Child ADHD and ODD Over Time

Family emotional climate is often assessed as expressed emotion (EE) using the five-minute speech sample (FMSS). Parent EE is related to child externalizing behavior, but the relationship with ADHD apart from externalizing is unclear. We report the largest ADHD-non-ADHD study of EE to date, introduce computational scoring of the FMSS to assay parent negative sentiment, and use this to evaluate reciprocal parent-child effects over time in ADHD while considering comorbid ODD. Parents of 810 children (nADHD = 509), aged 7-13 years old, completed the FMSS at three points. The FMSS was expert-coded for EE-Criticism at Time 1 and Time 2, negative sentiment was scored at all three time points. Sentiment and EE-Criticism were moderately correlated (r =.39, p <.001, 95% CI [0.32, 0.46]), and each was similarly correlated with baseline ADHD symptoms (r's range 0.31-0.33, p <.001) and ODD symptoms (r(ODD-EE) = 0.35, p <.001; r(ODD-sentiment = 0.28, p <.001). A longitudinal, cross-lagged panel model revealed that increases over time in parental negative sentiment scores led to increased ODD symptoms. Parent sex (namely fathers, but not mothers) showed an interaction effect of sentiment with ADHD. ADHD and ODD are independently and jointly associated with parental EE-Criticism and negative sentiment assessed by the FMSS cross-sectionally. A recursive effects model is supported for ODD, but for ADHD effects depend on which parent is assessed. For fathers, ADHD was related to negative sentiment in complex manners but for mothers, negative sentiment was related primarily to ODD.

Bifactor models of psychopathology using multi-informant and multi-instrument dimensional measures in the ABCD study

Background

Due to limitations of categorical definitions of mental illness, there is a need for quantitative empirical investigations of the dimensional structure of psychopathology. Using exploratory bifactor methods, this study investigated a comprehensive and representative structure of psychopathology in children to better understand how psychotic-like experiences (PLEs), autism spectrum disorder (ASD) symptoms, impulsivity, and sensitivity to reward and punishment, may be integrated into extant general factor models of psychopathology.

Methods

We used seven child-report and three parent-report instruments capturing diverse mental health symptoms in 11,185 children aged 9-10 from the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study. We built on previous modeling frameworks by conducting both split sample and full sample factor analytic approaches that harnessed recent methodological advances in bifactor exploratory structural equation modeling (B-ESEM) to examine a wide range of psychopathology measures not previously integrated into a single analysis. Validity of psychopathology dimensions was examined by investigating associations with sex, age, cognition, imaging measures, and medical service usage.

Results

All four factor analytic models showed excellent fit and similar structure within informant. PLEs loaded most highly onto a general psychopathology factor, suggesting that they may reflect non-specific risk for mental illness. ASD symptoms loaded separately from attention/hyperactivity symptoms. Symptoms of impulsivity and sensitivity to reward and punishment loaded onto specific factors, distinct from externalizing and internalizing factors. All identified factors were associated with clinically relevant risk factors, providing preliminary evidence for their construct validity.

Conclusion

By integrating diverse child-report and parent-report psychopathology measures for children in the ABCD sample, we deliver data on the quantitative structure of psychopathology for an exceptionally large set of measurements and discuss implications for the field.

Measurement Invariance in Longitudinal Bifactor Models: Review and Application Based on the p Factor

Bifactor models are increasingly being utilized to study latent constructs such as psychopathology and cognition, which change over the lifespan. Although longitudinal measurement invariance (MI) testing helps ensure valid interpretation of change in a construct over time, this is rarely and inconsistently performed in bifactor models. Our review of MI simulation literature revealed that only one study assessed MI in bifactor models under limited conditions. Recommendations for how to assess MI in bifactor models are suggested based on existing simulation studies of related models. Estimator choice and influence of missing data on MI are also discussed. An empirical example based on a model of the general psychopathology factor (p) elucidates our recommendations, with the present model of p being the first to exhibit residual MI across gender and time. Thus, changes in the ordered-categorical indicators can be attributed to changes in the latent factors. However, further work is needed to clarify MI guidelines for bifactor models, including considering the impact of model complexity and number of indicators. Nonetheless, using the guidelines justified herein to establish MI allows findings from bifactor models to be more confidently interpreted, increasing their comparability and utility.

Common Cause Versus Dynamic Mutualism: An Empirical Comparison of Two Theories of Psychopathology in Two Large Longitudinal Cohorts

Mental disorders are among the leading causes of global disease burden. To respond effectively, a strong understanding of the structure of psychopathology is critical. We empirically compared two competing frameworks, dynamic-mutualism theory and common-cause theory, that vie to explain the development of psychopathology. We formalized these theories in statistical models and applied them to explain change in the general factor of psychopathology (p factor) from early to late adolescence (N = 1,482) and major depression in middle adulthood and old age (N = 6,443). Change in the p factor was better explained by mutualism according to model-fit indices. However, a core prediction of mutualism was not supported (i.e., predominantly positive causal interactions among distinct domains). The evidence for change in depression was more ambiguous. Our results support a multicausal approach to understanding psychopathology and showcase the value of translating theories into testable statistical models for understanding developmental processes in clinical sciences.

Reactive and control processes in the development of internalizing and externalizing problems across early childhood to adolescence

Reactive and control processes - e.g., negative emotionality and immediacy preference - may predict distinct psychopathology trajectories. However, externalizing and internalizing problems change in behavioral manifestation across development and across contexts, thus necessitating the use of different measures and informants across ages. This is the first study that created developmental scales for both internalizing and externalizing problems by putting scores from different informants and measures onto the same scale to examine temperament facets as risk factors. Multidimensional linking allowed us to examine trajectories of internalizing and externalizing problems from ages 2 to 15 years (N = 1,364) using near-annual ratings by mothers, fathers, teachers, other caregivers, and self report. We examined reactive and control processes in early childhood as predictors of the trajectories and as predictors of general versus specific psychopathology in adolescence. Negative emotionality at age 4 predicted general psychopathology and unique externalizing problems at age 15. Wait times on an immediacy preference task at age 4 were negatively associated with age 15 general psychopathology, and positively associated with unique internalizing problems. Findings demonstrate the value of developmental scaling for examining development of psychopathology across a lengthy developmental span and the importance of considering reactive and control processes in development of psychopathology.

A Developmentally Informed Systematic Review and Meta-Analysis of the Strength of General Psychopathology in Childhood and Adolescence

Considerable support exists for higher-order dimensional conceptualizations of psychopathology in adults. A growing body of work has focused on understanding the structure of general and specific psychopathology in children and adolescents. No prior meta-analysis has examined whether the strength of the general psychopathology factor (p factor)-measured by explained common variance (ECV)-changes from childhood to adolescence. The primary objective of this multilevel meta-analysis was to determine whether general psychopathology strength changes across development (i.e. across ages) in childhood and adolescence. Several databases were searched in November 2021; 65 studies, with 110 effect sizes (ECV), nested within shared data sources, were identified. Included empirical studies used a factor analytic modeling approach that estimated latent factors for child/adolescent internalizing, externalizing, and optionally thought-disordered psychopathology, and a general factor. Studies spanned ages 2-17 years. Across ages, general psychopathology explained over half (~ 56%) of the reliable variance in symptoms of psychopathology. Age-moderation analyses revealed that general factor strength remained stable across ages, suggesting that general psychopathology strength does not significantly change across childhood to adolescence. Even if the structure of psychopathology changes with development, the prominence of general psychopathology across development has important implications for future research and intervention.

Factor and network analysis of psychosis-like experiences and depressive symptoms in a sample of Finnish adolescents entering psychiatric services

AIM

Psychosis-Like Experiences (PLEs) and depressive symptoms are correlated in clinical adolescent populations. However, symptom-level associations between the two phenomena are not clear.

METHODS

We analysed factor structures of a PLE instrument, the Prodromal Questionnaire-Brief (PQ-B), based on dimensions of positive symptoms of schizophrenia, and a depression measurement instrument, the Beck Depression Inventory (BDI-21A) and performed a network analysis of item-level associations between the two measures. The sample consisted of 417 adolescents (range 13-18 years of age, mean 14.9 years, 72.4% females) entering secondary psychiatric services at Helsinki metropolitan area, Finland.

RESULTS

Confirmatory factor analysis resulted in adequately fitting 2-factor solution, one for PQ-B and one for BDI-21, with a strong correlation coefficient of 0.605 between the two factors. In the network analysis, PQ-B and BDI-21 both formed their own clusters, and two significant pathways were estimated between PQ-B and BDI-21 clusters: 1. the association between paranoid thinking and distorted body image, and 2. the association between somatic preoccupation and worry about problems of one's mind.

CONCLUSIONS

Even though on a general, factor level, PLEs and depressive symptoms were strongly correlated, unique associations between symptoms of the two constructs were sparse. These findings should be considered in the psychiatric assessment and in the care of adolescents.

The relationship between general psychopathology in young people with family functioning and engagement with psychotherapy

OBJECTIVE

to examine whether an underlying general psychopathology factor (p factor) existed in children and adolescents attending psychodynamic psychotherapy and whether this general psychopathology factor was associated with family functioning and engagement with psychotherapy.

METHOD

Participants were 1976 children and adolescents, and their families, who sought psychodynamic psychotherapy from a community-based clinic in Southern Brazil. The Child Behavior Checklist and the Family Adaptability and Cohesion Evaluation Scales for assessing symptoms and family functioning were used, with treatment engagement data available through linked records. Confirmatory factor analytic methods examined psychopathology and regression models were constructed to examine associations.

