From error to insight: Removing non-systematic responding data in the delay discounting task may introduce systematic bias

Delay discounting (DD), which reflects a tendency to devalue rewards as the time to their receipt increases, is associated with health behaviors such as sleep disturbances, obesity, and externalizing behavior among adolescents. Response patterns characterized by inconsistent or unexpected reward valuation, called non-systematic responding (NSR), may also predict health outcomes. Many researchers flag and exclude NSR trials prior to analysis, which could lead to systematic bias if NSR (a) varies by demographic characteristics or (b) predicts health outcomes. Thus, in this study we characterized NSR and examined its potential beyond error by comparing it against DD with a secondary data analysis of the Adolescent Brain Cognitive Development (ABCD) Study—a population-based study that tracked youths (N = 11,948) annually from 8 to 11 years of age over 4 years. We assessed DD and NSR using the Adjusting Delay Discounting Task when youths were approximately 9.48 years old (SD = 0.51). We also examined three maladaptive health outcomes annually: sleep disturbances, obesity, and externalizing psychopathology. Our analysis revealed variations in NSR across races, ethnicities, and body mass index categories, with no significant differences observed by sex or gender. Notably, NSR was a stronger predictor of obesity and externalizing psychopathology than DD and inversely predicted the growth trajectory of obesity. These findings suggest that removing NSR patterns could systematically bias analyses given that NSR may capture unexplored response variability. This study demonstrates the significance of NSR and underscores the necessity for further research on how to manage NSR in future DD studies.