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

Utility of a brief measure of cannabis demand: Day-level associations with cannabis use

BACKGROUND

Cannabis demand (i.e., relative value) is usually assessed as a trait-level risk-factor for cannabis use and consequences. This study examined within-person variability in day-level intensity (i.e., amount consumed at zero cost) and Omax (i.e., maximum cannabis expenditure) and tested hypotheses that demand would be positively associated with day-level cannabis use.

METHODS

Young adults (n=85) reporting past-month simultaneous alcohol and cannabis use completed two daily surveys for 30 days. Morning surveys assessed prior-day cannabis use and evening surveys assessed day-level demand (i.e., intensity, Omax). Multilevel models tested day-level effects of intensity and Omax on any cannabis use and flower use frequency and quantity (i.e., grams).

RESULTS

Approximately 52 % and 46 % of variability in intensity and Omax, respectively, was due to within-person change. At the day-level, higher intensity and Omax were associated with higher likelihood of any cannabis use, regardless of formulation; Omax was associated with use of flower in particular; and intensity was associated with the highest quantity of use. At the person-level, only Omax was associated with flower use likelihood, and only intensity was associated with flower quantity across days.

CONCLUSIONS

Cannabis demand demonstrated day-to-day variability, conceivably in response to various internal states and external factors. Intensity and Omax were related to elevated likelihood of using any cannabis, particularly flower, at the day-level. Overall, these data illustrate the validity and utility of brief cannabis demand measures, which might be used to further understand cannabis' reinforcing value at a fine-grained level.

Human laboratory models of reward in substance use disorder

Human laboratory models in substance use disorder provide a key intermediary step between highly controlled and mechanistically informative non-human preclinical methods and clinical trials conducted in human populations. Much like preclinical models, the variety of human laboratory methods provide insights into specific features of substance use disorder rather than modelling the diverse causes and consequences simultaneously in a single model. This narrative review provides a discussion of popular models of reward used in human laboratory research on substance use disorder with a focus on the specific contributions that each model has towards informing clinical outcomes (forward translation) and analogs within preclinical models (backward translation). Four core areas of human laboratory research are discussed: drug self-administration, subjective effects, behavioral economics, and cognitive and executive function. Discussion of common measures and models used, the features of substance use disorder that these methods are purported to evaluate, unique issues for measure validity and application, and translational links to preclinical models and special considerations for studies wishing to evaluate homology across species is provided.

Behavioral therapies targeting reward mechanisms in substance use disorders

Behavioral therapies are considered best practices in the treatment of substance use disorders (SUD) and used as first-line approaches for SUDs without FDA-approved pharmacotherapies. Decades of research on the neuroscience of drug reward and addiction have informed the development of current leading behavioral therapies that, while differing in focus and technique, have in common the overarching goal of shifting reward responding away from drug and toward natural non-drug rewards. This review begins by describing key neurobiological processes of reward in addiction, followed by a description of how various behavioral therapies address specific reward processes. Based on this review, a conceptual 'map' is crafted to pinpoint gaps and areas of overlap, serving as a guide for selecting and integrating behavioral therapies.

Using behavioral economics to optimize safer undergraduate late-night transportation

Many universities sponsor student-oriented transit services that could reduce alcohol-induced risks but only if services adequately anticipate and adapt to student needs. Human choice data offer an optimal foundation for planning and executing late-night transit services. In this simulated choice experiment, respondents opted to either (a) wait an escalating delay for a free university-sponsored "safe" option, (b) pay an escalating fee for an on-demand rideshare service, or (c) pick a free, immediately available "unsafe" option (e.g., ride with an alcohol-impaired driver). Behavioral-economic nonlinear models of averaged-choice data describe preference across arrangements. Best-fit metrics indicate adequate sensitivity to contextual factors (i.e., wait time, preceding late-night activity). At short delays, students preferred the free transit option. As delays extend beyond 30 min, most students preferred competing alternatives. These data depict a policy-relevant delay threshold to better safeguard undergraduate student safety.

