Comparing exponential and exponentiated models of drug demand in cocaine users

Exponentiated model of drug demand is preferred over exponential models in people with daily/near daily cannabis use

Cannabis use is a growing health concern emphasizing the need to better understand the complexities of drug choice in people with daily/near daily cannabis use. Hypothetical purchasing tasks provide a means to collect data on drug consumption behavior without requiring drug administration and have been used to isolate behavioral economic factors of choice, including facets of drug demand in substance using populations. Various models are used for analyzing hypothetical purchasing task data, but challenges exist in modeling data sets with consumption values of zero. Additionally, a single model or approach may not be best for all commodities and drug classes. This study compared two common demand models (exponential vs. exponentiated) applied to identical hypothetical purchasing task data from 21 (n = 21) individuals with daily/near daily cannabis use. The exponential model was fit using three common levels of replacement values for zero consumption (.1, .01, .001) and compared to the exponentiated model without replacement values. We found that the exponentiated model produced significantly better model fits for individual data, compared to all exponential models. Additionally, significant differences for model derived values of demand elasticity and intensity were found between the exponentiated model and different levels of the exponential model. We conclude that the exponentiated model is preferred over the exponential model for performing demand analysis on hypothetical purchasing task data from individuals with daily/near daily cannabis use. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A Different Scintigraphic Perspective on the Systolic Function of the Left Ventricle-1

Objectives

The aim of this study was to analyze the systolic part of the left ventricular (LV) volume curve obtained by gated myocardial perfusion imaging with the formula used in exponential decay and to investigate the clinical value of the results.

Methods

One hundred fifty eight patients were retrospectively enrolled in the study. The study group was divided into three groups as normal, ischemia, and infarct. The systolic portion of the LV volume curve was also analyzed using the exponential decay formula. The scintigraphic parameter obtained using this formula is called the ejection constant (Ec).

Results

The Ec results were 1.8±0.8, 2.7±0.9, 3.5±1 in infarct, ischemia, and normal groups, respectively, and the difference in Ec results between the groups was statistically significant (p≤0.001).

Conclusion

It appears that Ec may play a clinical role as a scintigraphic parameter in the evaluation of systolic functions of the left ventricle.

Assessing cocaine motivational value: Comparison of brain reactivity bias toward cocaine cues and cocaine demand

The behavioral economic measure drug demand and the neural measure late positive potential (LPP) are two measures of motivational value that have been associated with drug relapse risk and treatment outcomes. Despite having overlapping themes, no studies have directly compared drug demand and LPP. Participants (N = 59) included treatment-seeking individuals with cocaine use disorder that had completed both a baseline cocaine demand task and an electroencephalogram (EEG) picture-viewing task of drug-related and pleasant picture cues. Associations between the LPP difference score amplitude (drug-pleasant) and five demand indices (Q₀, essential value [EV], Omax, Pmax, and breakpoint [BP]) were evaluated via Bayesian generalized linear modeling. Positive associations (posterior probabilities ≥ 75%) were found between LPP amplitude and four demand indices (Q₀, EV, Omax, BP). These results suggest that individuals who attach greater relevance to cocaine cues also exhibit greater valuation of cocaine reward. Implications for incorporating methodology from behavioral science and brain imaging are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Behavioral economic relationship between cannabis flower and concentrates: Evidence from simulated purchase tasks

Cannabis users use different forms of cannabis, which are associated with distinct public health concerns. Policies that aim to regulate one specific form may have unintended impacts on other forms. This study examined the behavioral economic relationship between flower and concentrates, the two most common forms of cannabis. We surveyed 605 adult cannabis users (21+) who lived in one of the U.S. states that had legalized recreational cannabis by the time of interview in 2019. The participants completed simulated purchase tasks, which asked how much cannabis flower and concentrates they would purchase in the next 30 days at escalating prices. We estimated (a) demand indices and own-price elasticities using nonlinear exponential demand models and (b) group- and individual-level cross-price elasticities using log-linear demand models. The estimated rate of change in demand elasticity (α) was 0.00066 for cannabis flower (SE = 0.00002, p < .001) and 0.00058 for cannabis concentrate (SE = 0.00002, p < .001). Group-level cross-price elasticity estimate (slope = -0.075, SE = 0.0135, p < .001) indicated that cannabis flower and concentrates were weak complements. Individual-level cross-price elasticity estimates showed that flower and concentrates were treated as independent by 76.2% of the users, as complements by 19.0% of the users, and as substitutes by 4.8% of the users. The findings suggested that cannabis flower and concentrates were overall weak complements and for most adult cannabis users were treated as independent of each other. Price and tax policies regulating either cannabis form may have minimal impacts on the other form. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Behavioral economic relationship between cannabis and cigarettes: Evidence from hypothetical purchase tasks