RESULTS

A general psychopathology factor and specific internalizing and externalizing factors were identified. Higher general psychopathology scores at assessment were associated with an increased likelihood of dropout and poorer attendance compared to completing treatment. Father's educational level, living with both parents, lack of family adaptability and cohesion, and maltreatment experience were related to increased p factor severity.

CONCLUSION

General psychopathology severity seems to contribute to child and adolescent psychotherapy outcomes, increasing the risk of non-adherence and dropout. Family difficulties and traumatic experiences may increase p factor severity. Identifying general psychopathology routinely can be crucial for developing effective treatment plans.

Direction of dependence analysis for pre-post assessments using non-Gaussian methods: a tutorial

OBJECTIVE

We introduced methods for solving causal direction of dependence between variables observed in pre- and post-psychotherapy assessments, showing how to apply them and investigate their properties via simulations. In addition, we investigated whether changes in depressive symptoms drive changes in social and occupational functioning as suggested by the phase model of psychotherapy or vice versa, or neither.

METHOD

As a Gaussian (normal-distribution) model is unidentifiable here, we used an identifiable linear non-Gaussian structural vector autoregression model, conceptualizing instantaneous effects as during-psychotherapy causation and lagged effects as pre-treatment predictors of change. We tested six alternative estimators in six simulation settings that captured different real-world scenarios, and used real psychotherapy data from 1428 adult patients (Finnish Psychotherapy Quality Registry; assessments on Patient Health Questionnaire-9 and Social and Occupational Functioning Assessment Schedule).

RESULTS

The methodology was successful in identifying causal directions in simulated data. The real-data results provided no evidence for single direction of dependence, suggesting shared or reciprocal causation.

CONCLUSIONS

A powerful new tool was presented to investigate the process of psychotherapy using observational data. Application to patient data suggested that depression symptoms and functioning may reciprocate or reflect third variables instead of one predominantly driving the other during psychotherapy.

Measurement Invariant but Non-Normal Treatment Responses in Guided Internet Psychotherapies for Depressive and Generalized Anxiety Disorders

Assessment of treatment response in psychotherapies can be undermined by lack of longitudinal measurement invariance (LMI) in symptom self-report inventories, by measurement error, and/or by wrong model assumptions. To understand and compare these threats to validity of outcome assessment in psychotherapy research, we studied LMI, sum scores, and Davidian Curve Item Response Theory models in a naturalistic guided internet psychotherapy treatment register of 2,218 generalized anxiety disorder (GAD) patients and 3,922 depressive disorder (DD) patients (aged ≥16 years). Symptoms were repeatedly assessed by Generalized Anxiety Disorder Assessment-7 (GAD-7) or Beck Depression Inventory. The symptom self-reports adhered to LMI under equivalence testing, suggesting sum scores are reasonable proxies for disorder status. However, the standard LMI assumption of normally distributed latent factors did not hold and inflated treatment response estimates by 0.2 to 0.3 standard deviation units compared with sum scores. Further methodological research on non-normally distributed latent constructs holds promise in advancing LMI and mental health assessment.

On the Meaning of the "P Factor" in Symmetrical Bifactor Models of Psychopathology: Recommendations for Future Research From the Bifactor-(S-1) Perspective

Symmetrical bifactor models are frequently applied to diverse symptoms of psychopathology to identify a general P factor. This factor is assumed to mark shared liability across all psychopathology dimensions and mental disorders. Despite their popularity, however, symmetrical bifactor models of P often yield anomalous results, including but not limited to nonsignificant or negative specific factor variances and nonsignificant or negative factor loadings. To date, these anomalies have often been treated as nuisances to be explained away. In this article, we demonstrate why these anomalies alter the substantive meaning of P such that it (a) does not reflect general liability to psychopathology and (b) differs in meaning across studies. We then describe an alternative modeling framework, the bifactor-(S-1) approach. This method avoids anomalous results, provides a framework for explaining unexpected findings in published symmetrical bifactor studies, and yields a well-defined general factor that can be compared across studies when researchers hypothesize what construct they consider "transdiagnostically meaningful" and measure it directly. We present an empirical example to illustrate these points and provide concrete recommendations to help researchers decide for or against specific variants of bifactor structure.

Assessing severity in anorexia nervosa: Do the DSM-5 and an alternative severity rating based on overvaluation of weight and shape severity differ in psychological and biological correlates?

OBJECTIVE

This study evaluated the severity ratings for anorexia nervosa (AN) in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and an alternative severity rating based on overvaluation of weight/shape, on a range of psychological and biological variables.

METHOD

A sample of 312 treatment-seeking patients with AN (mean age = 25.3, SD = 7.6; mean BMI = 16.8 kg/m² , SD = 2.4) were categorised using both DSM-5 severity levels (mild/moderate/severe/extreme) and weight/shape (low/high) overvaluation. The severity categories were compared on a range of psychological (e.g., eating psychopathology) and biological (e.g., sodium) variables.

RESULTS

Results showed that the overvaluation of weight/shape appeared better at indexing the level of severity in psychological variables among patients with AN compared to the DSM-5 severity rating with moderate to large effect sizes. Moreover, the DSM-5 mild and moderate severity groups experienced significantly higher eating and general psychopathology than the severe and extreme groups. Finally, neither the DSM-5 nor the weight/shape severity groups differed on any of the biological variables.

CONCLUSIONS

This study provided no support for the DSM-5 severity rating for AN, while initial support was found for the weight/shape overvaluation approach in indexing psychological but not biological correlates.

Meta-analysis of structural evidence for the Hierarchical Taxonomy of Psychopathology (HiTOP) model

BACKGROUND

The Hierarchical Taxonomy of Psychopathology (HiTOP) is a classification system that seeks to organize psychopathology using quantitative evidence - yet the current model was established by narrative review. This meta-analysis provides a quantitative synthesis of literature on transdiagnostic dimensions of psychopathology to evaluate the validity of the HiTOP framework.

METHODS

Published studies estimating factor-analytic models from diagnostic and statistical manual of mental disorders (DSM) diagnoses were screened. A total of 120,596 participants from 35 studies assessing 23 DSM diagnoses were included in the meta-analytic models. Data were pooled into a meta-analytic correlation matrix using a random effects model. Exploratory factor analyses were conducted using the pooled correlation matrix. A hierarchical structure was estimated by extracting one to five factors representing levels of the HiTOP framework, then calculating congruence coefficients between factors at sequential levels.

RESULTS

Five transdiagnostic dimensions fit the DSM diagnoses well (comparative fit index = 0.92, root mean square error of approximation = 0.07, and standardized root-mean-square residual = 0.03). Most diagnoses had factor loadings >|0.30| on the expected factors, and congruence coefficients between factors indicated a hierarchical structure consistent with the HiTOP framework.

CONCLUSIONS

A model closely resembling the HiTOP framework fit the data well and placement of DSM diagnoses within transdiagnostic dimensions were largely confirmed, supporting it as valid structure for conceptualizing and organizing psychopathology. Results also suggest transdiagnostic research should (1) use traits, narrow symptoms, and dimensional measures of psychopathology instead of DSM diagnoses, (2) assess a broader array of constructs, and (3) increase focus on understudied pathologies.

Which symptoms are the psychopathological core affecting the manifestation of pseudo-cardiac symptoms and poor sleep quality in young adults? Symptoms of personality disorders versus clinical disorders

Background

Diagnosing and identifying the psychological origin of pseudo-cardiac symptoms and comorbid conditions such as poor sleep quality is very difficult due to its extensive and complex nature. The present study was conducted to determine the contribution of symptoms of personality disorders (PDs) and clinical disorders (CDs; i.e., psychological symptoms measured using the Symptom Checklist-90) to the manifestation of pseudo-cardiac symptoms and poor sleep quality.

Methods

Subjects in this cross-sectional study were 953 (64.3% female; 28.8 ± 6.2 years) community samples in the west of Iran who were selected by convenience sampling. After applying the inclusion criteria, data were collected using the Symptom Checklist-90 (SCL-90-R), the Personality Diagnostic Questionnaire (PDQ-4), and the Scale for Pseudo-Cardiac Symptoms and Poor Sleep Quality (SPSQ). Pearson correlations, factor analytical techniques, and hierarchical regression models were used to examine associations between symptoms of PDs/CDs and outcome factors.

Results

Factor analytical techniques confirmed both the integrated structure of symptoms of PDs and CDs. Both pseudo-cardiac symptoms and poor sleep quality were more strongly associated with symptoms of CDs than PDs. The results of the hierarchical analysis show that the CDs factor alone could explain the total variance of both pseudo-cardiac symptoms (change in R² = 0.215 vs. 0.009; p < 0.001) and poor sleep quality (change in R² = 0.221 vs. 0.001; p < 0.001).

Conclusion

The different capabilities of two unique factors for the symptoms of PDs and CDs were confirmed by factor analytical methods and regression analysis techniques. Although each of the symptoms of PDs and CDs independently contributes to the manifestation of pseudo-cardiac symptoms and poor sleep quality, the CDs factor is the psychopathological core.

