Understanding alcohol motivation using the alcohol purchase task: A methodological systematic review

Experimental manipulations of behavioral economic demand for addictive commodities: a meta-analysis

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, O_max , P_max , 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 O_max (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.

Utilizing the commodity purchase task to evaluate behavioral economic demand for illicit substances: a review and meta-analysis

BACKGROUND ANDAIMS

The commodity purchase task is a simulated demand procedure that is easy and quick to complete (< 5 minutes) as well as adaptable for remote delivery and use with varied study populations. The purpose of this meta-analysis was to synthesize research using the commodity purchase task with illicit substances to evaluate the magnitude of omnibus effects sizes and moderators of the correlation of demand indices with quantity-frequency (QF) and severity measures.

DESIGN

Random-effects meta-analyses and meta-regressions involving studies with cross-sectional correlational designs.

SETTING AND PARTICIPANTS

Eleven studies, 10 outcomes and 2146 participants from two countries (USA and UK) published up to 1 October 2018.

MEASUREMENTS

Omnibus effect sizes (correlation coefficients) of five demand indices from the commodity purchase task [intensity (unconstrained consumption), elasticity (price sensitivity), O_max (maximum expenditure), P_max (price at maximum expenditure) and breakpoint (first price of zero consumption)] with QF and severity measures. Meta-regression models tested moderators of effect sizes (i.e. sample age and sex composition, commodity type and number of prices used in the commodity purchase task).

FINDINGS

Significant omnibus effect sizes were observed with QF and severity measures for intensity (r = 0.32/0.28, QF/severity, respectively), elasticity (r = -0.14/-0.18), O_max (r = 0.30/0.29) and breakpoint (r = 0.17/0.22) values. P_max was only significantly associated with severity measures (r = 0.15). The percentage of female participants and number of prices used in the purchase task significantly moderated P_max and breakpoint effect-size estimates in that stronger associations were observed in samples with a greater percentage of women and in studies using tasks with more price points. Commodity type (cannabis versus cocaine) did not significantly moderate associations involving any demand index.

CONCLUSIONS

Behavioral economic demand as measured by the commodity purchase task is consistently correlated with measures of illicit substance use quantity-frequency and severity.

Alcohol demand assessed daily: Validity, variability, and the influence of drinking-related consequences

BACKGROUND

Alcohol demand, typically assessed at the trait-level, via single administration, reflects individualized alcohol value. We examined correspondence between baseline trait-level and daily brief measures of alcohol demand, and whether demand changes day-to-day in response to recent drinking-related consequences. Understanding whether consequences influence demand fluctuations may provide insight into when demand can be reduced in the context of intervention.

METHODS

Heavy drinking college students (n = 95, age 18-20, 52% female) completed a baseline 14-item alcohol purchase task (APT). Observed demand indices were: intensity (consumption at zero cost), O_max (maximum expenditure), and breakpoint (cost whereby consumption is suppressed to zero). Participants subsequently completed 28 daily reports including a 3-item APT (one item corresponding to each baseline index) and prior day drinking and consequences.

RESULTS

Intraclass correlations revealed within-person variability (i.e., day-to-day change) across daily demand indices. In hierarchical linear models (HLM), each daily demand index was significantly predicted by its corresponding baseline full APT index, when all three baseline indices were entered, suggesting convergent validity of the daily measure. Lower day-level intensity was predicted by more prior day negative consequences, controlling for several day- and person-level variables in HLM. Recent positive consequences did not impact intensity, and daily O_max and breakpoint were not predicted by any tested day- or person-level variables.

CONCLUSIONS

APT indices collected daily map on well to traditional single-administration APT metrics and change in response to recent consequences. Intensity demonstrated the greatest within-person variability, the strongest association with its corresponding full APT index, and theoretically-consistent prediction by negative consequences of drinking.

The condom purchase task: A hypothetical demand method for evaluating sexual health decision-making

Behavioral economic theory has proved useful for understanding the influence of delay and probability on sexual health decision-making. Demand is another principle at the intersection of microeconomics and psychology that has helped advance research relevant to health behaviors. The purpose of the present study was to develop and test a demand measure related to sexual health decision-making and the influence of sexually transmitted infection (STI) risk. Participants (N = 438) recruited using Amazon Mechanical Turk completed a commodity purchase task assessing hypothetical condom demand. Condom demand was evaluated at varied prices for use with hypothetical sexual partners that varied in STI risk. Demand was characterized by prototypic decreases in consumption with increases in cost. Higher partner STI risk was associated with greater intentions for condom-protected sex at no cost and smaller decreases in condom demand with increases in cost. Price sensitivity was also related to individual difference factors relevant to sexual health (e.g., alcohol use severity, lower STI knowledge). This study supports the utility of a condom purchase task for indexing condom valuation and capturing individual difference and contextual risk factors relevant to STI transmission. Future studies may leverage this methodology as a means to study sexual health decision-making.