BACKGROUND

In the United States (U.S), cannabis policies have been increasingly liberalized whereas tobacco policies have been increasingly stringent. Given the high prevalence of cannabis and tobacco dual use, there are concerns that a policy regulating one substance may unintendedly influence the other. This study examined the responsiveness of the demand for cannabis joints and cigarettes when price varied.

METHODS

The study included 338 adult participants (21+) who used both cannabis and tobacco and lived in one of the U.S. states with recreational cannabis legalized by the time of interview in 2019. They completed hypothetical purchase tasks to indicate the quantity desired of cannabis joints and cigarette packs 1) when only one substance was available with escalating prices and 2) when both substances were concurrently available with escalating prices of cannabis joints and a fixed price of cigarette packs. We estimated 1) the own-price elasticity of demand for each substance using nonlinear exponential demand model, and 2) the cross-price elasticity of demand at aggregate level using nonlinear exponential demand model and at individual level using log-linear demand model.

RESULTS

The estimates for the rate of change of own-price elasticity (α) were 0.0011 (SE = 0.000039, p < 0.001) for cannabis joints and 0.00095 (SE = 0.000037, p < 0.001) for cigarette packs. The aggregate-level estimates of cross-price elasticity (I = 13.032, SE = 0.34, p < 0.001; β = 0.0029, SE = 0.0021, p > 0.05) suggest an independent relationship between the two substances. At individual level, 78.70% of the participants treated the two substances as independent, 17.46% as complements, and 3.85% as substitutes.

CONCLUSIONS

For most adults who used both cannabis and tobacco in the U.S., cannabis joints and cigarettes had an independent relationship. Policies regulating the price of cannabis may not have large unintended consequences on cigarette use.

(Non-) impact of task experience on behavioral economic decision-making

Behavioral economic research has been widely conducted via crowdsourcing resources to evaluate novel task designs or pilot interventions. One under recognized and yet-to-be tested concern is the impact of non-naïvety (i.e., prior task exposure) on behavioral economic task performance. We evaluated the influence of non-naïvety on task performance in two popular areas of behavioral economic research: behavioral economic demand and delay discounting. Participants (N = 485) recruited using Amazon Mechanical Turk (mTurk) completed alcohol and soda purchase tasks and delay discounting tasks for monetary and alcohol outcomes. Equivalence of responding and effect sizes with clinical variables were compared based on prior task experience. Over one quarter of participants reported demand task experience (26.9%) and nearly half endorsed delay discounting task experience (48.6%). Statistically equivalent responding was observed for alcohol purchase task data with less-than-small effect size differences based on task experience (d = 0.01-0.13). Similar results were observed for a soda purchase task thereby supporting generalization to a non-alcohol commodity. Measures of convergent and discriminant validity for behavioral economic demand indicated medium-to-large and stimulus-specific effect sizes with little variation based on prior task exposure. Delay discounting for money and alcohol showed some sensitivity to prior task experience (i.e., less steep discounting for non-naïve participants), however these effects were attenuated after accounting for group differences in alcohol use. These findings support the fidelity of behavioral economic task outcomes and emphasize that participant non-naïvety in crowdsourcing settings may minimally impact performance on behavioral economic assays commonly used in behavioral and addiction science. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Behavioral economic demand modeling chronology, complexities, and considerations: Much ado about zeros

Behavioral economic demand has been shown to have high utility in quantifying the value or consumption of a commodity. Demand describes the relationship between cost and consumption of a commodity, and tends to be curvilinear with consumption approaching zero as the cost increases to a sufficiently high cost to suppress consumption completely. Over a period spanning greater than three decades, behavioral economists have made great strides in the modeling of demand and addressing analytical challenges, although this work is not complete and unresolved challenges remain. The analytical challenges associated with modeling zeros both when they arise as consumption values of zero and when consumption at zero cost is assessed have been a substantial part of this evolution in models. The goals of this methodological review are to provide a historical overview of the major behavioral economic demand models that have been proposed, describe some of the common difficulties with analyzing behavioral economic demand, and discuss general considerations for the analysis of demand. In an environment with evolving and multiple competing analytical practices, we conclude that researchers can maximize scientific rigor by embracing transparency in their analysis choices and employing techniques such as sensitivity analyses to determine if their analysis choices impact the conclusions of their experiments.

