Latent class profiles of depressive symptoms from early to middle childhood: predictors, outcomes, and gender effects

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Abstract

Background: There has been little available data to inform the predictors and outcomes of latent class trajectories of depressive symptoms beginning during preschool and continuing throughout school age. Further, the extant literature in this domain has been limited by the use of parent report checklists of nonspecific ‘internalizing’ psychopathology rather than diagnostic interviews for depression. Methods: To address these gaps in the literature, this study applied growth mixture modeling to depressive symptom severity endorsed by children and/or their caregivers (N = 348) during a structured clinical interview in a 10-year longitudinal dataset spanning from preschool into late school age. Results: Three distinct trajectories of depressive symptom severity were found in boys and girls. For boys, but not girls, the high depression severity latent class increased in depressive symptoms from preschool through school age, followed by a decline in depressive symptom severity during later school age. For girls, the high depression severity latent class remained stable across time. Early childhood social adversity, familial history of affective disorder, preschool-onset ODD/CD, and school age functional impairment differentiated high-risk trajectory classes among both boys and girls. Conclusions: Extending the literature on trajectories of depressive symptoms to the preschool period, these findings incorporate structured clinical interviews of depressive symptom severity and indicate gender differences as well as psychosocial predictors and functional outcomes among children in high severity latent classes. The findings from this study suggest that increased attention to screening for depressive symptoms in early childhood is of significant public health importance.

Original languageEnglish
Pages (from-to)794-804
Number of pages11
JournalJournal of Child Psychology and Psychiatry and Allied Disciplines
Volume57
Issue number7
DOIs
StatePublished - Jul 1 2016

Keywords

  • Depression
  • childhood
  • growth mixture modeling
  • longitudinal

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