Abstract

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.

Highlights

  • Time preference, or the preference of typical humans for immediate over delayed rewards, has long been a subject of study in economics, finance, neuroscience, and psychology

  • As our goal is to propose this methodology to the fields that do not already employ it, we used simple standard binary choice tasks widely used in the psychology and neuroscience literature [24, 25, 54, 55] in a real-world non-expert sample

  • The correlation between α and the κ derived from model Nonlinear utility Hyperbolic discounting (NLH) was not significant (Pearson’s r = -0.02, p = 0.861). These results show that the NLH model yields a discount parameter that is more precise and allows for κ and α to reflect distinct aspects of decision-making rather than being conflated as is the case with estimates derived from the traditional model Linear utility Hyperbolic discounting (LH)

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Summary

Introduction

The preference of typical humans for immediate over delayed rewards, has long been a subject of study in economics, finance, neuroscience, and psychology. Temporal discounting describes this preference mathematically by quantifying how the subjective value of a payoff decreases as the time to its receipt increases. Risk distorts impulsivity data collection and analysis, decision to publish, or preparation of the manuscript

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