Demand for Factory-Made Cigarettes and Roll-Your-Own Tobacco and Differences Between Age and Socioeconomic Groups: Findings From the International Tobacco Control Netherlands Survey

INTRODUCTION

Macroeconomic studies have shown that young individuals who smoke, and have a low socioeconomic status respond more strongly to price increases. Most of this evidence stems from research on factory-made (FM) cigarettes. With the rising popularity of roll-your-own (RYO) tobacco, there is a need for studies on cigarette demand that distinguish between both.

AIMS AND METHODS

This study examined whether individual demand differed for FM and RYO tobacco, and across age, and socioeconomic (income and education) groups. Purchase tasks for FM and RYO cigarettes were included in the 2020 International Tobacco Control (ITC) Netherlands Survey. Adults who smoke daily (n = 1620) stated how many cigarettes they would smoke in 24 hours across eight prices. Four demand indices were derived: intensity (consumption at zero costs), alpha (rate of change in elasticity), Pmax (turning point elasticity), and breakpoint (lowest price where consumption equals zero). The indices were tested for subgroup differences.

RESULTS

Individuals who smoke RYO tobacco indicated higher intensity, and greater alpha than individuals who smoke FM cigarettes. Participants aged 25-39 had lower Pmax, and 18-24 year olds displayed higher breakpoints. Participants with low income displayed higher intensity, and lower Pmax than other income groups. No associations were found with education.

CONCLUSIONS

Individuals who smoke RYO tobacco indicated higher price sensitivity than those smoking FM cigarettes, supporting the need to harmonize tobacco taxation. Taxation may be especially beneficial to reducing consumption among individuals with a low income or smoke RYO tobacco. Substantially higher prices are needed in the Netherlands to achieve the desired results.

IMPLICATIONS

Individuals who smoke daily were willing to pay substantially higher prices than the current market prices, indicating the room and need for much higher taxation levels. Demand for RYO tobacco was more sensitive to price changes than demand for FM cigarettes. Taxation should be raised at equivalent rates for FM and RYO cigarettes. Taxation appears to be especially effective in reducing consumption among people who smoke RYO tobacco and low-income individuals. It remains important to combine increased taxation with other tobacco control measures.

Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics

Rapid advancements in high-throughput omics technologies and experimental protocols have led to the generation of vast amounts of scale-specific biomolecular data on cancer that now populates several online databases and resources. Cancer systems biology models built using this data have the potential to provide specific insights into complex multifactorial aberrations underpinning tumor initiation, development, and metastasis. Furthermore, the annotation of these single- and multi-scale models with patient data can additionally assist in designing personalized therapeutic interventions as well as aid in clinical decision-making. Here, we have systematically reviewed the emergence and evolution of (i) repositories with scale-specific and multi-scale biomolecular cancer data, (ii) systems biology models developed using this data, (iii) associated simulation software for the development of personalized cancer therapeutics, and (iv) translational attempts to pipeline multi-scale panomics data for data-driven in silico clinical oncology. The review concludes that the absence of a generic, zero-code, panomics-based multi-scale modeling pipeline and associated software framework, impedes the development and seamless deployment of personalized in silico multi-scale models in clinical settings.

Applying Mixed-Effects Modeling to Behavioral Economic Demand: An Introduction

Behavioral economic demand methodology is increasingly being used in various fields such as substance use and consumer behavior analysis. Traditional analytical techniques to fitting demand data have proven useful yet some of these approaches require preprocessing of data, ignore dependence in the data, and present statistical limitations. We term these approaches "fit to group" and "two stage" with the former interested in group or population level estimates and the latter interested in individual subject estimates. As an extension to these regression techniques, mixed-effect (or multilevel) modeling can serve as an improvement over these traditional methods. Notable benefits include providing simultaneous group (i.e., population) level estimates (with more accurate standard errors) and individual level predictions while accommodating the inclusion of "nonsystematic" response sets and covariates. These models can also accommodate complex experimental designs including repeated measures. The goal of this article is to introduce and provide a high-level overview of mixed-effects modeling techniques applied to behavioral economic demand data. We compare and contrast results from traditional techniques to that of the mixed-effects models across two datasets differing in species and experimental design. We discuss the relative benefits and drawbacks of these approaches and provide access to statistical code and data to support the analytical replicability of the comparisons.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40614-021-00299-7.

