227 Poor sleep as a predictor of COVID-19 related stress, fear and sadness in young adolescents: a longitudinal study

Abstract

have been shown to be strongly impacted by the COVID-19 pandemic, with most studies focusing on adults. The current study investigates psychological distress in young adolescents during the pandemic, and specifically, whether poor sleep before the pandemic predicts psychological distress. Methods: Self-report data were analyzed from 3099 adolescents (9-10 years at baseline) in the population-based, demographically diverse , Adolescent Brain Cognitive Development (ABCD) study across three pre-pandemic annual visits and 3 monthly time points during the COVID-19 pandemic (ages 11-13 years). At each assessment, children and their guardians completed questionnaires including those about sleep, environment, and psychological wellbeing. Gradient Boosted Tree machine learning algorithms were used to identify the strongest predictors of pandemic-related psychological distress in individuals. We trained models using pre-pandemic sleep measures along with demographics, economic, and social measures during the pandemic. We evaluated the performance of the models using area under curve (AUC) metrics and interpreted the models by using the recently proposed SHapley Additive exPlanations methodology. Results: Pandemic-related perceived stress, fear and sadness were accurately detected with our classifiers (AUC = 0.83 for perceived stress, AUC = 0.73 for fear, AUC = 0.79 for sadness). Across all models, shorter sleep duration, prolonged sleep onset latency, and longer time between waking and getting out of bed predicted greater distress. Moreover, female sex, and pandemic-related factors, including greater family conflict, fewer economic resources, and more screen time contributed to prediction performance in all three models.