IMPORTANCE Delay discounting is a behavioral economic index of impulsive preferences for smaller-immediate or larger-delayed rewards that is argued to be a transdiagnostic process across health conditions. Studies suggest some psychiatric disorders are associated with differences in discounting compared with controls, but null findings have also been reported. OBJECTIVE To conduct a meta-analysis of the published literature on delay discounting in people with psychiatric disorders. DATA SOURCES PubMed, MEDLINE, PsycInfo, Embase, and Web of Science databases were searched through December 10, 2018. The psychiatric keywords used were based on DSM-IV or DSM-5 diagnostic categories. Collected data were analyzed from December 10, 2018, through June 1, 2019. STUDY SELECTION Following a preregistered Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol, 2 independent raters reviewed titles, abstracts, and full-text articles. English-language articles comparing monetary delay discounting between participants with psychiatric disorders and controls were included. DATA EXTRACTION AND SYNTHESIS Hedges g effect sizes were computed and random-effects models were used for all analyses. Heterogeneity statistics, one-study-removed analyses, and publication bias indices were also examined. MAIN OUTCOMES AND MEASURES Categorical comparisons of delay discounting between a psychiatric group and a control group. RESULTS The sample included 57 effect sizes from 43 studies across 8 diagnostic categories. Significantly steeper discounting for individuals with a psychiatric disorder compared with controls was observed for major depressive disorder (Hedges g = 0.37; P = .002; k = 7), schizophrenia (Hedges g = 0.46; P = .004; k = 12), borderline personality disorder (Hedges g = 0.60; P < .001; k = 8), bipolar disorder (Hedges g = 0.68; P < .001; k = 4), bulimia nervosa (Hedges g = 0.41; P = .001; k = 4), and binge-eating disorder (Hedges g = 0.34; P = .001; k = 7). In contrast, anorexia nervosa exhibited statistically significantly shallower discounting (Hedges g =-0.30; P < .001; k = 10). Modest evidence of publication bias was indicated by a statistically significant Egger test for schizophrenia and at the aggregate level across studies. CONCLUSIONS AND RELEVANCE Results of this study appear to provide empirical support for delay discounting as a transdiagnostic process across most of the psychiatric disorders examined; the literature search also revealed limited studies in some disorders, notably posttraumatic stress disorder, which is a priority area for research.

Objective When given the choice between $100 today and $110 in one week, certain people are more likely to choose the immediate, yet smaller reward. The present study examined the relations between temporal discounting rate and body mass while accounting for important demographic variables, depressive symptoms, and behavioral inhibition and approach. Methods After having their heights and weights measured, 100 healthy adults completed the Monetary Choice Questionnaire, the Beck Depression Inventory-II, and the Behavioral Inhibition Scale/Behavioral Approach Scale. Results Overweight and obese participants exhibited higher temporal discounting rates than underweight and healthy weight participants. Temporal discounting rates decreased as the magnitude of the delayed reward increased, even when other variables known to impact temporal discounting rate (i.e., age, education level, and annual household income) were used as covariates. Conclusion A higher body mass was strongly related to choosing a more immediate monetary reward. Additional research is needed to determine whether consideration-of-future-consequences interventions, or perhaps cognitive control interventions, could be effective in obesity intervention or prevention programs.

Reducing the nicotine content of cigarettes may decrease their addiction potential in populations that are highly vulnerable to tobacco addiction. Smokers with psychiatric conditions and socioeconomic disadvantage are more addicted and less likely to quit and experience greater adverse health impacts. Policies to reduce these disparities are needed; reducing the nicotine content in cigarettes should be a policy focus.

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Delay discounting describes the process wherein rewards lose value as a function of their delayed receipt; how quickly rewards lose value is termed the rate of delay discounting. Rates of delay discounting are robust predictors of much behavior of societal importance. One efficient approach to obtaining a human subject's rate of delay discounting is via the 21-and 27-item Monetary Choice Questionnaires, brief dichotomous choice tasks that assess preference between small immediate and larger delayed monetary outcomes. Unfortunately, the scoring procedures for the Monetary Choice Questionnaires are rather complex, which may serve as a barrier to their use. This report details a freely available Excel-based spreadsheet tool that automatically scores Monetary Choice Questionnaire response sets, using both traditional and contemporary/ advanced approaches. An overview of the Monetary Choice Questionnaire and its scoring algorithm is provided. We conclude with general considerations for using the spreadsheet tool.

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We reviewed all school‐based experimental studies with individuals 0 to 18 years published in the Journal of Applied Behavior Analysis (JABA) between 1991 and 2005. A total of 142 articles (152 studies) that met review criteria were included. Nearly all (95%) of these experiments provided an operational definition of the independent variable, but only 30% of the studies provided treatment integrity data. Nearly half of studies (45%) were judged to be at high risk for treatment inaccuracies. Treatment integrity data were more likely to be included in studies that used teachers, multiple treatment agents, or both. Although there was a substantial increase in reporting operational definitions of independent variables, results suggest that there was only a modest improvement in reported integrity over the past 30 years of JABA studies. Recommendations for research and practice are discussed. We thank Heidi Olson‐Tinker, Lisa Dolstra, Veronica McLaughlin, and Mai Van for assistance with the initial preparation of this article. We also are grateful to Michael J. Vance for assistance with data collection.

A mathematical model of operant choice, the generalized matching law was used to analyze play-calling data from the 2004 National Football League season. In all analyses, the relative ratio of passing to rushing plays was examined as a function of the relative ratio of reinforcement, defined as yards gained, from passing versus rushing. Different analyses focused on season-aggregate data for the league as a whole, game-by-game data for the league as a whole, and game-by-game data for individual teams. In all analyses except those for a few individual teams, the generalized matching law accounted for a majority of variance in play calling. The typical play-calling pattern reflected undermatching (suggesting imperfect sensitivity of play calling to yardage-gained reinforcers) and a bias for calling rushing plays. Bias was found to be a function of both the relative risk of turnovers and the relative variability in yards gained associated with passing versus rushing plays. The external validity of the matching analyses was supported by significant correlations between parameters of the generalized matching law and team success on offense and season winning percentage. These results illustrate the broad applicability of the generalized matching law to problems outside of the laboratory.