Decreased cocaine demand following contingency management treatment

A hypothetical cocaine purchasing task (CocPT) was used to assess changes in cocaine demand in the context of contingency management (CM) treatment for cocaine use disorder (CUD). Participants (N = 89) were treatment-seeking individuals with CUD receiving 4 weeks of abstinence-based, high-magnitude CM. Treatment response (vs. non-response) was operationally defined as the submission of 6 consecutive cocaine-negative urine samples across two weeks. The CPT was assessed at baseline, week 2, and week 5. Demand data were well described by the exponentiated demand model, and baseline demand indices (Q0, Pmax, breakpoint, essential value) were significantly associated with self-report measures of cocaine use. The probability of being a zero-responder reporting zero cocaine consumption at all prices significantly increased over the course of treatment, and was greater among treatment responders vs. non-responders. Among non-zero demand data, decreases in Omax, Pmax, breakpoint, and essential value were observed over the course of CM treatment, favoring responders. To our knowledge, this is the first study to assess change in cocaine demand in the context of CM treatment targeting cocaine abstinence. Our results support the utility of cocaine demand as a measure for both identifying individuals with greater treatment need and tracking relapse risk over the course of treatment.

Assessment of demand for methamphetamine and cigarettes among individuals with methamphetamine use disorder

Methamphetamine (MA) is a highly addictive stimulant with recent upward trends in prevalence and associated public health problems. Drug demand, as assessed by hypothetical purchasing tasks, has been useful in addictions research and may help our understanding of the factors influencing MA use. However, no studies have assessed MA demand using current models of demand. The purpose of the current study was to assess demand for MA using a hypothetical drug purchasing task. Given high rates of cigarette smoking among MA users, it was of interest also to assess and compare demand for MA relative to cigarettes. Participants consisted of non-treatment-seeking volunteers with MA use disorder (N = 18), of whom 17 reported daily smoking. Results showed the exponentiated demand model provided a good fit to consumption data. Results from Bayesian generalized linear modeling demonstrated multiple positive relationships (posterior probability ≥75%) between self-reported drug use (days MA used in the past 30 days, cigarettes smoked per day) and indices of demand for each drug (Qo, Omax, Pmax, and break point). Comparing MA to cigarettes, results from Bayesian generalized linear mixed modeling revealed greater abuse liability for MA compared to cigarettes (posterior probability ≥99%) based on α and essential value. Overall, the findings of the current study support the feasibility and validity of the exponentiated demand model for assessing demand for drugs among individuals with MA use disorder. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Initial development of a brief assessment of cocaine demand

Cocaine demand is a behavioral economic measure assessing drug reward value and motivation to use drug. The purpose of the current study was to develop a brief assessment of cocaine demand (BACD). Results from the BACD were compared with self-report measures of cocaine use. Participants consisted of treatment-seeking individuals with cocaine use disorder (N = 22). Results revealed that indices of brief demand were significantly associated with various self-report measures of cocaine use. Overall, these results support the utility of a BACD for assessing cocaine demand.

E-Cigarette Demand: Impact of Commodity Definitions and Test-Retest Reliability

INTRODUCTION

Behavioral economic demand provides a multidimensional understanding of reinforcement. Commodity purchase tasks are an efficient method for measuring demand in human participants. One challenge in translating these procedures to electronic nicotine delivery systems (ENDS or e-cigarettes) is defining commodity units given the lack of standardization in the e-cigarette marketplace.

AIMS AND METHODS

The purpose of this study was to directly compare methods of operationalizinge-cigarette purchases, puffs, cartridges, and mLs liquid, using a within-subject design. Participants (N = 132) reporting past week e-cigarette use were recruited using crowdsourcing. Purchase tasks were completed operationalizing e-cigarette units as puffs or cartridges at baseline and puffs or mLs liquid at a 3-month follow-up.

