Abstract
BackgroundThe 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. MethodsWe 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. ResultsWe 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. LimitationsObservational design, variation around measurement times, missing data. ConclusionsDepressive 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.
Highlights
The global burden of depression is considerable and adolescence is a key period in the development and presentation of first symptoms (Kwong, Manley, et al, 2019; Thapar et al, 2012)
Some of these studies have collected repeated measures of both internalising and externalising symptoms, with the aim to isolate the potential contribution of each to academic performance and to test the so-called cascade hy potheses (Masten et al, 2005; Moilanen et al, 2010; Vaillancourt et al, 2013; Van Der Ende et al, 2016; Zhang et al, 2019). Results from these studies point to a negative correlation between externalising symptoms and later academic achievement, with lower achievement being associated with higher depressive symptoms at a further point. Another set of studies focused on depressive symptoms and their associations with academic achievement during adolescence solely (Cole et al, 1996; Obradovic et al, 2010), with important variations in the results reported across studies that suggest a complex and potentially bidirectional as sociation that might be moderated by sex
We considered Akaike’s (AIC) and Bayesian information criteria (BIC), root mean square error of approximation (RMSEA), comparative fit index (CFI), Tucker-Lewis index (TLI), and standardized root mean residual (SRMR)
Summary
The global burden of depression is considerable and adolescence is a key period in the development and presentation of first symptoms (Kwong, Manley, et al, 2019; Thapar et al, 2012). This association remains poorly understood, with substantial uncertainty around its directionality, change over time and co-existence of anxiety and/or externalising symptoms (Fazel et al, 2014; Hale & Viner, 2018). We fitted crosslagged 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. 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
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