Comparing Transdiagnostic Risk Factors: Predicting Emergence of Significant Depressive, Anxiety, and Substance Abuse Symptoms Among Juvenile Delinquents.

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 fact...

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Publicado en:Child Psychiatry & Human Development Vol. 57; no. 2; pp. 353 - 368
Autores principales: Klein, Robert J., Lekkas, Damien, Nguyen, Nhi D., Jacobson, Nicholas C.
Formato: Artículo
Publicado: Springer Nature Apr2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Apr2026
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      pub: Springer Nature
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        193366272
        10.1007/s10578-024-01682-6
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        atl: Comparing Transdiagnostic Risk Factors: Predicting Emergence of Significant Depressive, Anxiety, and Substance Abuse Symptoms Among Juvenile Delinquents.
      aug:
        au:
          Klein, Robert J.
          Lekkas, Damien
          Nguyen, Nhi D.
          Jacobson, Nicholas C.
        affil:
          https://ror.org/049s0rh22 Center for Technology and Behavioral Health, Dartmouth College, Hanover, USA
          The Well Living Lab, Rochester, USA
          Delos Living, LLC, New York, USA
          https://ror.org/049s0rh22 The Geisel School of Medicine, Dartmouth College, 1 Rope Ferry Road, 03755, Hanover, NH, USA
          https://ror.org/049s0rh22 Quantitative Biomedical Sciences Program, Dartmouth College, Hanover, USA
          https://ror.org/049s0rh22 Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Hanover, USA
          https://ror.org/049s0rh22 Department of Psychiatry, Geisel School of Medicine, Dartmouth College, Hanover, USA
      su:
        Juvenile offenders
        Substance abuse
        Anxiety
        Mental depression
        Disease risk factors
        Emotion regulation
        Machine learning
        Psychological resilience
      sug:
        subj:
          Juvenile offenders
          Substance abuse
          Anxiety
          Mental depression
          Disease risk factors
          Emotion regulation
          Machine learning
          Psychological resilience
      keyword:
        Depression
        First incidence
        Medical and Health Sciences Public Health and Health Services Psychology and Cognitive Sciences Psychology
        Negative emotionality
        Risk factor
        Transdiagnostic
        Depression
        First incidence
        Medical and Health Sciences Public Health and Health Services Psychology and Cognitive Sciences Psychology
        Negative emotionality
        Risk factor
        Transdiagnostic
      ab: 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.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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