Executive Function During Adolescence: Age-Related Variations and Mental Health Associations
Poster No:
730
Submission Type:
Abstract Submission
Authors:
Yang Li1, Zaixu Cui1
Institutions:
1Chinese Institute for Brain Research, Beijing, Beijing, China
First Author:
Co-Author:
Introduction:
Executive Function (EF) is a crucial set of cognitive abilities that impact academic success, social interactions, and emotional regulation. Adolescence is a key stage for EF development, characterized by significant maturation of the prefrontal cortex and anterior cingulate cortex (Constantinidis et al., 2019), which enhances self-regulation, planning, and problem-solving. However, no reference standards exist to quantify individual differences in EF over time, and the relationship between EF development and mental health during adolescence remains unclear, despite strong associations with issues like affective illness (Julian Wenzel et al., 2024) and Attention Deficit Hyperactivity Disorder (Hilton et al., 2004).
Methods:
We evaluated EF performance and mental health in 67,947 adolescents aged 11 to 18 years from primary, middle, and high schools in Yunfu City, Guangdong Province, China, organized on a class-by-class basis. Each participant was randomly assigned to complete one task. EF components-working memory and inhibitory control-were assessed using the N-back task (1-back and 2-back conditions) and the Go/No-Go (GNG) task, respectively. Mental health was measured using the Strengths and Difficulties Questionnaire (SDQ), which evaluates five subscales: emotional problems, conduct problems, hyperactivity, peer problems, and prosocial behavior.
To investigate normative growth patterns of EF, we employed the GAMLSS package in R version 4.2.0, applying it to cross-sectional data to generate growth charts and compute first derivatives across the age span. Age-related variability in EF was assessed by changes in variance and their first derivatives over time. Model fit was evaluated using out-of-sample metrics, and robustness was validated through bootstrap resampling. Furthermore, we first calculated the correlations between EF and mental health, followed by an analysis of the interaction effects between age and EF on psychiatric symptoms using partial R-squared values from generalized additive models (GAM).
To investigate normative growth patterns of EF, we employed the GAMLSS package in R version 4.2.0, applying it to cross-sectional data to generate growth charts and compute first derivatives across the age span. Age-related variability in EF was assessed by changes in variance and their first derivatives over time. Model fit was evaluated using out-of-sample metrics, and robustness was validated through bootstrap resampling. Furthermore, we first calculated the correlations between EF and mental health, followed by an analysis of the interaction effects between age and EF on psychiatric symptoms using partial R-squared values from generalized additive models (GAM).
Results:
After applying the specified criteria, we included data from 17,409 participants for the GNG task, 15,966 for the 1-back task, and 10,177 for the 2-back task. We delineated the developmental trajectories of EF during adolescence to capture interindividual variability across the three tasks (Fig. 1A). The results revealed a linear growth pattern for EF, with trajectories showing continued significant improvements in inhibitory control and working memory capacity throughout adolescence. Additionally, we observed a notable decrease in the standard deviation (SD) of the normative scores with age, indicating a reduction in EF variability across the population as adolescents mature (Fig. 1B).
We also identified significant associations between EF normative scores and various mental health dimensions (Fig. 2A), including emotional problems (1-back: r = 0.016, P = 0.012), peer problems (GNG: r = -0.10, P = 0.001; 1-back: r = -0.11, P = 0.001; 2-back: r = -0.12, P = 0.001), conduct problems (GNG: r = -0.02, P = 0.001; 1-back: r = -0.02, P = 0.017; 2-back: r = -0.08, P = 0.012), hyperactivity (GNG: r = -0.05, P = 0.001; 2-back: r = -0.02, P = 0.001), and prosocial behavior (GNG: r = 0.07, P = 0.001; 1-back: r = 0.07, P = 0.001; 2-back: r = 0.08, P = 0.001). Importantly, these associations weakened with age. Specifically, the correlations between inhibitory control (GNG, P ＜0.01, partial R² = 0.001) and low-load working memory (1-back, P＜0.01, partial R² = 0.001) with hyperactivity significantly declined as adolescents matured (Fig. 2B).
We also identified significant associations between EF normative scores and various mental health dimensions (Fig. 2A), including emotional problems (1-back: r = 0.016, P = 0.012), peer problems (GNG: r = -0.10, P = 0.001; 1-back: r = -0.11, P = 0.001; 2-back: r = -0.12, P = 0.001), conduct problems (GNG: r = -0.02, P = 0.001; 1-back: r = -0.02, P = 0.017; 2-back: r = -0.08, P = 0.012), hyperactivity (GNG: r = -0.05, P = 0.001; 2-back: r = -0.02, P = 0.001), and prosocial behavior (GNG: r = 0.07, P = 0.001; 1-back: r = 0.07, P = 0.001; 2-back: r = 0.08, P = 0.001). Importantly, these associations weakened with age. Specifically, the correlations between inhibitory control (GNG, P ＜0.01, partial R² = 0.001) and low-load working memory (1-back, P＜0.01, partial R² = 0.001) with hyperactivity significantly declined as adolescents matured (Fig. 2B).
Conclusions:
This study provides a normative reference for quantifying individual variations in EF development during adolescence and offers insights into the dynamic relationship between EF and mental health, highlighting significant age-related changes. Our findings suggest that early adolescence is a critical period for EF interventions, potentially improving mental health outcomes.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism)
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Higher Cognitive Functions:
Executive Function, Cognitive Control and Decision Making 1
Learning and Memory:
Working Memory
Perception, Attention and Motor Behavior:
Attention: Visual
Keywords:
Other - executive function, adolescent metal health, normative model, adolescent cognitive development
1|2Indicates the priority used for review
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Provide references using APA citation style.
Hilton, R. A., Tozzi, L., Nesamoney, S., Kozlowska, K., Kohn, M. R., Harris, A., ... & Williams, L. M. (2024). Transdiagnostic neurocognitive dysfunction in children and adolescents with mental illness. Nature Mental Health, 2(3), 299-309.
Constantinidis, C., & Luna, B. (2019). Neural substrates of inhibitory control maturation in adolescence. Trends in neurosciences, 42(9), 604-616.