RESULTS

Bivariate associations supported convergent and discriminant validity with the largest effect size correlations for intensity and elasticity observed for the puff version. Interaction models suggested that product preferences moderated the relationship between time-to-first use and cartridge demand with larger effect size correlations among persons reporting a preference for JUULs, but weaker relationships among persons reporting other device preferences. Puff intensity (rxx = .61) and elasticity (rxx = .62) showed good test-retest reliability for participants reporting stable consumption, but poor test-retest reliability for individuals with changed consumption levels (intensity rxx = -.08; elasticity rxx = -.10).

CONCLUSIONS

This study highlights the relevance of commodity definitions in the e-cigarette purchase task. Puffs as an experimental commodity may provide flexibility for studying e-cigarette demand in heterogenous or unknown populations, whereas more tailored or personalized approaches like cartridge or mL-based tasks will likely be helpful when studying known subgroups.

IMPLICATIONS

The commodity purchase task procedure is widely used for understanding cigarette and e-cigarette demand in nicotine dependence research. This study evaluates the importance of operational definitions of e-cigarette commodities in the purchase task (ie, puffs, cartridges, or mLs liquid). Puffs may provide a more flexible commodity unit when evaluating e-cigarette demand in general or heterogenous populations, whereas device-specific units may prove more valuable when studying populations with consistent and known product use.

Purchase task sensitivity to drug and nondrug reinforcers in opioid-agonist treatment patients

The behavioral economics of substance abuse has been increasingly recognized as a method of determining the value of abused substances for individuals who use those substances. It has been hypothesized that such analyses could serve as a clinical tool and that demand functions can be targeted predictors for the level of intervention necessary. This study evaluated the sensitivity of a demand task in 2 patient groups in a medication assisted treatment program (methadone maintenance), those who had used opioids in the last 2 months and those who had not used opioids in at least 18 months. Demand for 7 drugs and a control was assessed using hypothetical purchase tasks. Participants maintaining long-term abstinence had significantly higher α (sensitivity to price) and lower Q₀ (intensity of demand) for heroin than participants who had recently used opioids. Further research is necessary to illustrate if treatment is responsible for this reduction in demand. If so, demand analyses may provide clinical utility as an aid for treatment planning or as a target for treatment.

A zero-bounded model of operant demand

Contemporary approaches for evaluating the demand for reinforcers use either the Exponential or the Exponentiated model of operant demand, both derived from the framework of Hursh and Silberberg (2008). This report summarizes the strengths and complications of this framework and proposes a novel implementation. This novel implementation incorporates earlier strengths and resolves existing shortcomings that are due to the use of a logarithmic scale for consumption. The Inverse Hyperbolic Sine (IHS) transformation is reviewed and evaluated as a replacement for the logarithmic scale in models of operant demand. Modeling consumption in the "log₁₀ -like" IHS scale reflects relative changes in consumption (as with a log scale) and accommodates a true zero bound (i.e., zero consumption values). The presence of a zero bound obviates the need for a separate span parameter (i.e., k) and the span of the model may be more simply defined by maximum demand at zero price (i.e., Q₀ ). Further, this reformulated model serves to decouple the exponential rate constant (i.e., α) from variations in span, thus normalizing the rate constant to the span of consumption in IHS units and permitting comparisons when spans vary. This model, called the Zero-bounded Exponential (ZBE), is evaluated using simulated and real-world data. The direct reinstatement ZBE model showed strong correspondence with empirical indicators of demand and with a normalization of α (ZBEn) across empirical data that varied in reinforcing efficacy (dose, time to onset of peak effects). Future directions in demand curve analysis are discussed with recommendations for additional replication and exploration of scales beyond the logarithm when accommodating zero consumption data.