Assessing Cannabis Demand: A Comprehensive Review of the Marijuana Purchase Task

The marijuana purchase task (MPT) is a behavioral economic measure of individualized cannabis value (i.e., demand). The MPT follows purchase tasks for other substances (e.g., alcohol, tobacco), though presents with unique caveats due to its mixed illicit status, non-uniform units of purchase and use, and substantial within substance variability in strain, potency, and quality. As the regulatory climate surrounding purchase and use of cannabis continues to evolve in the USA and globally, rigorous assessment of cannabis use and value are of the utmost importance. This study represents the first comprehensive review of investigations utilizing the MPT. Searches through PubMed and Web of Science databases by two independent coders identified 15 empirical articles referencing the use of an MPT and were published through the year 2019. Articles were coded for demographic and procedural characteristics, structural characteristics of the MPT itself, data analytic characteristics, and relationships with cannabis-related outcomes. Rigorous assessment of demand for cannabis is essential with respect to the broad public health issues surrounding cannabis legalization. We have synthesized the research presented herein and comment on vital considerations for subsequent MPT work, including recommendations for a unified approach to using the MPT in subsequent research.

The influence of sex and estrous cyclicity on cocaine and remifentanil demand in rats

The application of behavioral economic demand theory in addiction science has proved useful for evaluating individual characteristics underlying abuse liability. Two factors that have received comparably little attention within this literature are sex and gonadal hormones. We determined cocaine and remifentanil demand in male and female rats using a within‐session procedure. Cocaine and remifentanil demand were evaluated for 15 consecutive days using a balanced, crossover design that randomized drug order. This design allowed for the evaluation of temporal and exposure effects on two independent dimensions of demand, unconstrained demand (Q₀) and demand elasticity (α). Estrous cyclicity was tracked to determine the contribution of phase to demand. No overall sex differences were observed. Increased unconstrained demand for cocaine and remifentanil was observed in females during periods in which estrogen was high (eg, estrus phase). Unconstrained remifentanil demand escalated over the 15‐day testing period, but escalation was not observed for cocaine or for demand elasticity. A significant exposure effect was also observed in which greater prior remifentanil intake increased unconstrained cocaine demand and reduced cocaine demand elasticity. These effects were directionally specific as no significant effects of prior cocaine exposure were observed on remifentanil demand measures. These data suggest that unconstrained demand and demand elasticity do not differ between male and female subjects; however, that unconstrained demand is associated with estrous cyclicity. These findings also suggest that opioid exposure enhances subsequent demand for psychomotor stimulants, which may be important when considering recent increases in nonmedical prescription opioid use in the United States.

Reinforcer Pathology: Implications for Substance Abuse Intervention

The rate at which individuals discount future rewards (i.e., discounting rate) is strongly associated with their propensity for substance abuse as well as myriad other negative health behaviors. An excessive preference for immediately available rewards suggests a shortened time horizon in which immediate rewards are overvalued and future, potentially negative consequences are undervalued. This review outlines Reinforcer Pathology Theory (i.e., the interaction between excessive preference for immediately available rewards and the overvaluation of a particular commodity that offers brief, intense reinforcement), its neurobiological/behavioral underpinnings, and its implications for treating substance use disorders. In doing so, the current review provides an overview of a variety of ways in which interventions have been used to manipulate aspects of reinforcer pathology in an individual, including narrative theory, framing manipulations, and neuromodulation (e.g., working memory training, TMS) which may serve as promising avenues for the modulation of the temporal window and/or valuation of reinforcers.

High Opportunity Cost Demand as an Indicator of Weekday Drinking and Distinctly Severe Alcohol Problems: A Behavioral Economic Analysis

INTRODUCTION

Behavioral economic theory views addiction as a reinforcer pathology characterized by excessive demand for drugs relative to alternatives. Complementary to this theory, Lamb and Ginsburg (Pharmacology Biochemistry and Behavior, 164, 2018, 62) describe addiction as a behavioral allocation disorder and predict that decisions to drink under increasingly stringent constraints are a central indicator of addiction. This study used a modified demand-curve paradigm to examine alcohol demand in the context of a next-day contingency (high opportunity cost demand) as a specific indicator of a severe pattern of alcohol problems.