Use of drug purchase tasks in medications development research: orexin system regulation of cocaine and drug demand

Commodity purchase tasks provide a useful method for evaluating behavioral economic demand in the human laboratory. Recent research has shown how responding to purchase tasks for blinded drug administration can be used to study abuse liability. This analysis uses data from a human laboratory study to highlight how similar procedures may be particularly useful for understanding momentary changes in drug valuation when screening novel interventions. Eight nontreatment-seeking participants with cocaine use disorder (one with partial data) were enrolled in a cross-over, double-blind, randomized inpatient study. Participants were maintained on the Food and Drug Administration-approved insomnia medication suvorexant (oral; 0, 5, 10, 20 mg/day) in randomized order with experimental sessions completed after at least 3 days of maintenance on each suvorexant dose. Experimental sessions included administration of a sample dose of 0, 10 and 30 mg/70 kg intravenous cocaine. Analyses focused on purchase tasks for the blinded sample dose as well as alcohol, cigarettes and chocolate completed 15 min after the sample dose. As expected based on abuse liability, near zero demand was observed for placebo with dose-related increases in cocaine demand. Suvorexant maintenance increased cocaine demand in a dose-related manner with the greatest increase observed for the 10 mg/kg cocaine dose. Increased demand under suvorexant maintenance was also observed for alcohol. No effect of cocaine administration was observed for alcohol, cigarette, or chocolate demand. These data support the validity of demand procedures for measuring blinded drug demand. Findings also parallel self-administration data from this study by showing increases in cocaine use motivation under suvorexant maintenance.

The Blinded-Dose Purchase Task: assessing hypothetical demand based on cocaine, methamphetamine, and alcohol administration

RATIONALE

Behavioral economic drug purchase tasks quantify the reinforcing value of a drug (i.e., demand). Although widely used to assess demand, drug expectancies are rarely accounted for and may introduce variability across participants given diverse drug experiences.

OBJECTIVES

Three experiments validated and extended previous hypothetical purchase tasks by using blinded drug dose as a reinforcing stimulus, and determined hypothetical demand for experienced effects while controlling for drug expectancies.

METHODS

Across three double-blind, placebo-controlled, within-subject experiments, cocaine (0, 125, 250 mg/70 kg; n=12), methamphetamine (0, 20, 40 mg; n=19), and alcohol (0, 1 g/kg alcohol; n=25) were administered and demand was assessed using the Blinded-Dose Purchase Task. Participants answered questions regarding simulated purchasing of the blinded drug dose across increasing prices. Demand metrics, subjective effects, and self-reported real-world monetary spending on drugs were evaluated.

RESULTS

Data were well modeled by the demand curve function, with significantly higher intensity (purchasing at low prices) for active drug doses compared to placebo for all experiments. Unit-price analyses revealed more persistent consumption across prices (lower α) in the higher compared to lower active dose condition for methamphetamine (a similar non-significant finding emerged for cocaine). Significant associations between demand metrics, peak subjective effects, and real-world spending on drugs also emerged across all experiments.

CONCLUSIONS

Orderly demand curve data revealed differences across drug and placebo conditions, and relations to real-world measures of drug spending, and subjective effects. Unit-price analyses enabled parsimonious comparisons across doses. Results lend credence to the validity of the Blinded-Dose Purchase Task, which allows for control of drug expectancies.

Concurrent validity of the marijuana purchase task: a meta-analysis of trait-level cannabis demand and cannabis involvement

BACKGROUND AND AIMS

The Marijuana Purchase Task (MPT) is increasingly used to measure cannabis reinforcing value and has potential use for cannabis etiological and regulatory research. This meta-analysis sought to evaluate for the first time the MPT's concurrent validity in relation to cannabis involvement.

METHODS

Electronic databases and pre-print repositories were searched for MPT studies that examined the cross-sectional relationship between frequency and quantity of cannabis use, problems, dependence, and five MPT indicators: intensity (i.e. unrestricted consumption), Omax (i.e. maximum consumption), Pmax (i.e. price at which demand becomes elastic), breakpoint (i.e. first price at which consumption ceases), and elasticity (i.e. sensitivity to rising costs). Random effects meta-analyses of cross-sectional effect sizes were conducted, with Q tests for examining differences by cannabis variables, meta-regression to test quantitative moderators, and publication bias assessment. Moderators included sex, number of MPT prices, variable transformations, and year of publication. Populations included community and clinical samples.