Behavioral Economic Assessment of Alcohol and Cigarette Demand in Smokers With Alcohol Use Disorder

Background and Objectives: Behavioral economic purchase tasks are widely used to assess drug demand in substance use disorder research. Comorbid alcohol use is common among cigarette smokers and associated with greater difficulty in quitting smoking. However, demand for alcohol and cigarettes in this population has not been fully characterized. The present study addressed this gap by examining alcohol and cigarette demand among treatment-seeking smokers with alcohol use disorder (AUD). Methods: Alcohol and cigarette demand was assessed among 99 smokers with AUD. We conducted Principal Component Analysis (PCA) and correlational analyses on the demand indices. Results: Participants showed higher demand for alcohol than for cigarettes, as evidenced lower elasticity (resistance to increasing price) and higher O_max (maximum response output for drug). PCA revealed a two-factor structure (Persistence and Amplitude) for both alcohol and cigarette demand indices. Cigarette-related demand indices were positively correlated with nicotine dependence, but alcohol-related demand indices were not associated with alcohol dependence, suggesting dissociation between alcohol demand and use behaviors. Discussion and Conclusions: Our results suggest that smokers with AUD were more resistant to price elevations in relation to reducing alcohol consumption as compared to cigarette consumption, suggesting preferential demand for alcohol over cigarettes. However, it is unclear how acute substance exposure/withdrawal impacts the demand indices. Scientific Significance: Potentially differential alcohol and cigarette demands among smokers with AUD should be considered in the concurrent treatment of smoking and alcohol.

Behavioral economic measurement of cigarette demand: A descriptive review of published approaches to the cigarette purchase task

The cigarette purchase task (CPT) is a behavioral economic method for assessing demand for cigarettes. Growing interest in behavioral correlates of tobacco use in clinical and general populations as well as empirical efforts to inform policy has seen an increase in published articles employing the CPT. Accordingly, an examination of the published methods and procedures for obtaining these behavioral economic metrics is timely. The purpose of this investigation was to provide a review of published approaches to using the CPT. We searched specific Boolean operators (["behavioral economic" AND "purchase task"] OR ["demand" AND "cigarette"]) and identified 49 empirical articles published through the year 2018 that reported administering a CPT. Articles were coded for participant characteristics (e.g., sample size, population type, age), CPT task structure (e.g., price framing, number and sequence of prices; vignettes, contextual factors), and data analytic approach (e.g., method of generating indices of cigarette demand). Results of this review indicate no standard approach to administering the CPT and underscore the need for replicability of these behavioral economic measures for the purpose of guiding clinical and policy decisions. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Behavioral economic demand as a unifying language for addiction science: Promoting collaboration and integration of animal and human models

The intersection of pharmacological, psychological, and economic theory within behavioral economics has helped advance an understanding of substance use disorder. A notable contribution of this approach is the conceptualization of reinforcement from a behavioral economic demand perspective. Demand analyses provide a multidimensional view of reinforcement in which distinct behavioral mechanisms are measured that impact decision making and drug consumption. This review describes the state of research on behavioral economic demand as a common language for addiction science researchers across varied model systems and stages of a translational continuum. We first provide an overview of the theoretical concepts and procedures used to evaluate demand in animal and human models. The potential for demand to serve as a common language for diverse research groups in psychopharmacology and addiction science (e.g., those evaluating neurobehavioral outcomes, medications development, clinical practice) is then described. An overview is also provided of existing empirical studies that, while small in number, suggest good linguistic and conceptual overlap between animal and human demand models when studying biological, environmental, and pharmacological individual difference vulnerabilities underlying drug-taking behavior. Refinement of methodological procedures and incorporation of more nuanced environmental features should help improve correspondence between animal and human demand studies as well as clinical translation of such findings. Our hope is that this review and commentary ultimately serves as inspiration for new collaborative efforts involving behavioral economic demand between animal and human researchers who share a common goal of improving substance use treatment outcomes and broader psychological wellbeing. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

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.

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.

Baseline cocaine demand predicts contingency management treatment outcomes for cocaine-use disorder

Cocaine use disorder (CUD) is a significant public health issue. Behavioral interventions such as contingency management (CM) have been demonstrated to be highly effective in promoting cocaine abstinence. However, identifying individual characteristics associated with cocaine relapse may help improve treatment outcomes. Cocaine demand is a behavioral economic measure that shares a scientific foundation with CM. In the current study, we assessed baseline cocaine demand using a hypothetical cocaine purchasing task. Participants (N = 58) consisted of treatment-seeking individuals with CUD. All participants received 1 month of CM treatment for cocaine abstinence, and treatment responders were defined as presenting 6 consecutive cocaine negative urine samples from thrice weekly clinic visits. Demand data were well described by the exponentiated demand model. Indices of demand (intensity of demand [Q₀], elasticity [α]) were significantly associated with recent (last 30 days) cocaine use. Importantly, linear regression revealed that CM treatment nonresponders presented significantly higher Q₀ (p = .025). Subsequent quantile regression analyses examining the relationship between CM treatment response and Q₀ revealed statistically reliable effects of being a nonresponder across 3 of the lower percentiles (i.e., 15, 25, and 30). Overall, these findings provide further support for the utility of exponentiated demand model. To our knowledge, this is the first study to demonstrate an association between baseline demand and contingency management response and systematically extend the findings of prior demand research to a novel drug class, cocaine. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

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.

