Comparing Transdiagnostic Risk Factors: Predicting Emergence of Significant Depressive, Anxiety, and Substance Abuse Symptoms Among Juvenile Delinquents.
Anxiety
Depression
First incidence
Machine learning
Negative emotionality
Risk factor
Substance abuse
Transdiagnostic
Journal
Child psychiatry and human development
ISSN: 1573-3327
Titre abrégé: Child Psychiatry Hum Dev
Pays: United States
ID NLM: 1275332
Informations de publication
Date de publication:
23 May 2024
23 May 2024
Historique:
accepted:
15
02
2024
medline:
24
5
2024
pubmed:
24
5
2024
entrez:
23
5
2024
Statut:
aheadofprint
Résumé
In a 7-year 11-wave study of low-SES adolescents (N = 856, age = 15.98), we compared multiple well-established transdiagnostic risk factors as predictors of first incidence of significant depressive, anxiety, and substance abuse symptoms across the transition from adolescence to adulthood. Risk factors included negative emotionality, emotion regulation ability, social support, gender, history of trauma, parental histories of substance abuse, parental mental health, and socioeconomic status. Machine learning models revealed that negative emotionality was the most important predictor of both depression and anxiety, and emotion regulation ability was the most important predictor of future significant substance abuse. These findings highlight the critical role that dysregulated emotion may play in the development of some of the most prevalent forms of mental illness.
Identifiants
pubmed: 38782806
doi: 10.1007/s10578-024-01682-6
pii: 10.1007/s10578-024-01682-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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