Deep learning in neuroimaging data analysis: Applications, challenges, and solutions

Methods for the analysis of neuroimaging data have advanced significantly since the beginning of neuroscience as a scientific discipline. Today, sophisticated statistical procedures allow us to examine complex multivariate patterns, however most of them are still constrained by assuming inherent linearity of neural processes. Here, we discuss a group of machine learning methods, called deep learning, which have drawn much attention in and outside the field of neuroscience in recent years and hold the potential to surpass the mentioned limitations. Firstly, we describe and explain the essential concepts in deep learning: the structure and the computational operations that allow deep models to learn. After that, we move to the most common applications of deep learning in neuroimaging data analysis: prediction of outcome, interpretation of internal representations, generation of synthetic data and segmentation. In the next section we present issues that deep learning poses, which concerns multidimensionality and multimodality of data, overfitting and computational cost, and propose possible solutions. Lastly, we discuss the current reach of DL usage in all the common applications in neuroimaging data analysis, where we consider the promise of multimodality, capability of processing raw data, and advanced visualization strategies. We identify research gaps, such as focusing on a limited number of criterion variables and the lack of a well-defined strategy for choosing architecture and hyperparameters. Furthermore, we talk about the possibility of conducting research with constructs that have been ignored so far or/and moving toward frameworks, such as RDoC, the potential of transfer learning and generation of synthetic data.

Dimensionality of narcissism: a Bifactorial model of the Narcissistic Personality Inventory using single-stimulus response formats

The Narcissistic Personality Inventory is a widely used measure of narcissism; however, several different conflicting factor structures have been proposed. The present study aimed to untangle those differences by offering a bifactor model of narcissism with an underlying general narcissism factor and several specific factors. Our objective was to estimate the variance explained by the general and the specific factors. Therefore, we applied a set of confirmatory factor analyses on three independent studies (N = 791; N = 319 and N = 237), and also tested the construct validity of these factors with other contemporary measures of grandiose and vulnerable narcissism, big five personality traits, explicit self-esteem, gender and well-being. Our results suggest that the bifactor model with three specific factors yielded acceptable fit to our data in all of the different single-stimulus response formats and languages used in our studies and modelling three specific factors offered more insight into the adaptive and maladaptive characteristics of narcissism. The general narcissism factor alone explains only about half of the common variance, highlighting the importance of the specific factors as well.

Feasibility of generic, short, and easy-to-use assessment of psychological distress during psychotherapy: Longitudinal measurement invariance of CORE-10 and -OM

Objective: While the CORE-10 inventory for Clinical Outcome Routine Evaluation has shown good psychometric properties in cross-sectional assessment, the feasibility of generic, short, and easy-to-use longitudinal assessment of a broadband construct such as the targeted "general psychological distress" remains to be psychometrically demonstrated. Therefore, we investigated longitudinal measurement invariance (LMI) of CORE-10. For comprehensiveness, we also analyzed its parent inventory, CORE-OM.

Method: We investigated the LMI of pre- and post-therapy CORE-10 and -OM assessments in a naturalistic treatment register of 1715 patients' short psychotherapies, testing whether the construct of "psychological distress" remained the same across the treatments.

Results: We observed good psychometric properties and no violations of LMI for CORE-10 in chi-squared equivalence tests, nor in effect-size-based evaluations. Only the highly sensitive chi-squared difference tests detected LMI violations but these had little practical influence. The CORE-OM data did not fit well with factorial models but this was cross-sectional rather than a genuinely longitudinal (LMI-related) issue.

Conclusions: CORE-10 appeared a structurally valid measure of general psychological distress and suitable for longitudinal assessment, whereas the CORE-OM had a less clear factorial structure. Regarding psychometrics, these findings support the use of CORE-10 in longitudinal assessment during psychotherapy and do not support CORE-OM.

Reliability and validity of bifactor models of dimensional psychopathology in youth

Bifactor models are a promising strategy to parse general from specific aspects of psychopathology in youth. Currently, there are multiple configurations of bifactor models originating from different theoretical and empirical perspectives. We aimed to test the reliability, validity, measurement invariance, and the correlation of different bifactor models of psychopathology using the Child Behavior Checklist (CBCL). We used data from the Reproducible Brain Charts (RBC) initiative (N = 7,011, ages 5 to 22 years, 40.2% females). Factor models were tested using the baseline data. To address our aim, we (a) searched for the published item-level bifactor models using the CBCL; (b) tested their global model fit; (c) calculated model-based reliability indices; (d) tested associations with symptoms' impact in everyday life; (e) tested measurement invariance across many characteristics, and (f) analyzed the observed factor correlation across the models. We found 11 bifactor models ranging from 39 to 116 items. Their global model fit was broadly similar. Factor determinacy and H index were acceptable for the p-factors, internalizing, externalizing, and somatic specific factors in most models. However, only the p- and attention factors predicted daily life symptoms' impact in all models. Models were broadly invariant across different characteristics. P-factors were highly correlated across models (r = .88 to .99) and homotypic specific factors were highly correlated. These results suggest that regardless of item selection and strategy to compose CBCL bifactor models, they assess very similar constructs. Taken together, our results support the robustness of the p-factor across distinct bifactor models and studies of distinct characteristics. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Parenting in the Context of the Child: Genetic and Social Processes

