Wyngaarden James B, Yang Yi, Dennison Jeffrey B, Smith David V
Temple University, Philadelphia, PA, USA.
University of Pennsylvania, Philadelphia, PA, USA.
Data Brief. 2025 Jun 27;61:111844. doi: 10.1016/j.dib.2025.111844. eCollection 2025 Aug.
How individuals make decisions under ambiguity (i.e., uncertain situations where the probability of an outcome is unknown) has been related to numerous individual differences of clinical importance including aging, substance use, and autism spectrum disorders. Despite this, many studies rely on a max-min model of ambiguity decision-making, which assumes that individuals evaluate ambiguous options based solely on worst-case and best-case scenarios. However, this approach does not account for the role of individual beliefs about underlying probabilities, which can significantly shape decision-making behavior. We introduce a novel task, the Linked Colored Lottery Task, in an in-person (N= 53) and online sample (N= 300) which allows for analyses that examine the effect of these beliefs. Along with this novel task, demographic information and data for several personality and clinical questionnaires were collected. By incorporating measures that capture differences in probability beliefs, this dataset enables researchers to examine how ambiguity-related decision-making varies beyond max-min assumptions, providing a richer understanding of how individuals form and act upon beliefs about probabilities. These data offer opportunities to explore how individual tendencies-such as risk preferences, cognitive styles, and clinical traits-interact with beliefs about uncertainty, advancing both theoretical and applied perspectives on decision-making under ambiguity.
个体在模糊性（即结果概率未知的不确定情况）下如何做出决策，这与许多具有临床重要性的个体差异有关，包括衰老、物质使用和自闭症谱系障碍。尽管如此，许多研究依赖于模糊性决策的最大-最小模型，该模型假设个体仅基于最坏情况和最好情况来评估模糊选项。然而，这种方法没有考虑个体对潜在概率的信念所起的作用，而这种信念会显著影响决策行为。我们引入了一项新任务，即关联彩色彩票任务，在一个线下样本（N = 53）和一个线上样本（N = 300）中进行，该任务允许进行分析以检验这些信念的影响。除了这项新任务，还收集了人口统计学信息以及几份人格和临床问卷的数据。通过纳入能够捕捉概率信念差异的测量方法，这个数据集使研究人员能够研究模糊性相关决策在最大-最小假设之外是如何变化的，从而更深入地理解个体如何形成关于概率的信念并据此行动。这些数据为探索个体倾向（如风险偏好、认知风格和临床特征）如何与关于不确定性的信念相互作用提供了机会，推动了关于模糊性下决策的理论和应用视角的发展。
