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Delayed reward discounting (DRD) refers to the extent to which an individual devalues a reward based on a temporal delay and is known to be elevated in individuals with substance use disorders and many mental illnesses. DRD has been linked previously with both features of brain structure and function, as well as various behavioral, psychological, and life-history factors. However, there has been little work on the neurobiological and behavioral antecedents of DRD in childhood. This is an important question, as understanding the antecedents of DRD can provide signs of mechanisms in the development of psychopathology. The present study used baseline data from the Adolescent Brain Cognitive Development Study ( N = 4,042) to build machine learning models to predict DRD at the first follow-up visit, 1 year later. In separate machine learning models, we tested elastic net regression, random forest regression, light gradient boosting regression, and support vector regression. In five-fold cross-validation on the training set, models using an array of questionnaire/task variables were able to predict DRD, with these findings generalizing to a held-out (i.e., "lockbox") test set of 20% of the sample. Key predictive variables were neuropsychological test performance at baseline, socioeconomic status, screen media activity, psychopathology, parenting, and personality. However, models using magnetic resonance imaging (MRI)-derived brain variables did not reliably predict DRD in either the cross-validation or held-out test set. These results suggest a combination of questionnaire/task variables as antecedents of excessive DRD in late childhood, which may presage the development of problematic substance use in adolescence. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

There is some evidence that cannabis use is associated with lower cognitive performance and symptoms of attention-deficit/hyperactivity disorder (ADHD), but the existing literature is relatively inconsistent, potentially due to small samples in previous studies. Using a dimensional design, the current study examined cannabis use severity and age of first cannabis use in relation to neurocognitive performance and ADHD symptoms in a large sample of community adults ( N = 1,008, M age = 38.49, 56.0% female). Participants were assessed for cannabis involvement, neurocognitive performance, and ADHD symptoms. Dimensional relationships were investigated using multiple hierarchical regressions. Using a covariate model of age, income, sex, alcohol use, and tobacco use, severity of cannabis involvement was significantly associated with greater endorsement of both hyperactive-impulsive and inattentive ADHD symptoms but not with any other cognitive measures in the full sample. Exploratory analyses found greater cannabis use severity was associated with digit span forward and hyperactive ADHD symptoms in young adults ( n = 371) and was associated with greater delay discounting, hyperactive, and impulsive ADHD symptoms in high-risk cannabis users ( n = 161). Age of first cannabis use was not significantly associated with any neurocognitive variables or ADHD symptomatology in all analyses. The current findings provide evidence of a link between current cannabis misuse and both hyperactive and inattentive ADHD symptoms in general, and possible links to attention and impulsive delay discounting in subgroups of cannabis users, but no associations in other cognitive domains or implication of earlier initiation of cannabis use in relation to cognitive performance or ADHD. (PsycInfo Database Record (c) 2020 APA, all rights reserved).