Behavioral economic tobacco demand in relation to cigarette consumption and nicotine dependence: a meta-analysis of cross-sectional relationships

BACKGROUND AND AIMS

A cigarette purchase task (CPT) aims to characterize individual variation in the reinforcing value of tobacco. This meta-analysis estimated the associations between cigarette demand, tobacco consumption and nicotine dependence using this task.

DESIGN

A meta-analysis of cross-sectional studies identified by PubMed and PsycINFO databases was conducted. Fixed- and random-effects models were used. The study also examined the model used to derive elasticity of demand (exponential or exponentiated) as a potential moderator. Publication bias was assessed using 'fail-safe N', Begg-Mazumdar test, Egger's test, Tweedie's trim-and-fill approach and meta-regression of publication year with effect size.

SETTING

Studies from any setting that reported coefficient correlations on the tested associations.

PARTICIPANTS

Daily cigarette users (i.e. 5 to 38 cigarettes per day; n = 7649).

MEASUREMENTS

Cigarette consumption, nicotine dependence and five tobacco demand indicators: intensity (i.e. consumption at no cost), elasticity (i.e. sensitivity to rises in costs), Omax (maximum expenditure), Pmax (i.e. price at which consumption becomes elastic) and breakpoint (i.e. price at which consumption ceases).

FINDINGS

Twenty-three studies met inclusion criteria. All the CPT indices were significantly correlated with smoking behavior (rs = 0.044-0.572, Ps = 0.012-10-8 ). Medium-to-large effect size associations were present for intensity, Omax, and elasticity, whereas small effects were obtained for breakpoint and Pmax . Evidence of a moderating effect of the different elasticity modeling approaches was not present. There was limited evidence of publication bias.

CONCLUSIONS

All five demand indices derived from the cigarette purchase task by (CPT) were robustly associated with cigarette consumption and tobacco dependence. Of the demand indices, maximum expenditure, intensity and elasticity exhibited the largest magnitude associations.

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.

Influence of phendimetrazine maintenance on the reinforcing, subjective, performance, and physiological effects of intranasal cocaine

RATIONALE

No pharmacotherapies are approved for cocaine use disorder. Phendimetrazine, a prodrug of the monoamine-releaser phenmetrazine, attenuates the reinforcing effects of cocaine in preclinical models, has minimal abuse potential, and is safe when combined with cocaine.

OBJECTIVES

This study determined the influence of phendimetrazine maintenance on the reinforcing effects of cocaine (i.e., choice to self-administer cocaine), along with the subjective, performance, and physiological effects of cocaine. We hypothesized that phendimetrazine would attenuate the reinforcing effects of cocaine.

METHODS

Twenty-nine subjects with cocaine use disorder completed this within-subject, inpatient study. The subjects were maintained on placebo and 210 mg phendimetrazine in a counterbalanced order. After at least 7 days of maintenance on the target dose, the subjects completed experimental sessions in which the effects of single doses of 0, 20, 40, and 80 mg of intranasal cocaine were determined.

RESULTS

Cocaine functioned as a reinforcer, producing significant dose-related increases in self-administration. Cocaine increased prototypic effects (e.g., ratings of stimulated and blood pressure). Phendimetrazine attenuated ratings on a select set of subjective outcomes (e.g., ratings of talkative/friendly), but failed to reduce the reinforcing effects of cocaine or a majority of positive subjective cocaine effects. Phendimetrazine increased heart rate, indicating a physiologically active dose was tested, but heart rate increases were not clinically significant.

CONCLUSIONS

These results indicate that although phendimetrazine can safely be combined with cocaine, it does not attenuate the abuse-related effects of cocaine. It is unlikely, then, that phendimetrazine will be an effective standalone treatment for cocaine use disorder.

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.

