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.
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