Rates of Depression in Children and Adolescents With ADHD: A Systematic Review and Meta-Analysis

Accumulating evidence indicates high rates of major depressive disorder (MDD) in children and adolescents with ADHD. This systematic review and meta-analysis aimed to examine the rate of depression in children and adolescents with ADHD who are without intellectual disability (ID).

A comprehensive search of six databases identified 20,745 studies. After screening based on inclusion and exclusion criteria, 24 studies were retained. A meta-analysis estimated the pooled depression rate in this population, and subgroup analyses examined differences based on sex, pubertal status, ADHD medication use, recruitment settings, depression assessment tools, informants, and risk of bias rating. Depression rates in children and adolescents with ADHD were compared with neurotypical peers in the retained case-control studies.

Depression rates in children and adolescents with ADHD across the included studies ranged from 1.7% to 60%, with the meta-analysis estimating a pooled depression rate of 11.31% (95% CI [0.07, 0.16]). Subgroup analyses indicated significant differences by sex, with females showing higher rates than males. Differences were also noted by assessment methods, with the highest rates observed when both questionnaires and interviews were used. While other factors did not significantly affect rates, notable trends were identified and reported in the current article.

Depression is a common co-occurrent psychiatric condition in children and adolescents with ADHD, with rates observed in this review and meta-analysis being higher than those reported for neurotypical children and adolescents. This review underscores the importance of combining multiple assessment methods to capture a comprehensive picture of depression in this population, as well as ensuring balanced demographic representation. This review also suggests that further research should explore the depression developmental patterns in children and adolescents with ADHD and identify whether patterns are similar to the neurotypical population.