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Longitudinal Clustering of Psychopathology Across Childhood and Adolescence: An Approach Toward Developmentally Based Classification

  • Stony Brook University
  • Temple University
  • Rutgers University

Research output: Contribution to journalArticlepeer-review

Abstract

Current classification systems of psychopathology focus on cross-sectional symptoms rather than continuity, discontinuity, and comorbidity across development. Here, a community sample of 600 youths was assessed every 3 years from early childhood through late adolescence using semistructured diagnostic interviews. We used longitudinal k-means clustering of joint-diagnostic trajectories to identify six distinct clusters (healthy, childhood anxiety, childhood/adolescent attention-deficit/hyperactivity disorder, adolescent depression/anxiety, adolescent depression/substance use, and early childhood disruptive behavior). Comparing psychopathology clusters with the healthy cluster on age-3 predictors (parental education and psychopathology, early environment, temperament, cognitive and social functioning) and age-18 functional outcomes, we found that the clusters captured developmental patterning of psychopathology not apparent in cross-sectional nosology. The study serves as a proof of principle in applying a longitudinal clustering approach to common mental disorders, affording a rich perspective on the unfolding of sequential comorbidity and heterotypic continuity and identifying transdiagnostic subgroups with meaningful clinical, family, and temperamental correlates.

Original languageEnglish
Pages (from-to)219-239
Number of pages21
JournalClinical Psychological Science
Volume14
Issue number2
DOIs
StatePublished - Mar 2026

Keywords

  • adolescence
  • childhood
  • classification
  • clustering
  • development
  • psychopathology

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