Three-month stability of delay and probability discounting measures.

Abstract

Psychopharmacologists are interested in delay and probability discounting because the tendency to discount the value of future and uncertain rewards has been linked with drug dependency. However, relatively little is known about the long-term stability of discounting measures typically studied in clinical psychopharmacology. To evaluate the stability of discounting over a 3-month period, the authors compared points of subjective equality (indifference points) with those collected from the same subjects 3 months earlier. Seven delay periods, ranging from 1 week to 25 years, and 7 probability values, ranging from .95 to .05, were assessed in an undergraduate sample (n=22, delay discounting; n=18, probability discounting). The authors examined both differential stability (stability of individual differences) and absolute stability (stability of the group mean) of delay and probability discounting measures as well as their respective indifference points. The results demonstrate that standard delay and probability discounting parameters (e.g., hyperbolic k and area under the curve) had both differential stability and absolute stability across 3 months. Moreover, most indifference points in the delay and probability discounting tasks demonstrated both differential and absolute stability. All together, these results suggest that delay and probability parameters are stable enough to predict future behavior, such as substance abuse. Additional findings indicated that a hyperbolic function fitted the data better than an exponential function and that delay and probability discounting parameters were not significantly correlated.

Determinants of Early Alcohol Use In Healthy Adolescents: The Differential Contribution of Neuroimaging and Psychological Factors

“…However, the MID task shows a fairly high test-retest reliability of relevant brain areas during reward processing (Fliessbach et al, 2010), specifically in the right striatum in response to alcohol cues in alcohol-dependent patients (Schacht et al, 2011). In addition, behavioral variables such as risk taking (White et al, 2008) and delay discounting (Ohmura et al, 2006) were also shown to be relatively stable. Although none of these studies investigated the same tasks used in the present study, they report adequate test-retest reliabilities of risk taking and reward processing and thus indicate that Determinants of early alcohol use in adolescents F Nees et al our present results might not be dependent on differences in reliability between measures.…”

An algorithm for identifying nonsystematic delay-discounting data.

“…Moreover, researchers have commonly identified those data sets with an R 2 less than some threshold (e.g., R 2 < 0, .3, .4, or .5) and eliminated these data sets from comparative analyses (e.g., Acheson, Richards, de Wit, 2007;Epstein et al, 2003;Green & Myerson, 1995;Hamidovic, Kang, & de Wit, 2008;Myerson & Green, 1995;Ohmura et al, 2006;McDonald, Schleifer, Richards, & de Wit, 2003;Reynolds, Richards, & de Wit;Richards, Zhang, Mitchell, & de Wit, 1999;Reynolds & Schiffbauer, 2004;Simpson & Vuchinich, 2000). An R 2 value is obtained by using nonlinear regression to fit the data to a mathematical discounting model.…”

Testing the Reliability of Delay Discounting of Ten Commodities Using the Fill-in-the-Blank Method

“…Again, the discounting data were analyzed using a hyperbolic function and the reported correlations ranged from .71 to .90. Ohmura, Takahashi, Kitamura, and Wehr (2006) conducted a similar procedure but increased the delay between the two completions of the discounting task to 3 months and also analyzed their data with both a hyperbolic function and with area under the discounting curve (Myerson, Green, & Warusawitharana, 2001). For the hyperbolic function, the correlation between tests dropped to .60.…”