Samuel F Acuff1, Michael Amlung2, Ashley A Dennhardt1, James MacKillop2, James G Murphy1. 1. Department of Psychology, The University of Memphis, Memphis, TN, USA. 2. Peter Boris Centre for Addictions Research, Department of Psychiatry and Behavioural Neurosciences, McMaster University/St Joseph's Healthcare Hamilton, Hamilton, ON, Canada.
Abstract
BACKGROUND AND AIMS: Reinforcing value, an index of motivation for a drug, is commonly measured using behavioral economic purchase tasks. State-oriented purchase tasks are sensitive to phasic manipulations, but with heterogeneous methods and findings. The aim of this meta-analysis was to characterize the literature examining manipulations of reinforcing value, as measured by purchase tasks and multiple-choice procedures, to inform etiological models and treatment approaches METHODS: A random-effects meta-analysis of published findings in peer-reviewed articles. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol, studies were gathered through searches in PsycINFO and PubMed/MEDLINE (published 22 May 2018). Searches returned 34 unique studies (aggregate sample n = 2402; average sample size = 68.94) yielding 126 effect sizes. Measurements included change (i.e. Cohen's d) in six behavioral economic indices (intensity, breakpoint, Omax , Pmax , elasticity, cross-over point) in relation to six experimental manipulations (cue exposure, stress/negative affect, reinforcer magnitude, pharmacotherapy, behavioral interventions, opportunity cost). RESULTS: Cue exposure (d range = 0.25-0.44, all Ps < 0.05) and reinforcer magnitude [d = 0.60; 95% confidence interval (CI) = 0.18, 1.01; P < 0.005] manipulations resulted in significant increases in behavioral economic demand across studies. Stress/negative affect manipulations also resulted in a small, significant increase in Omax (d = 0.18; 95% CI = 0.01, 0.34; P = 0.03); all other effect sizes for negative affect/stress were non-significant, albeit similar in size (d range = 0.14-0.18). In contrast, pharmacotherapy (d range = -0.37 to -0.49; Ps < 0.04), behavioral intervention (d = -0.36 to -1.13) and external contingency (d = -1.42; CI = -2.30, -0.54; P = 0.002) manipulations resulted in a significant decrease in intensity. Moderators (substance type) explained some of the heterogeneity in findings across meta-analyses. CONCLUSIONS: In behavioral economic studies, purchase tasks and multiple-choice procedures appear to provide indices that are sensitive to manipulations found to influence motivation to consume addictive substances in field experiments.
BACKGROUND AND AIMS: Reinforcing value, an index of motivation for a drug, is commonly measured using behavioral economic purchase tasks. State-oriented purchase tasks are sensitive to phasic manipulations, but with heterogeneous methods and findings. The aim of this meta-analysis was to characterize the literature examining manipulations of reinforcing value, as measured by purchase tasks and multiple-choice procedures, to inform etiological models and treatment approaches METHODS: A random-effects meta-analysis of published findings in peer-reviewed articles. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol, studies were gathered through searches in PsycINFO and PubMed/MEDLINE (published 22 May 2018). Searches returned 34 unique studies (aggregate sample n = 2402; average sample size = 68.94) yielding 126 effect sizes. Measurements included change (i.e. Cohen's d) in six behavioral economic indices (intensity, breakpoint, Omax , Pmax , elasticity, cross-over point) in relation to six experimental manipulations (cue exposure, stress/negative affect, reinforcer magnitude, pharmacotherapy, behavioral interventions, opportunity cost). RESULTS: Cue exposure (d range = 0.25-0.44, all Ps < 0.05) and reinforcer magnitude [d = 0.60; 95% confidence interval (CI) = 0.18, 1.01; P < 0.005] manipulations resulted in significant increases in behavioral economic demand across studies. Stress/negative affect manipulations also resulted in a small, significant increase in Omax (d = 0.18; 95% CI = 0.01, 0.34; P = 0.03); all other effect sizes for negative affect/stress were non-significant, albeit similar in size (d range = 0.14-0.18). In contrast, pharmacotherapy (d range = -0.37 to -0.49; Ps < 0.04), behavioral intervention (d = -0.36 to -1.13) and external contingency (d = -1.42; CI = -2.30, -0.54; P = 0.002) manipulations resulted in a significant decrease in intensity. Moderators (substance type) explained some of the heterogeneity in findings across meta-analyses. CONCLUSIONS: In behavioral economic studies, purchase tasks and multiple-choice procedures appear to provide indices that are sensitive to manipulations found to influence motivation to consume addictive substances in field experiments.
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