Literature DB >> 31539681

Gender differences in trajectories of depressive symptoms across childhood and adolescence: A multi-group growth mixture model.

Andrew J Lewis1, Jonathan H Sae-Koew2, John W Toumbourou3, Bosco Rowland3.   

Abstract

BACKGROUND: This study sought to identify depression trajectories across childhood and to model a range of child and family predictors of whether a child may be on an increasing trajectory towards depressive disorder in adolescence.
METHODS: Multi-group growth mixture modelling (MGMM) was used on a sample of 4983 children from the Longitudinal Study of Australia Children (LSAC). Depressive symptoms of these children were assessed over 10-years with six time-points, administered every second year commencing at 4 years via the parent report version of the Strength and Difficulties Questionnaire. Predictors of class membership were also examined.
RESULTS: Four trajectories were found to be the best fitting model characterising low-stable (75%); decreasing (11%); increasing (9%); high and rising (6%) groups. Females were more likely to be in a trajectory of increasing depressive symptoms between 4 and 14 years of age than males. Reactive temperament and maternal depression at four and six years of age were consistent predictors of increasing and high trajectories while persistent temperament acts as a protective factor for females. LIMITATIONS: The findings should be interpreted in the light of limitations due to common-method variance and the absence of diagnostic indicators of depressive disorder.
CONCLUSIONS: We conclude that there are gender differences in patterns of depressive symptoms from childhood to adolescence and meaningful predictors of these early developmental trajectories. Preventative interventions in childhood targeting parents with depression and children with temperamental difficulties may be indicated.
Copyright © 2019. Published by Elsevier B.V.

Entities:  

Keywords:  Adolescent depression; Childhood depression; Latent class growth curve modelling; Person-centred methods; Trajectory modelling

Mesh:

Year:  2019        PMID: 31539681     DOI: 10.1016/j.jad.2019.09.027

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   4.839


  9 in total

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