Depressive symptoms and academic achievement in UK adolescents: a cross-lagged analysis with genetic covariates

López-López, Jose A, Kwong, Alex SF, Washbrook, Liz, Tilling, Kate, Fazel, Mina S and Pearson, Rebecca M (2021) Depressive symptoms and academic achievement in UK adolescents: a cross-lagged analysis with genetic covariates. Journal of Affective Disorders, 284. pp. 104-113. ISSN 0165-0327

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Abstract

Background: The relationship between adolescent depressive symptoms and academic achievement remains poorly understood. The aim of this study was to help clarify the nature and directionality of this association. Methods: We used a sample of 13,599 British adolescents (main sample of N=3,809 participants). We fitted cross-lagged panel models using four repeated measures of self-reported depressive symptoms and four measures of academic achievement based on British national records between 11-18 years, separately for male and female adolescents and considering polygenic risk scores (PRS) for educational attainment and depression, alongside other child and parental covariates. Results: We found evidence of an overall negative association that was stronger in boys (R=-0.21, 95% CI -0.31 to -0.11) than in girls (-0.13, -0.31 to 0.05). Higher depressive symptoms were associated with lower academic achievement at a later stage up to the end of compulsory education (16 years), when the direction of the association reversed, although girls with lower achievement also appeared vulnerable to depressive symptoms at previous stages. The genetic variables derived for this study showed stronger associations for academic achievement, but the PRS for depression also showed a negative association with academic achievement in girls. Child intelligence quotient and peer victimization also showed relevant associations. Limitations: Observational design, variation around measurement times, missing data. Conclusions: Depressive symptoms and academic achievement should be considered jointly when designing school-based programmes for children and adolescents, alongside gender, child ability and school experience. Including genetic information in research can help to disentangle average from time-varying effects.