Predicting Impulsive Choices: Development of a Novel Experimental Task

AimsDue to the multifaceted nature of "impulsivity", its measurement remains fragmented. Here, we developed the Risky Social Choices task to provide evidence for its validity and reliability, while testing the hypothesis that impaired access to implicit knowledge of negative long-term consequences is of distinct importance for "impulsive" decision-making in a general population sample. MethodsForty participants chose whether to engage in risk-taking behaviors, which combined web-based AI-generated videos with narrated hypothetical scenarios and measured worries related to negative long-term consequences, approach-related motivation for short-term rewards, response time to and accuracy of recognizing degraded auditory prime words denoting negative long-term consequences. ResultsA pre-registered multi-step regression model was constructed with worry, motivation, response time and accuracy as predictors and percentage of risky choices as the outcome. Among all predictors, only prime word recognition accuracy was significantly negatively associated with risky choices, confirming our hypothesis of the role of reduced implicit access to negative long-term consequences in risk-taking decisions. In contrast, approach-related motivation for rewards was the only predictor significantly positively related to percentage of risky choices. DiscussionAs predicted, the negative association between risky choices and implicit access to negative long-term consequences supports its role as a distinct aspect of "impulsivity". The novel task successfully captured this aspect, paving the way for a more precise neurocognitive characterization of clinical conditions where "impulsivity" plays a key role. The findings unveil the importance of implicit social sequential knowledge for impulsivity in neurotypical populations, so far only investigated in patients with brain lesions.