Risk preferences impose a hidden distortion on measures of choice impulsivity

Measuring temporal discounting through the use of intertemporal choice tasks is now the gold standard method for quantifying human choice impulsivity (impatience) in neuroscience, psychology, behavioral economics, public health and computational psychiatry. A recent area of growing interest is individual differences in discounting levels, as these may predispose to (or protect from) mental health disorders, addictive behaviors, and other diseases. At the same time, more and more studies have been dedicated to the quantification of individual attitudes towards risk, which have been measured in many clinical and non-clinical populations using closely related techniques. Economists have pointed to interactions between measurements of time preferences and risk preferences that may distort estimations of the discount rate. However, although becoming standard practice in economics, discount rates and risk preferences are rarely measured simultaneously in the same subjects in other fields, and the magnitude of the imposed distortion is unknown in the assessment of individual differences. Here, we show that standard models of temporal discounting —such as a hyperbolic discounting model widely present in the literature which fails to account for risk attitudes in the estimation of discount rates— result in a large and systematic pattern of bias in estimated discounting parameters. This can lead to the spurious attribution of differences in impulsivity between individuals when in fact differences in risk attitudes account for observed behavioral differences. We advance a model which, when applied to standard choice tasks typically used in psychology and neuroscience, provides both a better fit to the data and successfully de-correlates risk and impulsivity parameters. This results in measures that are more accurate and thus of greater utility to the many fields interested in individual differences in impulsivity.

通过跨期选择任务（intertemporal choice tasks）测量时间折扣（temporal discounting），现已成为神经科学、心理学、行为经济学、公共卫生及计算精神病学领域量化人类选择冲动性（即不耐受性）的金标准方法。近年来，折扣水平的个体差异愈发受到学界关注，因其可能使个体易患（或抵御）精神健康障碍、成瘾行为及其他疾病。与此同时，越来越多研究致力于量化个体风险态度，这类测量在诸多临床与非临床人群中均采用密切相关的实验技术开展。经济学家指出，时间偏好与风险偏好的测量间存在交互作用，该作用可能会扭曲折扣率的估计结果。尽管在经济学领域，同时测量折扣率与风险偏好已成为常规操作，但在其他学科中，研究者极少在同一批受试者中同步开展这两类测量，且针对个体差异评估中此类交互作用导致的扭曲程度，目前仍不明晰。本研究表明，现有时间折扣经典模型——如学界广泛应用的、未在折扣率估计中纳入风险态度的双曲线折扣模型（hyperbolic discounting model）——会在估计的折扣参数中产生显著且系统性的偏差模式。这可能会导致研究者将观测到的行为差异虚假归因于个体间的冲动性差异，而实际上此类差异源于风险态度的不同。本文提出了一种改进模型，将其应用于心理学与神经科学中常用的标准选择任务时，该模型不仅能对数据实现更优拟合，还可成功消除风险与冲动性参数间的相关性。由此得到的测量指标更为精准，因而对于诸多关注冲动性个体差异的研究领域而言，具备更高的应用价值。