An ecological assessment of decision-making under risk and ambiguity through the virtual serious game Kalliste Decision Task

TL;DR

The Kalliste Decision Task is a new, user-friendly tool that better captures the complexity of real-world decision-making compared to traditional methods.

Contribution

Introduces Kalliste Decision Task as an ecologically valid, comprehensive method for assessing decision-making under risk and ambiguity.

Findings

KDT showed high usability and user satisfaction according to the USEQ scores.

KDT outcomes correlated with traditional measures of risk attitudes and decision-making performance.

Hierarchical clustering identified three distinct decision-making profiles among participants.

Abstract

Traditional methods for evaluating decision-making provide valuable insights yet may fall short in capturing the complexity of this cognitive capacity, often providing insufficient for the multifaceted nature of decisions. The Kalliste Decision Task (KDT) is introduced as a comprehensive, ecologically valid tool aimed at bridging this gap, offering a holistic perspective on decision-making. In our study, 81 participants completed KDT alongside established tasks and questionnaires, including the Mixed Gamble Task (MGT), Iowa Gambling Task (IGT), and Stimulating & Instrumental Risk Questionnaire (S&IRQ). They also completed the User Satisfaction Evaluation Questionnaire (USEQ). The results showed excellent usability, with high USEQ scores, highlighting the user-friendliness of KDT. Importantly, KDT outcomes showed significant correlations with classical decision-making variables, shedding light on participants’ risk attitudes (S&IRQ), rule-based decision-making (MGT), and performance in ambiguous contexts (IGT). Moreover, hierarchical clustering analysis of KDT scores categorized participants into three distinct profiles, revealing significant differences between them on classical measures. The findings highlight KDT as a valuable tool for assessing decision-making, addressing limitations of traditional methods, and offering a comprehensive, ecologically valid approach that aligns with the complexity and heterogeneity of real-world decision-making, advancing research and providing insights for understanding and assessing decision-making across multiple domains.

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