We often forego a larger future reward in order to obtain a smaller reward immediately, known as impatient intertemporal choice. The current study investigated the role of Pavlovian-to-instrumental transfer (PIT) as a mechanism contributing to impatient intertemporal choice, following a theoretical framework proposing that cues associated with immediate gratification trigger a Pavlovian approach response, interfering with goal-directed (instrumental) inhibitory behavior. We developed a paradigm in which participants first learned to make instrumental go/no-go responses in order to win rewards and avoid punishments. Next, they learned the associations between Pavlovian cues and rewards varying in amount and delay. Finally, we tested whether these (task-irrelevant) cues exerted transfer effects by influencing instrumental actions while participants again completed the go/no-go task. Across two experiments, Pavlovian cues associated with larger (versus smaller) and immediate (versus delayed) rewards were evaluated more positively, reflecting the successful acquisition of Pavlovian cue–outcome associations. These findings replicated the previously reported classical transfer effect of reward amount on instrumental behavior, as large (versus smaller) cues increased instrumental approach. In contrast, we found no evidence for the hypothesized transfer effects for reward delay, contrary to the proposed role of PIT in impatient intertemporal choice. These results suggest that although both reward amount and delay were important in the evaluation of cues, only the amount associated with cues influenced instrumental choice. We provide concrete suggestions for future studies, addressing instrumental outcome identity, competition between cue–amount and cue–delay associations, and individual differences in response to Pavlovian cues.

Recent research has shown that risk and reward are positively correlated in many environments, and that people have internalized this association as a “risk-reward heuristic”: when making choices based on incomplete information, people infer probabilities from payoffs and vice-versa, and these inferences shape their decisions. We extend this work by examining people’s expectations about another fundamental trade-off — that between monetary reward and delay. In 2 experiments (total N = 670), we adapted a paradigm previously used to demonstrate the risk-reward heuristic. We presented participants with intertemporal choice tasks in which either the delayed reward or the length of the delay was obscured. Participants inferred larger rewards for longer stated delays, and longer delays for larger stated rewards; these inferences also predicted people’s willingness to take the delayed option. In exploratory analyses, we found that older participants inferred longer delays and smaller rewards than did younger ones. All of these results replicated in 2 large-scale pre-registered studies with participants from a different population (total N = 2138). Our results suggest that people expect intertemporal choice tasks to offer a trade-off between delay and reward, and differ in their expectations about this trade-off. This “delay-reward heuristic” offers a new perspective on existing models of intertemporal choice and provides new insights into unexplained and systematic individual differences in the willingness to delay gratification.

Preferences about delayed rewards and preferences about risk are central to the literature on decision making. Several proposals suggest that such preferences arise from a single process and thus predict strong associations between preferences about delay and risk. Although there is a wealth of data on this association, the evidence is inconclusive; some studies have reported significant associations but many have not. Consequently, it is unclear whether the association between delay preferences and risk preferences is strong enough to support single-process theories. To further explore this question, we took a meta-analytic approach surveying 26 studies totaling 32 effect sizes. Results reveal a small to moderate association between risk preferences and delay preferences. This result provides little support for existing proposals because the observed relationship is no stronger than associations observed between either delay preferences or risk preferences and other variables. Moderating variables provide some explanation for inconsistencies across studies. Implications, including the apparent discrepancy between this literature and the conventional construct of impulsivity, are also discussed.

How do people make decisions between an immediate but small reward and a delayed but large one? The outcome of such decisions indicates that people discount rewards by their delay and hence these outcomes are well described by discounting functions. However, to understand irregular decisions and dysfunctional behavior one needs models which describe how the process of making the decision unfolds dynamically over time: how do we reach a decision and how do sequential decisions influence one another? Here, we present an attractor model that integrates into and extends discounting functions through a description of the dynamics leading to a final choice outcome within a trial and across trials. To validate this model, we derive qualitative predictions for the intra-trial dynamics of single decisions and for the inter-trial dynamics of sequences of decisions that are unique to this type of model. We test these predictions in four experiments based on a dynamic delay discounting computer game where we study the intra-trial dynamics of single decisions via mouse tracking and the inter-trial dynamics of sequences of decisions via sequentially manipulated options. We discuss how integrating decision process dynamics within and across trials can increase our understanding of the processes underlying delay discounting decisions and, hence, complement our knowledge about decision outcomes.

The two most influential models in delay discounting research have been the exponential (E) and hyperbolic (H) models. We develop a new methodology to design binary choice questions such that exponential and hyperbolic discount rates can be purposefully manipulated to make their rate parameters orthogonal (Pearson’s R = 0), negatively correlated (R = –1), positively correlated (R = +1), or to hold one rate constant while allowing the other to vary. Then we extend the method to similarly contrast different versions of the hyperboloid model. The arithmetic discounting model (A), which is based on differences between present and future rewards rather than their ratios, may easily be made orthogonal to any other pair of models. Our procedure makes it possible to design choice stimuli that precisely vary the relationship between different discount rates. However, the additional control over the correlation between different discount rate parameters may require the researcher to either restrict the range that those rate parameters can take, or to expand the range of times the participant must wait for future rewards.