RESULTS

The searches yielded 14 studies (n = 4077, median % females: 44.8%: weighted average age = 29.08 [SD = 6.82]), published between 2015 and 2022. Intensity, Omax , and elasticity showed the most robust concurrent validity (|r's| = 0.147-325, ps < 0.014) with the largest significant effect sizes for quantity (|r| intensity = 0.325) and cannabis dependence (|r| Omax  = 0.320, |r| intensity = 0.305, |r| elasticity = 0.303). Higher proportion of males was associated with increased estimates for elasticity-quantity and Pmax -problems. Higher number of MPT prices significantly altered magnitude of effects sizes for Pmax and problems, suggesting biased estimations if excessively low prices are considered. Methodological quality was generally good, and minimal evidence of publication bias was observed.

CONCLUSIONS

The marijuana purchase task presents adequate concurrent validity to measure cannabis demand, most robustly for intensity, Omax , and elasticity. Moderating effects by sex suggest potentially meaningful sex differences in the reinforcing value of cannabis.

Reinforcer pathology, probabilistic choice, and medication adherence in patients with multiple sclerosis

The reinforcer pathology model posits that core behavioral economic mechanisms, including delay discounting and behavioral economic demand, underlie adverse health decisions and related clinical disorders. Extensions beyond substance use disorder and obesity, however, are limited. Using a reinforcer pathology framework, this study evaluates medical adherence decisions in patients with multiple sclerosis. Participants completed behavioral economic measures, including delay discounting, probability discounting, and a medication purchase task. A medical decision-making task was also used to evaluate how sensitivity to mild side effect risk and efficacy contributed to the likelihood of taking a hypothetical disease-modifying therapy. Less steep delay discounting and more intense (greater) medication demand were independently associated with greater adherence to the medication decision-making procedure. More generally, the pattern of interrelations between the medication-specific and general behavioral economic metrics was consistent with and contributes to the reinforcer pathology model. Additional research is warranted to expand these models to different populations and health behaviors, including those of a positive health orientation (i.e., medication adherence).

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.

Hyperbolic discounting and exponentiated demand: Modeling demand for cigarettes in three dimensions

Behavioral economics has been a fruitful area of research in substance use. Mathematical descriptions of how individuals temporally discount the value of a commodity have been correlated with substance use and mathematical descriptions of drug consumption decreasing as a function of price (i.e., demand) predict maladaptive substance use. While there is a logical assumption that temporal factors affect demand for a drug, little has been done to merge these models. Thus, the purpose of this study was to combine models of discounting and demand, extending Howard Rachlin's work and contributions to novel areas of study. Data from 85 participants from Amazon Mechanical Turk (MTurk) who completed a hypothetical cigarette purchase task that included price of and delay to cigarettes were analyzed. Multilevel modeling was used to determine descriptive accuracy of combined additive and multiplicative models of discounting and demand. Of the discounting models used in conjunction with the exponentiated demand equation, the Rachlin hyperboloid best described the delay dimension of consumption. The multiplicative version of the Rachlin equation applied to both delay and price outperformed other models tested. Therefore, existing models of discounting and demand can be extended to modeling consumption data from complex multidimensional experimental arrangements.

Behavioral economic methods predict future COVID-19 vaccination

Increasing vaccine utilization is critical for numerous diseases, including COVID-19, necessitating novel methods to forecast uptake. Behavioral economic methods have been developed as rapid, scalable means of identifying mechanisms of health behavior engagement. However, most research using these procedures is cross-sectional and evaluates prediction of behaviors with already well-established repertories. Evaluation of the validity of hypothetical tasks that measure behaviors not yet experienced is important for the use of these procedures in behavioral health. We use vaccination during the COVID-19 pandemic to test whether responses regarding a novel, hypothetical behavior (COVID-19 vaccination) are predictive of later real-world response. Participants (N = 333) completed a behavioral economic hypothetical purchase task to evaluate willingness to receive a hypothetical COVID-19 vaccine based on efficacy. This was completed in August 2020, before clinical trial data on COVID-19 vaccines. Participants completed follow-up assessments approximately 1 year later when the COVID-19 vaccines were widely available in June 2021 and November 2021 with vaccination status measured. Prediction of vaccination was made based on data collected in August 2020. Vaccine demand was a significant predictor of vaccination after controlling for other significant predictors including political orientation, delay discounting, history of flu vaccination, and a single-item intent to vaccinate. These findings show predictive validity of a behavioral economic procedure explicitly designed to measure a behavior for which a participant has limited-to-no direct prior experience or exposure. Positive correspondence supports the validity of these hypothetical arrangements for predicting vaccination utilization and advances behavioral economic methods.

