Disorder agnostic network structure of psychopathology symptoms in youth
| Autor: | Brandy Reardon, Benjamin Cherian, Rose Mary Xavier, Emily Wang, Wales T. George |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Adult
Obsessive-Compulsive Disorder Adolescent media_common.quotation_subject Suicidal Ideation Cohort Studies Young Adult Intervention (counseling) medicine Humans Child Biological Psychiatry Depression (differential diagnoses) media_common Psychopathology medicine.disease Comorbidity Mental health Sadness Psychiatry and Mental health Mental Health Conduct disorder Cohort Psychology Clinical psychology |
| Zdroj: | Journal of Psychiatric Research. 143:246-253 |
| ISSN: | 0022-3956 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect