8 research outputs found
Personality dimensions emerging during adolescence and young adulthood are underpinned by a single latent trait indexing impairment in social functioning
No full textBackground: Personality with stable behavioural traits emerges in the adolescent and young adult years. Models of putatively distinct, but correlated, personality traits have been developed to describe behavioural styles including schizotypal, narcissistic, callous-unemotional, negative emotionality, antisocial and impulsivity traits. These traits have influenced the classification of their related personality disorders. We tested if a bifactor model fits the data better than correlated-factor and orthogonal-factor models and subsequently validated the obtained factors with mental health measures and treatment history. / Method: A set of self-report questionnaires measuring the above traits together with measures of mental health and service use were collected from a volunteer community sample of adolescents and young adults aged 14 to 25 years (N = 2443). Results: The bifactor model with one general and four specific factors emerged in exploratory analysis, which fit data better than models with correlated or orthogonal factors. The general factor showed high reliability and validity. / Conclusions: The findings suggest that a selected range of putatively distinct personality traits is underpinned by a general latent personality trait that may be interpreted as a severity factor, with higher scores indexing more impairment in social functioning. The results are in line with ICD-11, which suggest an explicit link between personality disorders and compromised interpersonal or social function. The obtained general factor was akin to the overarching dimension of personality functioning (describing one’s relation to the self and others) proposed by DSM-5 Section III
Developmental cognitive neuroscience using Latent Change Score models: A tutorial and applications
No full textAssessing and analysing individual differences in change over time is of central scientific importance to developmental neuroscience. However, the literature is based largely on cross-sectional comparisons, which reflect a variety of influences and cannot directly represent change. We advocate using latent change score (LCS) models in longitudinal samples as a statistical framework to tease apart the complex processes underlying lifespan development in brain and behaviour using longitudinal data. LCS models provide a flexible framework that naturally accommodates key developmental questions as model parameters and can even be used, with some limitations, in cases with only two measurement occasions. We illustrate the use of LCS models with two empirical examples. In a lifespan cognitive training study (COGITO, N = 204 (N = 32 imaging) on two waves) we observe correlated change in brain and behaviour in the context of a high-intensity training intervention. In an adolescent development cohort (NSPN, N = 176, two waves) we find greater variability in cortical thinning in males than in females. To facilitate the adoption of LCS by the developmental community, we provide analysis code that can be adapted by other researchers and basic primers in two freely available SEM software packages (lavaan and Ωnyx)
Increased decision thresholds trigger extended information gathering across the compulsivity spectrum
No full textIndecisiveness and doubt are cognitive phenotypes of compulsive disorders, including obsessive-compulsive disorder. Little is known regarding the cognitive mechanisms that drive these behaviours across a compulsivity spectrum. Here, we used a sequential information gathering task to study indecisiveness in subjects with high and low obsessive-compulsive scores. These subjects were selected from a large population-representative database, and matched for intellectual and psychiatric factors. We show that high compulsive subjects sampled more information and performed better when sampling was cost-free. When sampling was costly, both groups adapted flexibly to reduce their information gathering. Computational modelling revealed that increased information gathering behaviour could be explained by higher decision thresholds that, in turn, were driven by a delayed emergence of impatience or urgency. Our findings show that indecisiveness generalises to a compulsivity spectrum beyond frank clinical disorder, and this behaviour can be explained within a decision-theoretic framework as arising from an augmented decision threshold associated with an attenuated urgency signal
Compulsivity and impulsivity are linked to distinct aberrant developmental trajectories of fronto-striatal myelination
No full textAbstractThe transition from adolescence into adulthood is a period where rapid brain development coincides with an enhanced incidence of psychiatric disorder. The precise developmental brain changes that account for this emergent psychiatric symptomatology remain obscure. Capitalising on a unique longitudinal dataset, that includesin-vivomyelin-sensitive magnetization transfer (MT) MRI, we show this transition period is characterised by brain-wide growth in MT, within both gray matter and adjacent juxta-cortical white matter. We show that an expression of common developmental psychiatric risk symptomatology in this otherwise healthy population, specifically compulsivity and impulsivity, is tied to regionally specific aberrant unfolding of these MT trajectories. This is most marked in frontal midline structures for compulsivity, and in lateral frontal areas for impulsivity. The findings highlight a brain developmental linkage for emergent psychiatric risk features, evident in regionally specific perturbations in the expansion of MT-related myelination.</jats:p
