The degree to which real and hypothetical rewards were discounted across delays ranging from 6 hr to 1 year was explored in a within-subjects design. An adjusting-amounts procedure was used to estimate the subjective value of real and hypothetical rewards at each delay. A hyperbolic discounting function provided a significantly better fit to individual participants' preferences than did an exponential function. No significant effect of reward type on degree of hyperbolic discounting or area under the discounting curves was detected. These findings offer some support for the validity of using hypothetical rewards to estimate discounting rates in substance-abusing and other populations, but caution is suggested because this support is gleaned from a failure to detect an effect of reward type.

Prior studies comparing discounting of delayed hypothetical or potentially real rewards have reported no differences, but they used within-subjects designs. This raises the possibility that participants remembered their choices in one condition and repeated them in the other. In Experiment 1, between-subjects comparisons were made with an adjusting-amount procedure. No significant effect of reward type on delay discounting was detected. Experiment 2 increased the proportion of real rewards and made between- and within-subject comparisons. These comparisons also failed to reveal a significant effect of reward type. Although these findings are consistent with prior findings, caution is urged because choices involving hypothetical rewards have yet to be compared with choices involving real rewards (i.e., the consequences of every choice are obtained) in an experiment using forced-choice trials and steady-state methodology.

Technology-based interventions to promote health are expanding rapidly. Assessing the preliminary efficacy of these interventions can be achieved by employing single-case experiments (sometimes referred to as n-of-1 studies). Although single-case experiments are often misunderstood, they offer excellent solutions to address the challenges associated with testing new technology-based interventions. This paper provides an introduction to single-case techniques and highlights advances in developing and evaluating single-case experiments, which help ensure that treatment outcomes are reliable, replicable, and generalizable. These advances include quality control standards, heuristics to guide visual analysis of time-series data, effect size calculations, and statistical analyses. They also include experimental designs to isolate the active elements in a treatment package and to assess the mechanisms of behavior change. The paper concludes with a discussion of issues related to the generality of findings derived from single-case research and how generality can be established through replication and through analysis of behavioral mechanisms.

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The patch did not attenuate delay discounting or smoking after a period of deprivation, but contingencies for abstinence significantly decreased smoking. Higher rates of delay discounting were related to smoking in a model of abstinence reinforcement treatment.