The focus on the role of parenting in child development has a long-standing history. When measures of parenting precede changes in child development, researchers typically infer a causal role of parenting practices and attitudes on child development. However, this research is usually conducted with parents raising their own biological offspring. Such research designs cannot account for the effects of genes that are common to parents and children, nor for genetically influenced traits in children that influence how they are parented and how parenting affects them. The aim of this monograph is to provide a clearer view of parenting by synthesizing findings from the Early Growth and Development Study (EGDS). EGDS is a longitudinal study of adopted children, their birth parents, and their rearing parents studied across infancy and childhood. Families (N = 561) were recruited in the United States through adoption agencies between 2000 and 2010. Data collection began when adoptees were 9 months old (males = 57.2%; White 54.5%, Black 13.2%, Hispanic/Latinx 13.4%, Multiracial 17.8%, other 1.1%). The median child age at adoption placement was 2 days (M = 5.58, SD = 11.32). Adoptive parents were predominantly in their 30s, White, and coming from upper-middle- or upper-class backgrounds with high educational attainment (a mode at 4-year college or graduate degree). Most adoptive parents were heterosexual couples, and were married at the beginning of the project. The birth parent sample was more racially and ethnically diverse, but the majority (70%) were White. At the beginning of the study, most birth mothers and fathers were in their 20s, with a mode of educational attainment at high school degree, and few of them were married. We have been following these family members over time, assessing their genetic influences, prenatal environment, rearing environment, and child development. Controlling for effects of genes common to parents and children, we confirmed some previously reported associations between parenting, parent psychopathology, and marital adjustment in relation to child problematic and prosocial behavior. We also observed effects of children's heritable characteristics, characteristics thought to be transmitted from parent to child by genetic means, on their parents and how those effects contributed to subsequent child development. For example, we found that genetically influenced child impulsivity and social withdrawal both elicited harsh parenting, whereas a genetically influenced sunny disposition elicited parental warmth. We found numerous instances of children's genetically influenced characteristics that enhanced positive parental influences on child development or that protected them from harsh parenting. Integrating our findings, we propose a new, genetically informed process model of parenting. We posit that parents implicitly or explicitly detect genetically influenced liabilities and assets in their children. We also suggest future research into factors such as marital adjustment, that favor parents responding with appropriate protection or enhancement. Our findings illustrate a productive use of genetic information in prevention research: helping parents respond effectively to a profile of child strengths and challenges rather than using genetic information simply to identify some children unresponsive to current preventive interventions.

Is executive dysfunction a risk marker or consequence of psychopathology? A test of executive function as a prospective predictor and outcome of general psychopathology in the adolescent brain cognitive development study®

A general psychopathology ('p') factor captures shared variation across mental disorders. One hypothesis is that poor executive function (EF) contributes to p. Although EF is related to p concurrently, it is unclear whether EF predicts or is a consequence of p. For the first time, we examined prospective relations between EF and p in 9845 preadolescents (aged 9-12) from the Adolescent Brain Cognitive Development Study® longitudinally over two years. We identified higher-order factor models of psychopathology at baseline and one- and two-year follow-up waves. Consistent with previous research, a cross-sectional inverse relationship between EF and p emerged. Using residualized-change models, baseline EF prospectively predicted p factor scores two years later, controlling for prior p, sex, age, race/ethnicity, parental education, and family income. Baseline p factor scores also prospectively predicted change in EF two years later. Tests of specificity revealed that bi-directional prospective relations between EF and p were largely generalizable across externalizing, internalizing, neurodevelopmental, somatization, and detachment symptoms. EF consistently predicted change in externalizing and neurodevelopmental symptoms. These novel results suggest that executive dysfunction is both a risk marker and consequence of general psychopathology. EF may be a promising transdiagnostic intervention target to prevent the onset and maintenance of psychopathology.

Genome-wide DNA methylation patterns associated with general psychopathology in children

Psychiatric symptoms are interrelated and found to be largely captured by a general psychopathology factor (GPF). Although epigenetic mechanisms, such as DNA methylation (DNAm), have been linked to individual psychiatric outcomes, associations with GPF remain unclear. Using data from 440 children aged 10 years participating in the Generation R Study, we examined the associations of DNAm with both general and specific (internalizing, externalizing) factors of psychopathology. Genome-wide DNAm levels, measured in peripheral blood using the Illumina 450K array, were clustered into wider co-methylation networks ('modules') using a weighted gene co-expression network analysis. One co-methylated module associated with GPF after multiple testing correction, while none associated with the specific factors. This module comprised of 218 CpG probes, of which 198 mapped onto different genes. The CpG most strongly driving the association with GPF was annotated to FZD1, a gene that has been implicated in schizophrenia and wider neurological processes. Associations between the probes contained in the co-methylated module and GPF were supported in an independent sample of children from the Avon Longitudinal Study of Parents and Children (ALSPAC), as evidenced by significant correlations in effect sizes. These findings might contribute to improving our understanding of dynamic molecular processes underlying complex psychiatric phenotypes.