METHODS

Participants were 370 undergraduates (61.1% female, 86.5% white, Mage  = 18.8) reporting multiple past-month heavy drinking episodes (5/4 drinks per occasion for men/women) who completed 2 versions of an alcohol purchase task (APT), along with measures of past-month alcohol use and problems. In 1 APT (low opportunity cost), students imagined they had no next-day responsibilities, and in the other APT (high opportunity cost), they imagined having a 10:00 am test the next day. Item-response theory analyses were used to determine mild and severe alcohol problems from the Young Adult Alcohol Consequences Questionnaire (Journal of Studies on Alcohol, 67, 2006, 169), and the most and least severe binge drinking days throughout the week.

RESULTS

Low opportunity cost demand (β = 0.15, p = 0.02) significantly predicted beyond high opportunity cost demand for the least severe problems, and high opportunity cost demand (β = 0.17, p = 0.009) significantly predicted beyond low opportunity cost demand for the most severe problems. Similarly, low opportunity cost demand (β = 0.26, p < 0.001) was more highly associated with weekend drinking, whereas high opportunity cost demand (β = 0.21, p = 0.001) was more highly associated with weekday drinking.

CONCLUSIONS

The current results suggest high opportunity cost alcohol demand is a distinct marker of severe alcohol problems among college student heavy drinkers.

Behavioral economic demand assessments in the addictions

Behavioral economics in the addictions is the application of both economics and psychology to study multifaceted components of substance use decision-making behavior. One such component is demand: the relative value of a substance for a user (i.e., the association between drug use and cost). The degree to which a user values a substance can be measured via performance on hypothetical purchase tasks which replicate drug purchase and consumption. Demand has been evaluated across substances, including alcohol, marijuana, tobacco, and alternative tobacco products. Recent advances in the study of demand have greatly improved the assessment of drug value, including application to novel products, selection of optimal task unit, assessment of demand in naïve or potential future users, and the importance of instructional set specificity.

Sensitivity of hypothetical purchase task indices when studying substance use: A systematic literature review

Hypothetical Purchase Tasks (HPTs) simulate demand for a substance as a function of escalating price. HPTs are increasingly used to examine relationships between substance-related correlates and outcomes and demand typically characterized using a common battery of indices (Intensity, Omax, Pmax, Breakpoint, Elasticity). This review examines the relative sensitivity of the HPT indices. Reports were identified using the search term "purchase task" in PubMed and Web of Science. For inclusion, reports had to be original studies in English, examine relationships between HPT indices and substance-related correlates or outcomes, and appear in a peer-reviewed journal through December 2017. Indices were compared using effect sizes (Cohen's d) and the proportion of studies in which statistically significant relationships were observed. The search identified 1274 reports with 114 (9%) receiving full-text review and 82 (6%) meeting inclusion criteria. 41 reports examined alcohol, 34 examined cigarettes/nicotine products, and 10 examined other substances. Overall, statistically significant relationships between HPT indices and substance-related correlates and outcomes were most often reported for Intensity (88.61%, 70/79), followed by Omax (81.16%, 56/69), Elasticity (72.15%, 57/59), Breakpoint (62.12%, 41/66), and Pmax (48.08%; 25/52). The largest effect sizes were observed for Intensity (0.75 ± 0.04, CI 0.67-0.84) and Omax (0.64 ± 0.04, CI 0.56-0.71), followed by Elasticity (0.44 ± 0.04, CI 0.37-0.51), Breakpoint (0.30 ± 0.03, CI 0.25-0.36), and Pmax (0.25 ± 0.04, CI 0.18-0.33). Patterns were largely consistent across substances. In conclusion, HPTs can be highly effective in revealing relationships between demand and substance-related correlates and outcomes, with Intensity and Omax exhibiting the greatest sensitivity.

Evaluating non-medical prescription opioid demand using commodity purchase tasks: test-retest reliability and incremental validity

RATIONALE

Non-medical prescription opioid use and opioid use disorder (OUD) present a significant public health concern. Identifying behavioral mechanisms underlying OUD will assist in developing improved prevention and intervention approaches. Behavioral economic demand has been extensively evaluated as a measure of reinforcer valuation for alcohol and cigarettes, whereas prescription opioids have received comparatively little attention.

OBJECTIVES

Utilize a purchase task procedure to measure the incremental validity and test-retest reliability of opioid demand.

METHODS

Individuals reporting past year non-medical prescription opioid use were recruited using the crowdsourcing platform Amazon Mechanical Turk (mTurk). Participants completed an opioid purchase task as well as measures of cannabis demand, delay discounting, and self-reported pain. A 1-month follow-up was used to evaluate test-retest reliability.

