Hubness of strategic planning and sociality influences depressive mood and anxiety in College Population

Abstract

Depressive mood and anxiety can reduce cognitive performance. Conversely, the presence of a biased cognitive tendency may serve as a trigger for depressive mood-anxiety. Previous studies have largely focused on group-wise correlations between clinical-neurocognitive variables. Using network analyses for intra-individual covariance, we sought to decipher the most influential clinical-neurocognitive hub in the differential severity of depressive-anxiety symptoms in a college population. Ninety college students were evaluated for depressive-anxiety symptoms, Minnesota multiphasic personality inventory-2(MMPI-2), and neuro-cognition. Weighted and undirected version of the intra-individual covariance networks, comprised of 18 clinical-neurocognitive variables satisfied small-worldness and modular organization in the sparsity range of K = 0.20–0.21. Furthermore, betweenness centrality of perseverative error for the Wisconsin card sorting test was reduced in more depressive individuals; higher anxiety was related to the increased betweenness centrality of MMPI-2 clinical scale 0(Si). Elevated edge-betweenness centrality of covariance between the MMPI-2 clinical scale 7(Pt) versus commission error of the continuous performance test predicted more anxiety higher than depressive mood. With intra-individual covariance network of clinical-neurocognitive variables, this study demonstrated critical drivers of depressive mood[attenuated influence of strategic planning] or anxiety[domination of social introversion/extroversion, in addition to the influence of compulsivity-impulsivity covariance as a shortcut component among various clinical-neurocognitive features].

Verbal Abuse Related to Self-Esteem Damage and Unjust Blame Harms Mental Health and Social Interaction in College Population

“…Using network-based approaches, integrative as well as segregated patterns of interactions among the psychopathology, cognitive functioning, and perceived external stimuli have been explored in various populations 19,21–23 . In such networks, each psychological feature is considered to be a node; these nodes are connected with edges that represent strengths (with or without directionalities) of relationships among the nodes that collectively comprise the network.…”

“…In such networks, each psychological feature is considered to be a node; these nodes are connected with edges that represent strengths (with or without directionalities) of relationships among the nodes that collectively comprise the network. Depending on the data characteristics and the aims of study, several formats of networks are available; the directed acyclic network (DAG; a directed and group-wise Bayesian network) 22,24 , a Gaussian graphical model (an undirected, partial correlation network in which edges represent group-wise relationships between ordinal or continuous variables) 25–27 , an Ising model (an undirected network estimating group-wise relationships among the dichotomous variables) 28,29 , and an intra-individual covariance network (an undirected network that describes inter-connectedness between psychological constructs within each participant) 23 .…”

Association between body satisfaction and sociodemographic, behavioral and health of university students

“…Na literatura, estima-se que em média 24% dos estudantes universitários tenham alguns sintomas de depressão durante sua trajetória acadêmica, com maior prevalência os de ansiedade. 35 Esses sintomas são mais frequentes em estudantes universitários, porque possuem uma rede social pouco desenvolvida e tomam medidas extremistas e prejudiciais ao procurar novos grupos sociais. 36 No presente estudo, identificou-se maior prevalência de insatisfação corporal entre os estudantes que referiram ter essas doenças, mas sem significância estatística.…”

Symptom-level network analysis distinguishes the unique associations of repetitive negative thinking and experiential avoidance on depression and anxiety in a transdiagnostic clinical sample

“…Most network studies of psychopathology that incorporate nodes measuring theorized maintenance factors generally focus on a single disorder (c.f., Galderisi et al, 2018;Heeren & McNally, 2016;Mullarkey, Dobias, & Bluth, 2018). The network studies that have examined maintenance factors of psychopathology with symptoms beyond a single disorder have included measures of personality (c.f., Pereira-Morales, Adan, & Forero, 2019;Yun et al, 2017), social connectivity/neighborhood environment , and neuropsychological functioning (Yun et al, 2017). Surprisingly, to our knowledge no study has examined the contributions of transdiagnostic maintenance factors drawn from cognitive models of psychopathology, such as repetitive negative thinking or experiential avoidance, to transdiagnostic symptom networks.…”