We investigated whether people’s risk taking tendency established in one domain (gains or losses) carries over to the other domain. Participants played a game in which they made repeated decisions between a fixed payoff and a risky option, where the outcome of the risky option depended on whether they had responded correctly on a difficult perceptual-memory task. In some trials, participants played to gain points; on others, they played to avoid losing points. In two studies, we observed the following pattern of results. 1) Participants risked less on gain trials than on loss trials. 2) This difference in risk taking persisted (carried over) when the domain changed from gains to losses and vice versa (with the effect of experiencing losses first being stronger than the effect of experiencing gains first). 3) There was no analogous carryover effect on responses to a delay discounting measure, but there was a carryover effect on responses on a risk attitude measure. We compare these results with those from other recent studies and discuss various ways of explaining them.

There is a growing interest in studying individual differences in choices that involve trading off reward amount and delay to delivery because such choices have been linked to involvement in risky behaviors, such as substance abuse. The most ubiquitous proposal in psychology is to model these choices assuming delayed rewards lose value following a hyperbolic function, which has one free parameter, named discounting rate. Consequently, a fundamental issue is the estimation of this parameter. The traditional approach estimates each individual’s discounting rate separately, which discards individual differences during modeling and ignores the statistical structure of the population. The present work adopted a different approximation to parameter estimation: each individual’s discounting rate is estimated considering the information provided by all subjects, using state-of-the-art Bayesian inference techniques. Our goal was to evaluate whether individual discounting rates come from one or more subpopulations, using Mazur’s (1987) hyperbolic function. Twelve hundred eighty-four subjects answered the Intertemporal Choice Task developed by Kirby, Petry and Bickel (1999). The modeling techniques employed permitted the identification of subjects who produced random, careless responses, and who were discarded from further analysis. Results showed that one-mixture hierarchical distribution that uses the information provided by all subjects suffices to model individual differences in delay discounting, suggesting psychological variability resides along a continuum rather than in discrete clusters. This different approach to parameter estimation has the potential to contribute to the understanding and prediction of decision making in various real-world situations where immediacy is constantly in conflict with magnitude.

Laboratory studies of choice and decision making among real monetary rewards typically use smaller real rewards than those common in real life. When laboratory rewards are large, they are almost always hypothetical. In applying laboratory results meaningfully to real-life situations, it is important to know the extent to which choices among hypothetical rewards correspond to choices among real rewards and whether variation of the magnitude of hypothetical rewards affects behavior in meaningful ways. The present study compared real and hypothetical monetary rewards in two experiments. In Experiment 1, participants played a temporal discounting game that incorporates the logic of a repeated prisoner’s-dilemma (PD) game versus tit-for-tat; choice of one alternative (“defection” in PD terminology) resulted in a small-immediate reward; choice of the other alternative (“cooperation” in PD terminology) resulted in a larger reward delayed until the following trial. The larger-delayed reward was greater for half of the groups than for the other half. Rewards also differed in type across groups: multiples of real nickels, hypothetical nickels, or hypothetical hundred-dollar bills. All groups significantly increased choice of the larger delayed reward over the 40 trials of the experiment. Over the last 10 trials, cooperation was significantly higher when the difference between larger and smaller hypothetical rewards was greater. Reward type (real or hypothetical) made no significant difference in cooperation on most measures. In Experiment 2, real and hypothetical rewards were compared in social discounting—the decrease in value to the giver of a reward as social distance increases to the receiver of the reward. Social discount rates were well described by a hyperbolic function. Discounting rates for real and hypothetical rewards did not significantly differ. These results add to the evidence that results of experiments with hypothetical rewards validly apply in everyday life.

Although theories from economics and evolutionary biology predict that one's age, health, and survival probability should be associated with one's subjective discount rate (SDR), few studies have empirically tested for these links. Our study analyzes in detail how the SDR is related to age, health, and survival probability, by surveying a sample of individuals in townships around Durban, South Africa. In contrast to previous studies, we find that age is not significantly related to the SDR, but both physical health and survival expectations have a U-shaped relationship with the SDR. Individuals in very poor health have high discount rates, and those in very good health also have high discount rates. Similarly, those with expected survival probability on the extremes have high discount rates. Therefore, health and survival probability, and not age, seem to be predictors of one's SDR in an area of the world with high morbidity and mortality.

Delay discounting paradigms have gained widespread popularity across clinical research. Given the prevalence in the field, researchers have set lofty expectations for the importance of delay discounting as a key transdiagnostic process and a ‘core’ process underlying specific domains of dysfunction (e.g. addiction). We believe delay discounting has been prematurely reified as, in and of itself, a core process underlying psychological dysfunction, despite significant concerns with the construct validity of discounting rates. Specifically, high delay discounting rates are only modestly related to measures of psychological dysfunction and therefore are not ‘core’ to these more complex behavioral problems. Furthermore, discounting rates do not appear to be specifically related to any disorder(s) or dimension(s) of psychopathology. This raises fundamental concerns about the utility of discounting, if the measure is only loosely associated with most forms of psychopathology. This stands in striking contrast to claims that discounting can serve as a ‘marker’ for specific disorders, despite never demonstrating adequate sensitivity or specificity for any disorder that we are aware of. Finally, empirical evidence does not support the generalizability of discounting rates to other decisions made either in the lab or in the real-world, and therefore discounting rates cannot and should not serve as a summary measure of an individual's decision-making patterns. We provide recommendations for improving future delay discounting research, but also strongly encourage researchers to consider whether the empirical evidence supports the field's hyper-focus on discounting.