RESULTS

More intense and inelastic opioid demand was associated with OUD and more intense cannabis demand was associated with cannabis use disorder. Multivariable models indicated that higher opioid intensity and steeper opioid delay discounting rates each significantly and uniquely predicted OUD. Increased opioid demand intensity, but not elasticity, was associated with higher self-reported pain, and no relationship was observed with perceived pain relief from opioids. Opioid demand showed acceptable-to-good test-retest reliability (e.g., intensity rxx = .75; elasticity rxx = .63). Temporal reliability was lower for cannabis demand (e.g., intensity rxx = .53; elasticity rxx = .58) and discounting rates (rxx = .42-.61).

CONCLUSIONS

Opioid demand was incrementally valid and test-retest reliable as measured by purchase tasks. These findings support behavioral economic demand as a clinically useful measure of drug valuation that is sensitive to individual difference variables.

Using behavioral economic variables to predict future alcohol use in a crowdsourced sample

BACKGROUND

Theoretical perspectives at the intersection of behavioral economics and operant theory have resulted in numerous advances for addiction science. Three mechanisms (i.e. behavioral economic demand [consumption-price relationships], delay discounting [reinforcer devaluation with delay], and proportionate alcohol-related reinforcement [relative reinforcement attributable to alcohol]) are proposed to contribute to problematic alcohol use. Limited research has evaluated the unique contribution of these mechanisms for predicting future alcohol consumption.

AIM

The purpose of this study was to evaluate the predictive relationship between these mechanisms and self-reported alcohol use frequency, quantity, and severity.

METHODS

Participants (n=223) sampled from the crowdsourcing website Amazon Mechanical Turk completed a survey containing behavioral economic measures. Weekly reports of daily alcohol use were then collected for 18 weeks. Unadjusted and adjusted models determined the association between behavioral economic variables and alcohol use.

RESULTS/OUTCOMES

Behavioral economic measures were associated with alcohol and soda use at baseline in a stimulus-selective manner (e.g. alcohol demand associated with alcohol, but not soda, variables). Predictive models adjusted for Alcohol Use Disorder Identification Test scores indicated that increased proportionate alcohol-related reinforcement and behavioral economic demand were uniquely and incrementally associated with frequency (e.g. adjusted odds ratio (AOR)=5.54 for proportionate alcohol-related reinforcement, p<0.05) and quantity-severity measures (e.g. AOR=7.58 for alcohol demand intensity, p<0.001), respectively. Test-retest reliability was generally acceptable (r_xx=0.42-0.76) with the exception of proportionate alcohol-related reinforcement (r_xx=0.29).

CONCLUSION/INTERPRETATION

These findings indicate the unique, predictive, and incremental validity of behavioral economic measures for evaluating future alcohol consumption, supporting their continued use in addiction science research.

The R package beezdemand: Behavioral Economic Easy Demand

beezdemand: Behavioral Economic Easy Demand, a novel package for performing behavioral economic analyses, is introduced and evaluated. beezdemand extends the statistical program to facilitate many of the analyses performed in studies of behavioral economic demand. The package supports commonly used options for modeling operant demand and performs data screening, fits models of demand, and calculates numerous measures relevant to applied behavioral economists. The free and open source beezdemand package is compared to commercially available software (i.e., GraphPad Prism™) using peer-reviewed and simulated data. The results of this study indicated that beezdemand provides results consistent with commonly used commercial software but provides a wider range of methods and functionality desirable to behavioral economic researchers. A brief overview of the package is presented, its functionality is demonstrated, and considerations for its use are discussed.

The Demand Curve Analyzer: Behavioral economic software for applied research

Free and open-source software for applying models of operant demand called the Demand Curve Analyzer (DCA) was developed and systematically evaluated for use in research. The software was constructed to streamline the use of recommended screening measures, prepare suitable scaling parameters, fit one of several models of operant demand, and provide publication-quality figures. The DCA allows users to easily import price and consumption data into spreadsheet-based controls and to perform statistical modeling with the aid of a graphical user interface. The results from computer simulations and reanalyses of published study data indicated that the DCA provides results consistent with commercially available software that has been traditionally used to apply these analyses (i.e., GraphPadTM Prism). Further, the DCA provides additional functionality that other statistical packages do not include. Practical issues and future directions related to the determination of scaling parameter k, screening for nonsystematic data, and the incorporation of more advanced behavioral economic methods are also discussed.