Advancing understanding of executive function impairments and psychopathology: bridging the gap between clinical and cognitive approaches

Executive function (EF) is essential for successfully navigating nearly all of our daily activities. Of critical importance for clinical psychological science, EF impairments are associated with most forms of psychopathology. However, despite the proliferation of research on EF in clinical populations, with notable exceptions clinical and cognitive approaches to EF have remained largely independent, leading to failures to apply theoretical and methodological advances in one field to the other field and hindering progress. First, we review the current state of knowledge of EF impairments associated with psychopathology and limitations to the previous research in light of recent advances in understanding and measuring EF. Next, we offer concrete suggestions for improving EF assessment. Last, we suggest future directions, including integrating modern models of EF with state of the art, hierarchical models of dimensional psychopathology as well as translational implications of EF-informed research on clinical science

Temperament Factors and Dimensional, Latent Bifactor Models of child psychopathology: Transdiagnostic and Specific Associations in Two Youth Samples

Common emotional and behavioral symptoms co-occur and are associated with core temperament factors. This study investigated links between temperament and dimensional, latent psychopathology factors, including a general common psychopathology factor (p factor) and specific latent internalizing and externalizing liabilities, as captured by a bifactor model, in two independent samples of youth. Specifically, we tested the hypothesis that temperament factors of negative affectivity (NA), positive affectivity (PA), and effortful control (EC) could serve as both transdiagnostic and specific risks in relation to recent bifactor models of child psychopathology. Sample 1 included 571 youth (average age 13.6, SD = 2.37, range 9.3–17.5) with both youth and parent report. Sample 2 included 554 preadolescent children (average age 7.7, SD = 1.35, range = 5–11 years) with parent report. Structural equation modeling showed that the latent bifactor models fit in both samples. Replicated in both samples, the p factor was associated with lower EC and higher NA (transdiagnostic risks). Several specific risks replicated in both samples after controlling for co-occurring symptoms via the p factor: internalizing was associated with higher NA and lower PA, lower EC related to externalizing problems

Maternal Depressive Symptoms Predict General Liability in Child Psychopathology

Objective: The current study examines how maternal depressive symptoms relate to child psychopathology when structured via the latent bifactor model of psychopathology, a new organizational structure of psychopathological symptoms consisting of a general common psychopathology factor (p-factor) and internalizing- and externalizing-specific risk. Method: Maternal report of depressive symptoms (Beck Depression Inventory – II) and child psychopathological symptoms (Child Behavior Checklist and Children’s Behavior Questionnaire) were provided by 554 mother-child pairs. Children in the sample were 7.7 years old on average (SD = 1.35, range = 5–11 years), and were 49.8% female, 46% Latinx, and 67% White, 6% Black, 5% Asian/Pacific Islander, and 21% multiracial. Results: Maternal depressive symptoms were positively associated with the child p-factor but not with the internalizing- or externalizing-specific factors. We did not find evidence of sex/gender or race/ethnicity moderation when using latent factors of psychopathology. Consistent with past research, maternal depressive symptoms were positively associated with internalizing and externalizing composite scores on the Child Behavior Checklist. Conclusions: Findings suggest that maternal depressive symptoms are associated with transdiagnostic risk for broad child psychopathology (p-factor). Whereas the traditional Achenbach-style approach of psychopathological assessment suggests that maternal depressive symptoms are associated with both child internalizing and externalizing problems, the latent bifactor model suggests that these associations may be accounted for by risk pathways related to the p-factor rather than internalizing or externalizing specific risk. We discuss clinical and research implications of using a latent bifactor structure of psychopathology to understand how maternal depression may impact children’s mental health

Alcohol and cigarette use and misuse among hurricane Katrina survivors: Psychosocial risk and protective factors

The present study examined survivors’ use and misuse of cigarettes and alcohol following Hurricane Katrina. We also examined several psychosocial factors that we expected would be associated with higher or lower rates of substance use following the Hurricane. Participants were 209 adult survivors of Hurricane Katrina interviewed in Columbia, SC or New Orleans, LA between October 31, 2005 and May 13, 2006. Results revealed that survivors were smoking cigarettes, consuming alcohol, and experiencing alcohol-related problems at a substantially higher rate than expected based on pre- Hurricane prevalence data. Results also suggested that certain psychosocial factors were associated with participants’ substance use and misuse following the Hurricane

Personalized Depression Prevention: A Randomized Controlled Trial to Optimize Effects Through Risk-Informed Personalization

Objective: To evaluate whether evidence-based depression prevention programs can be optimized by matching youths to interventions that address their psychosocial vulnerabilities. Method: This randomized controlled trial included 204 adolescents (mean [SD] age ¼ 14.26 [1.65] years; 56.4% female). Youths were categorized as high or low on cognitive and interpersonal risks for depression and randomly assigned to Coping With Stress (CWS), a cognitive-behavioral program, or Interpersonal Psychotherapy–Adolescent Skills Training (IPT-AST), an interpersonal program. Some participants received a match between risk and prevention (eg, high cognitive–low interpersonal risk teen in CWS, low cognitive–high interpersonal risk teen in IPT-AST), others received a mismatch (eg, low cognitive-high interpersonal risk teen in CWS). Outcomes were depression diagnoses and symptoms through 18 months postintervention (21 months total). Results: Matched adolescents showed significantly greater decreases in depressive symptoms than mismatched adolescents from postintervention through 18-month follow-up and across the entire 21-month study period (effect size [d] ¼ 0.44, 95% CI ¼ 0.02, 0.86). There was no significant difference in rates of depressive disorders among matched adolescents compared with mismatched adolescents (12.0% versus 18.3%, t193 ¼ .78, p ¼ .44). Conclusion: This study illustrates one approach to personalizing depression prevention as a form of precision mental health. Findings suggest that risk-informed personalization may enhance effects beyond a one-size-fits-all approach. Clinical trial registration information: Bending Adolescent Depression Trajectories Through Personalized Prevention; https://www.clinicaltrials. gov/; NCT01948167