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

BACKGROUND

The Alcohol Purchase Task (APT) is a behavioral economic assessment of alcohol demand (i.e., motivation for consumption during escalating levels of response cost) using simulated marketplace survey techniques. While the APT is often used and widely cited, to date, there has yet to be a systematic review elucidating the variability in administering and analyzing the APT. The purpose of the current paper is to address this knowledge gap in the literature by cataloging the various purchase task methodologies and providing recommendations and future areas of inquiry.

METHODS

The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology was utilized (Prospero: No. CRD42017072159). Searches through Google Scholar, PsychINFO, PubMed, and SpringerLink databases identified 47 empirical articles referencing the use of an APT and published through the year 2016. Articles were coded for demographic and procedural characteristics, structural characteristics of the APT itself, and characteristics of data analysis.

RESULTS

Results indicate substantial variation within categories and suggest that there is no standard approach to administering the APT or analyzing the responses generated from it. The results underscore the need for researchers to report as much information as possible related to administration, instructions, price structuring, and analytical approach, as we found that many articles did not provide these details.

CONCLUSION

Enhancing the transparency of APT methods and analyses in published reports will aid in reproducibility as well as future meta-analytic studies of alcohol demand that could lead to the development of best-practice recommendations for this procedure.

Clinical models of decision making in addiction

As research on decision making in addiction accumulates, it is increasingly clear that decision-making processes are dysfunctional in addiction and that this dysfunction may be fundamental to the initiation and maintenance of addictive behavior. How drug-dependent individuals value and choose among drug and nondrug rewards is consistently different from non-dependent individuals. The present review focuses on the assessment of decision-making in addiction. We cover the common behavioral tasks that have shown to be fruitful in decision-making research and highlight analytical and graphical considerations, when available, to facilitate comparisons within and among studies. Delay discounting tasks, drug demand tasks, drug choice tasks, the Iowa Gambling Task, and the Balloon Analogue Risk Task are included.

Using crowdsourcing to examine behavioral economic measures of alcohol value and proportionate alcohol reinforcement

Online crowdsourcing websites such as Amazon's Mechanical Turk (MTurk) are increasingly being used in addictions research. However, there is a relative paucity of such research examining the validity of administering behavioral economic alcohol-related measures, via an online crowdsourcing platform. This study sought to validate an alcohol purchase task (APT) for assessing demand and a questionnaire measure of proportionate alcohol reinforcement, using an online sample of participants recruited via MTurk. Participants (N = 865, 59% female) were recruited via MTurk to complete the APT, proportionate alcohol reinforcement questionnaire, Alcohol Use Disorders Identification Test (AUDIT), and demographics. Responses on the APT were highly systematic (<3% nonsystematic data) and conformed to prototypical demand curves. Correlation analyses revealed significant associations among AUDIT total scores with a majority of the alcohol demand indices (r values .08-53, p values < .05) as well as proportionate alcohol reinforcement, r = .43, p < .001. Regression analyses controlling for relevant covariates indicated that intensity, BP, Omax, elasticity, and reinforcement ratio predicted significant variance in AUDIT scores. This study further supports the use of online crowdsourcing websites for investigating behavioral economic determinants of alcohol misuse. (PsycINFO Database Record

Unique prediction of cannabis use severity and behaviors by delay discounting and behavioral economic demand

Few studies have simultaneously evaluated delay discounting and behavioral economic demand to determine their unique contribution to drug use. A recent study in cannabis users found that monetary delay discounting uniquely predicted cannabis dependence symptoms, whereas cannabis demand uniquely predicted use frequency. This study sought to replicate and extend this research by evaluating delay discounting and behavioral economic demand measures for multiple commodities and including a use quantity measure. Amazon.com's Mechanical Turk was used to sample individuals reporting recent cannabis use (n=64) and controls (n=72). Participants completed measures of monetary delay discounting as well as alcohol and cannabis delay discounting and demand. Cannabis users and controls did not differ on monetary delay discounting or alcohol delay discounting and demand. Among cannabis users, regression analyses indicated that cannabis delay discounting uniquely predicted use severity, whereas cannabis demand uniquely predicted use frequency and quantity. These effects remained significant after controlling for other delay discounting and demand measures. This research replicates previous outcomes relating delay discounting and demand with cannabis use and extends them by accounting for the contribution of multiple commodities. This research also demonstrates the ability of online crowdsourcing methods to complement traditional human laboratory techniques.