Association of Air Pollution Exposure in Childhood and Adolescence With Psychopathology at the Transition to Adulthood

IMPORTANCE

Air pollution exposure damages the brain, but its associations with the development of psychopathology are not fully characterized.

OBJECTIVE

To assess whether air pollution exposure in childhood and adolescence is associated with greater psychopathology at 18 years of age.

DESIGN, SETTING, AND PARTICIPANTS

The Environmental-Risk Longitudinal Twin Study is a population-based cohort study of 2232 children born from January 1, 1994, to December 4, 1995, across England and Wales and followed up to 18 years of age. Pollution data generation was completed on April 22, 2020; data were analyzed from April 27 to July 31, 2020.

EXPOSURES

High-resolution annualized estimates of outdoor nitrogen oxides (NOx) and particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5) linked to home addresses at the ages of 10 and 18 years and then averaged.

MAIN OUTCOMES AND MEASURES

Mental health disorder symptoms assessed through structured interview at 18 years of age and transformed through confirmatory factor analysis into continuous measures of general psychopathology (primary outcome) and internalizing, externalizing, and thought disorder symptoms (secondary outcomes) standardized to a mean (SD) of 100 (15). Hypotheses were formulated after data collection, and analyses were preregistered.

RESULTS

A total of 2039 participants (1070 [52.5%] female) had full data available. After adjustment for family and individual factors, each interquartile range increment increase in NOx exposure was associated with a 1.40-point increase (95% CI, 0.41-2.38; P = .005) in general psychopathology. There was no association between continuously measured PM2.5 and general psychopathology (b = 0.45; 95% CI, -0.26 to 1.11; P = .22); however, those in the highest quartile of PM2.5 exposure scored 2.04 points higher (95% CI, 0.36-3.72; P = .02) than those in the bottom 3 quartiles. Copollutant models, including both NOx and PM2.5, implicated NOx alone in these significant findings. NOx exposure was associated with all secondary outcomes, although associations were weakest for internalizing (adjusted b = 1.07; 95% CI, 0.10-2.04; P = .03), medium for externalizing (adjusted b = 1.42; 95% CI, 0.53-2.31; P = .002), and strongest for thought disorder symptoms (adjusted b = 1.54; 95% CI, 0.50-2.57; P = .004). Despite NOx concentrations being highest in neighborhoods with worse physical, social, and economic conditions, adjusting estimates for neighborhood characteristics did not change the results.

CONCLUSIONS AND RELEVANCE

Youths exposed to higher levels of outdoor NOx experienced greater psychopathology at the transition to adulthood. Air pollution may be a nonspecific risk factor for the development of psychopathology.

Psychometric properties of the Brief Symptom Inventory support the hypothesis of a general psychopathological factor

INTRODUCTION

The existence of a general factor related to psychiatric symptoms is supported by studies using a variety of methods in both clinical and non-clinical samples.

OBJECTIVES

This study aims to evaluate the replicability of the internal structure of the Brief Symptom Inventory in a large Brazilian sample.

METHODS

Participants were 6,427 Brazilian subjects (81% female). Mean age was 42.1 years (standard deviation [SD] = 13.6, Min = 13, Max = 80). All participants completed the online version of the Brief Symptom Inventory. This scale presents a general score (GSI) and nine specific clusters of symptoms (depression, anxiety, phobic anxiety, interpersonal sensibility, psychoticism, paranoid ideation, obsessive-compulsive behavior, hostility, and somatization symptoms).

RESULTS

Confirmatory factor analysis was performed to assess the factor structure of the BSI. The results showed that the best-fitting model was a bifactor solution and the general factor was the main dimension explaining most of the reliable variability in the data.

CONCLUSION

The findings suggest that the BSI's internal structure was replicated in a non-clinical sample and that the general factor is the most reliable score. However, it is necessary to better understand the meaning of the general factor scores in a non-clinical sample to increase interpretability of scores.

Culture and psychopathology: An attempt at reconsidering the role of social learning

This paper proposes a model for developmental psychopathology that is informed by recent research suggestive of a single model of mental health disorder (the p factor) and seeks to integrate the role of the wider social and cultural environment into our model, which has previously been more narrowly focused on the role of the immediate caregiving context. Informed by recently emerging thinking on the social and culturally driven nature of human cognitive development, the ways in which humans are primed to learn and communicate culture, and a mentalizing perspective on the highly intersubjective nature of our capacity for affect regulation and social functioning, we set out a cultural-developmental approach to psychopathology.