Association between 5-HTTLPR and Borderline Personality Disorder Traits among Youth

This study provides the first genetic association examination of borderline personality disorder (BPD) traits in children and adolescents (ages 9–15) using two independent samples of youth recruited from the general community. We tested the a priori hypothesis that the serotonin transporter promoter gene (5-HTTLPR) would relate specifically to BPD traits in youth. This association was hypothesized based on prior genetic association research with BPD adults and theory positing that emotion dysregulation may be a core risk process contributing to BPD. Youth provided DNA via buccal cells. Both youth and a parent completed self-report measures assessing youth's BPD traits and depressive symptoms. Results from both Study 1 (N = 242) and an independent replication sample of Study 2 (N = 144) showed that carriers of the short allele of 5-HTTLPR exhibited the highest levels of BPD traits. This relation was observed even after controlling for the substantial co-occurrence between BPD traits and depressive symptoms. This specific association between 5-HTTLPR and BPD traits among youth supports previous genetic associations with adults diagnosed with BPD and provides preliminary support for a developmental extension of etiological risk for BPD among youth

Parental depression and child cognitive vulnerability predict children\u27s cortisol reactivity

Risk for depression is expressed across multiple levels of analysis. For example, parental depression and cognitive vulnerability are known markers of depression risk, but no study has examined their interactive effects on children\u27s cortisol reactivity, a likely mediator of early depression risk. We examined relations across these different levels of vulnerability using cross-sectional and longitudinal methods in two community samples of children. Children were assessed for cognitive vulnerability using self-reports (Study 1; n = 244) and tasks tapping memory and attentional bias (Study 2; n = 205), and their parents were assessed for depression history using structured clinical interviews. In both samples, children participated in standardized stress tasks and cortisol reactivity was assessed. Cross-sectionally and longitudinally, parental depression history and child cognitive vulnerability interacted to predict children\u27s cortisol reactivity; associations between parent depression and elevated child cortisol activity were found when children also showed elevated depressotypic attributions as well as attentional and memory biases. Findings indicate that models of children\u27s emerging depression risk may benefit from the examination of the interactive effects of multiple sources of vulnerability across levels of analysis

Exposure to Prenatal Maternal Distress and Infant White Matter Neurodevelopment

The prenatal period represents a critical time for brain growth and development. These rapid neurological advances render the fetus susceptible to various influences with life-long implications for mental health. Maternal distress signals are a dominant early life influence, contributing to birth outcomes and risk for offspring psychopathology. This prospective longitudinal study evaluated the association between prenatal maternal distress and infant white matter microstructure. Participants included a racially and socioeconomically diverse sample of 85 mother–infant dyads. Prenatal distress was assessed at 17 and 29 weeks’ gestational age (GA). Infant structural data were collected via diffusion tensor imaging (DTI) at 42–45 weeks’ postconceptional age. Findings demonstrated that higher prenatal maternal distress at 29 weeks’ GA was associated with increased fractional anisotropy, b = .283, t(64) = 2.319, p = .024, and with increased axial diffusivity, b = .254, t(64) = 2.067, p = .043, within the right anterior cingulate white matter tract. No other significant associations were found with prenatal distress exposure and tract fractional anisotropy or axial diffusivity at 29 weeks’ GA, or earlier in gestation

A multi-decade record of high quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT)

The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.7 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.6 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) “living data” publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: doi:10.1594/PANGAEA.849770. The gridded products are available here: doi:10.3334/CDIAC/OTG.SOCAT_V3_GRID

Traffic and Related Self-Driven Many-Particle Systems

Since the subject of traffic dynamics has captured the interest of physicists, many astonishing effects have been revealed and explained. Some of the questions now understood are the following: Why are vehicles sometimes stopped by so-called ``phantom traffic jams'', although they all like to drive fast? What are the mechanisms behind stop-and-go traffic? Why are there several different kinds of congestion, and how are they related? Why do most traffic jams occur considerably before the road capacity is reached? Can a temporary reduction of the traffic volume cause a lasting traffic jam? Under which conditions can speed limits speed up traffic? Why do pedestrians moving in opposite directions normally organize in lanes, while similar systems are ``freezing by heating''? Why do self-organizing systems tend to reach an optimal state? Why do panicking pedestrians produce dangerous deadlocks? All these questions have been answered by applying and extending methods from statistical physics and non-linear dynamics to self-driven many-particle systems. This review article on traffic introduces (i) empirically data, facts, and observations, (ii) the main approaches to pedestrian, highway, and city traffic, (iii) microscopic (particle-based), mesoscopic (gas-kinetic), and macroscopic (fluid-dynamic) models. Attention is also paid to the formulation of a micro-macro link, to aspects of universality, and to other unifying concepts like a general modelling framework for self-driven many-particle systems, including spin systems. Subjects such as the optimization of traffic flows and relations to biological or socio-economic systems such as bacterial colonies, flocks of birds, panics, and stock market dynamics are discussed as well.Comment: A shortened version of this article will appear in Reviews of Modern Physics, an extended one as a book. The 63 figures were omitted because of storage capacity. For related work see http://www.helbing.org