Cognitive and Emotional Predictors of Decision-Making in Adults: Roles of Cognitive Functions and Emotion Regulation Difficulties.

Abstract

Objectives: The Iowa Gambling Task (IGT) is a widely used measure of decision-making that mimics real-life situations involving uncertainty and reward. While prior research has separately explored the roles of cognitive functions (e.g., intelligence) and non-cognitive factors (e.g., emotion regulation), few have examined their combined and relative influence. This study aimed to clarify how cognitive abilities and emotion regulation difficulties contribute to decision-making under ambiguity and risk, as assessed by the IGT.

Methods: Fifty healthy adults completed a modified version of the IGT, a battery of cognitive tasks measuring planning, attention, and working memory, and the Japanese version of the Difficulties in Emotion Regulation Scale (J-DERS). Zero-order and partial correlations as well as hierarchical regression analyses were conducted.

Results: Zero-order correlations indicated significant positive associations between advantageous IGT performance and both working memory and attention. These associations remained significant after controlling J-DERS scores in partial correlations. However, hierarchical regression analyses revealed that neither cognitive abilities nor emotion regulation difficulties significantly predicted overall IGT performance. Contrary to expectations, emotion regulation difficulties were not significantly related to risky choices, suggesting a weaker role than previously attributed to emotional intelligence.

Conclusions: The findings suggest that cognitive functions, particularly attentional control, are more strongly associated with advantageous decision-making, especially during later stages of the task. These findings underscore the primacy of cognitive functions in implicit decision-making. Study limitations include a small sample size and a lack of neurophysiological data, highlighting the need for future studies with neuroimaging and larger samples.