Exposure to Bullying and General Psychopathology: A Prospective, Longitudinal Study

Although there is mounting evidence that the experience of being bullied associates with both internalizing and externalizing symptoms, it is not known yet whether the identified associations are specific to these symptoms, or shared between them. The primary focus of this study is to assess the prospective associations of bullying exposure with both general and specific (i.e., internalizing, externalizing) factors of psychopathology. This study included data from 6,210 children participating in the Avon Longitudinal Study of Parents and Children (ALSPAC). Child bullying was measured by self-report at ages 8 and 10 years. Child psychopathology symptoms were assessed by parent-interview, using the Development and Well-being Assessment (DAWBA) at ages 7 and 13 years. Bullying exposure significantly associated with the general psychopathology factor in early adolescence. In particular, chronically victimized youth exposed to multiple forms of bullying (i.e., both overt and relational) showed higher levels of general psychopathology. Bullying exposure also associated with both internalizing and externalizing factors from the correlated-factors model. However, the effect estimates for these factors decreased considerably in size and dropped to insignificant for the internalizing factor after extracting the shared variance that belongs to the general factor of psychopathology. Using an integrative longitudinal model, we found that higher levels of general psychopathology at age 7 also associated with bullying exposure at age 8 which, in turn, associated with general psychopathology at age 13 through its two-year continuity. Findings suggest that exposure to bullying is a risk factor for a more general vulnerability to psychopathology.

Criterion validity and relationships between alternative hierarchical dimensional models of general and specific psychopathology

[Correction Notice: An Erratum for this article was reported in Vol 129(7) of Journal of Abnormal Psychology (see record 2020-72912-001). In the article (http://dx.doi.org/10.1037/abn0000601), an acknowledgment is missing from the author note. The missing acknowledgement is included in the erratum.] Psychopathology can be viewed as a hierarchy of correlated dimensions. Many studies have supported this conceptualization, but they have used alternative statistical models with differing interpretations. In bifactor models, every symptom loads on both the general factor and 1 specific factor (e.g., internalizing), which partitions the total explained variance in each symptom between these orthogonal factors. In second-order models, symptoms load on one of several correlated lower-order factors. These lower-order factors load on a second-order general factor, which is defined by the variance shared by the lower-order factors. Thus, the factors in second-order models are not orthogonal. Choosing between these valid statistical models depends on the hypothesis being tested. Because bifactor models define orthogonal phenotypes with distinct sources of variance, they are optimal for studies of shared and unique associations of the dimensions of psychopathology with external variables putatively relevant to etiology and mechanisms. Concerns have been raised, however, about the reliability of the orthogonal specific factors in bifactor models. We evaluated this concern using parent symptom ratings of 9-10 year olds in the ABCD Study. Psychometric indices indicated that all factors in both bifactor and second-order models exhibited at least adequate construct reliability and estimated replicability. The factors defined in bifactor and second-order models were highly to moderately correlated across models, but have different interpretations. All factors in both models demonstrated significant associations with external criterion variables of theoretical and clinical importance, but the interpretation of such associations in second-order models was ambiguous due to shared variance among factors. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Bi-Directional Relationships Between Psychological Symptoms and Environmental Factors in Early Adolescence

AIM

Bi-directional relationships between various environmental factors and psychological symptoms can be seen from childhood to adolescence; however, there has been little prospective cohort study, which investigated the relationships simultaneously. In this study, we first distinguished specific psychological symptoms from general psychopathology using bifactor modeling and then tested the relationships between psychological symptoms and environmental factors from childhood to early adolescence using a structural equation model (SEM).

METHODS

The analyses were based on Tokyo TEEN Cohort (TTC) data collected between October 2012 and March 2016. We obtained self-reported psychological symptoms and environmental factors from both parents and children (at their ages of 10 and 12). Participants were 3,171 children aged 10 [girls = 1,487 (46.9%), mean age, SD = 10.2, 0.28] and subsequently 12 (N = 3,007, follow-up rate 94.8%, mean age, SD = 12.2, 0.31) from three municipalities in Tokyo area.

RESULTS

The best-fit symptom models included four unique factors and general psychopathology as the common factor. Combining the good fit bifactor model and the SEM, positive relationships between symptoms and environmental factors at the same waves and some bi-directional relationships were found. Especially, general psychopathology at age 10 was associated with bullying at age 12 and parental depressive symptoms at age 10 with general psychopathology at age 12. However, some negative relationships such as bullying/bullied involvement and later psychological symptoms were also seen.

CONCLUSION

By using the newly introduced methodology, our results were partly consistent with previous literature. Further studies are needed to validate this methodology and accelerate the findings regarding the emergence of psychological symptoms and the impact of environmental factors from childhood to early adolescence.