Disorder agnostic network structure of psychopathology symptoms in youth. (November 2021)

• Record Type: Journal Article
• Authors: Wang, Emily; Reardon, Brandy; Cherian, Benjamin; George, Wales T.; Xavier, Rose Mary
• Is Part Of: Journal of psychiatric research. Volume 143(2021)
• Page Start: 246
• Page End: 253
• Publication Date: 2021-11
• Subjects: Psychopathology -- Comorbidity -- Mixed graphical model -- Youth -- Network analysis; Psychiatry -- Periodicals; Mental Disorders -- Periodicals; Maladies mentales -- Périodiques; Psychiatry; Electronic journals; Periodicals; 616.89005
• DOI: 10.1016/j.jpsychires.2021.09.026
• Languages: English
• ISSNs: 0022-3956

Abstract

Abstract: Background: Youth mental health disorders are strong predictors of adult mental health disorders. Early identification of mental health disorders in youth is important as it could aid early intervention and prevention. In a disorder agnostic manner, we aimed to identify influential psychopathology symptoms that could impact mental health in youth. Methods: This study sampled 6063 participants from the Philadelphia Neurodevelopmental Cohort and comprised of youth of ages 12–21 years. A mixed graphical model was used to estimate the network structure of 115 symptoms corresponding to 16 psychopathology domains. Importance of individual symptoms in the network were assessed using node influence measures such as strength centrality and predictability. Results: The generated network had stronger associations between symptoms within a psychopathological domain; overall had no negative associations. A conduct disorder symptom eliciting threatening others and a depression symptom - persistent sadness or depressed mood - had the greatest strength centralities ( β = 2.85). Fear of traveling in a car and compulsively going in and out a door had the largest predictability (classification accuracy = 0.99). Conduct disorder, depression, and obsessive compulsive disorder symptoms generally had the largest strength centralities. Suicidal thoughts had the largest bridge strength centrality ( β = 2.85). Subgroup networks revealed that network structure differed by socioeconomic status (low versus high, p = 0.04) and network connectivity patterns differed by sex (p = 0.01), but not for age or race. Conclusions: Psychopathology symptom networks offer insights that could be leveraged for early identification, intervention, and possibly prevention of mental health disorders.