Behavioral economics indices predict alcohol use and consequences in young men at 4-year follow-up

BACKGROUND AND AIMS

The alcohol purchase task (APT), which presents a scenario and asks participants how many drinks they would purchase and consume at different prices, generates indices of alcohol reward value that have shown robust associations with alcohol-related outcomes in numerous studies. The aim was to test its prospective validity at 4-year follow-up.

DESIGN

Prospective cohort study.

SETTING

General population sample of young Swiss men.

PARTICIPANTS

A total of 4594 Swiss young men (median age = 21, 25th - 75th quartiles = 20.5 - 21.5) completed baseline questionnaires; among those, 4214 (91.7%) were successfully followed-up 4 years later.

MEASUREMENTS

Alcohol reward value parameters (i.e. intensity, the planned consumption when drinks are free; breakpoint, the price at which consumption would be suppressed; O_max , the maximum alcohol expenditure; P_max , the price associated with O_max ; and elasticity, the relative change in alcohol consumption as a function of the relative change in price) were derived from the APT at baseline and used to predict self-reported weekly drinking amount, monthly binge drinking, alcohol-related consequences and DSM-5 alcohol use disorder criteria.

FINDINGS

Regression analyses, adjusting for the baseline alcohol measure, age, linguistic region and socio-economic indicators showed that intensity, breakpoint, O_max and elasticity significantly predicted all tested outcomes in the expected direction (e.g. standardized incidence rate ratio [95% confidence interval] = 1.11 [1.07-1.15], 1.07 [1.03-1.10], 1.08 [1.04-1.11], and 0.92 [0.89-0.95], respectively, for weekly drinking amount, all P < 0.001). P_max did not significantly predict any outcomes. Non-adjusted correlations, baseline adjusted regression and ancillary analyses using (1) latent alcohol variables, (2) multiple imputation for missing data and (3) replications in training and testing subsamples to evaluate predictive accuracy provided consistent findings.

CONCLUSIONS

The alcohol purchase task demand curve measures of alcohol reward value are useful in characterizing alcohol-related risk in young men and have long-term predictive utility.

Prospective associations between sleep disturbances and cannabis use among Veterans: A behavioral economic approach

BACKGROUND

Veterans often use cannabis for sleep despite limited evidence of its efficacy. Moreover, how sleep disturbances impact cannabis use longitudinally is unclear. We applied a behavioral economic framework to examine whether sleep disturbances and cannabis demand (i.e., relative value) were related risk-factors for future cannabis use and problems.

METHODS

Veterans deployed post-9/11/2001 who reported past 6-month cannabis use at baseline (n = 126) completed surveys on their sleep disturbances, demand via the Marijuana Purchase Task (MPT), and cannabis use. Mediation analyses using Hayes' PROCESS Macro and zero-inflated negative binomial models tested indirect effects of baseline sleep disturbances on 12-month cannabis use frequency, quantity, and problems via 6-month cannabis demand (i.e., intensity, Omax, Pmax, and breakpoint).

RESULTS

Only Omax (i.e., maximum expenditure for cannabis) was a significant mediator for 12-month cannabis use quantity and problems when examined concurrently with other demand indices after controlling for covariates. Intensity (i.e., purchase at zero cost) was a significant mediator for 12-month cannabis use frequency when examined concurrently with other demand indices in models controlling for lifetime cannabis use, but not past 30-day use at baseline.