Author Correction: The impact of the initial COVID-19 outbreak on young adults’ mental health: a longitudinal study of risk and resilience factors
No full textCorrection to: Scientific Reportshttps://doi.org/10.1038/s41598-022-21053-2, published online 05 October 2022. The original version of this Article contained an omission in the Methods section, under the subheading ‘Risk factors’. “A detailed list of pandemic-related questionnaire items is provided in Supplementary Materials 2.” now reads: “The pandemic-related risk factors were adapted from questionnaire items developed as part of the COVID-19 Social Study (for more information, visit www.covidsocialstudy.org/), with a detailed list of items provided in Supplementary Materials 2.” In addition, the Funding section was incomplete. The Funding section now reads: “Data collection was supported by a strategic award from the Wellcome Trust (095844/Z/11/Z) to the University of Cambridge (IMG, ETB, PBJ) and University College London (RJD, PF). Data management was supported by the NIHR Cambridge Bioresource and data analysis by the NIHR ARC East of England. These funders had no role in determining our study design, hypotheses, interpretation, or the writing of this report. AW, JP, and PBJ were supported by the NIHR ARC East of England at Cambridgeshire and Peterborough NHS Foundation Trust. JF was supported by the NIHR Cambridge Biomedical Research Centre; ETB by an NIHR Senior Investigator award. SRC role in this study was funded by a Wellcome Trust Clinical Fellowship (110049/Z/15/Z & 110049/Z/15/A) which also co-supported data collection for the fourth assessment. The NSPN COVID-19 2020 follow-up survey included a collection of items derived from questionnaire material developed as part of the COVID-19 Social Study, which was supported by the Nuffield Foundation (WEL/FR-000022583), the MARCH Mental Health Network funded by the Cross-Disciplinary Mental Health Network Plus initiative supported by UK Research and Innovation (ES/S002588/1), and the Wellcome Trust (221400/Z/20/Z and 205407/Z/16/Z).” The original Article has been corrected.</p
373. Adolescence is Associated with Genomically Patterned Consolidation of the Hubs of the Human Brain Connectome
No full textAdolescent friendships predict later resilient functioning across psychosocial domains in a healthy community cohort
No full textBACKGROUND: Adolescence is a key time period for the emergence of psychosocial and mental health difficulties. To promote adolescent adaptive (‘resilient’) psychosocial functioning, appropriate conceptualization and quantification of such functioning and its predictors is a crucial first step. Here, we quantify resilient functioning as the degree to which an individual functions better or worse than expected given their self-reported childhood family experiences, and relate this to adolescent family and friendship support.
METHODS: We used Principal Component and regression analyses to investigate the relationship between childhood family experiences and psychosocial functioning (PSF: psychiatric symptomatology, personality traits and mental wellbeing) in healthy adolescents (the Neuroscience in Psychiatry Network; N=2389; ages 14-24). Residuals from the relation between childhood family experiences and PSF reflect resilient functioning; the degree to which an individual is functioning better, or worse, than expected given their childhood family experiences. Next, we relate family and friendship support with resilient functioning both cross-sectionally and one year later.
RESULTS: Friendship and family support were positive predictors of immediate resilient psychosocial functioning, with friendship support being the strongest predictor. However, whereas friendship support was a significant positive predictor of later resilient functioning, family support had a negative relationship with later resilient psychosocial functioning.
CONCLUSIONS: We show that friendship support, but not family support, is an important positive predictor of both immediate and later resilient psychosocial functioning in adolescence and early adulthood. Interventions that promote the skills needed to acquire and sustain adolescent friendships may be crucial in increasing adolescent resilient psychosocial functioning
Adolescent Tuning of Association Cortex in Human Structural Brain Networks.
No full textMotivated by prior data on local cortical shrinkage and intracortical myelination, we predicted age-related changes in topological organization of cortical structural networks during adolescence. We estimated structural correlation from magnetic resonance imaging measures of cortical thickness at 308 regions in a sample of N = 297 healthy participants, aged 14-24 years. We used a novel sliding-window analysis to measure age-related changes in network attributes globally, locally and in the context of several community partitions of the network. We found that the strength of structural correlation generally decreased as a function of age. Association cortical regions demonstrated a sharp decrease in nodal degree (hubness) from 14 years, reaching a minimum at approximately 19 years, and then levelling off or even slightly increasing until 24 years. Greater and more prolonged age-related changes in degree of cortical regions within the brain network were associated with faster rates of adolescent cortical myelination and shrinkage. The brain regions that demonstrated the greatest age-related changes were concentrated within prefrontal modules. We conclude that human adolescence is associated with biologically plausible changes in structural imaging markers of brain network organization, consistent with the concept of tuning or consolidating anatomical connectivity between frontal cortex and the rest of the connectome