CONCLUSION

Cannabis demand, specifically intensity and Omax, may help to identify Veterans with sleep disturbances who are at increased risk for escalating their cannabis use. Subsequent research should assess the extent that sleep disturbances impact cannabis demand in the context of withdrawal, which will inform novel prevention and intervention strategies geared toward reducing negative cannabis-related outcomes among Veterans.

What influences demand for cigars among African American adult cigar smokers? Results from a hypothetical purchase task

African Americans (AA) have historically been targeted by the tobacco industry and have the highest rates of current cigar use among racial/ethnic groups in the U.S. Yet, there is limited evidence on other factors influencing cigar use. Amongst a sample of 78 AA current cigar (any type) smokers, log-linear regression models examined correlates of cigar demand obtained from a validated behavioral economic purchase task. Mean intensity, or cigar demand when free, was 6.68 cigars (standard deviation [SD]: 8.17), while mean breakpoint, or the highest price a participant was willing to pay, was $4.62 (SD: 3.88). Mean maximum daily expenditure, Omax was $15.20 (SD: 25.73) and Pmax, the price at Omax was $5.25 (SD: 3.95). Participants aged 21 to 30 years compared to those aged 18 to 20 years, those with higher levels of dependence, and females compared to males, had a significantly higher intensity. Participants with cannabis use above the sample median in the last 30 days (4 + days) had significantly higher intensity and Omax than those below the median. Further, participants with a high school education or more had a significantly lower intensity, breakpoint, and Omax than those with less than high school education. Individuals with income below the federal poverty line (FPL) also had a significantly lower breakpoint and Omax than those above. Finally, tobacco harm perceptions were inversely associated with Pmax. Stricter policies on cigar products, such as higher taxes and product-specific harm messaging, may have an immediate and sustained impact on health disparities related to cigar use. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Use patterns, beliefs, experiences, and behavioral economic demand of indica and sativa cannabis: A cross-sectional survey of cannabis users

Cannabis products available for retail purchase are often marketed based on purported plant species (e.g., "indica" or "sativa"). The cannabis industry frequently claims that indica versus sativa cannabis elicits unique effects and/or is useful for different therapeutic indications. Few studies have evaluated use patterns, beliefs, subjective experiences, and situations in which individuals use indica versus sativa. A convenience sample of cannabis users (n = 179) was surveyed via Amazon Mechanical Turk (mTurk). Participants were asked about their prior use of, subjective experiences with, and opinions on indica versus sativa cannabis and completed hypothetical purchasing tasks for both cannabis subtypes. Participants reported a greater preference to use indica in the evening and sativa in the morning and afternoon. Participants were more likely to perceive feeling "sleepy/tired" or "relaxed" after using indica and "alert," "energized," and "motivated" after using sativa. Respondents were more likely to endorse wanting to use indica if they were going to sleep soon but more likely to use sativa at a party. Hypothetical purchasing patterns (i.e., grams of cannabis purchased as a function of escalating price) did not differ between indica and sativa, suggesting that demand was similar. Taken together, cannabis users retrospectively report feeling different effects from indica and sativa; however, demand generally did not differ between cannabis subtypes, suggesting situational factors could influence whether someone uses indica or sativa. Placebo-controlled, blinded studies are needed to characterize the pharmacodynamics and chemical composition of indica and sativa cannabis and to determine whether user expectancies contribute to differences in perceived indica/sativa effects. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Probability Discounting in College Students' Willingness to Isolate During COVID-19: Implications for Behavior Analysis and Public Health

The present study was a preliminary analysis of college students' willingness to self-isolate and socially isolate during the COVID-19 pandemic analyzed through a probability discounting framework. Researchers developed a pandemic likelihood discounting task where willingness to isolate from others was measured in days as a function of the perceived probability of the escalation of a virus to pandemic levels. Experiment 1 was conducted immediately prior to the World Health Organization (WHO) declaring COVID-19 a pandemic and results showed that participants were more willing to self-isolate when the perceived probability of reaching pandemic levels was high and when there was a guarantee that others in the community would do the same. Experiment 2 was conducted with a subset of participants from Experiment 1 with the same discounting task, and results showed that participants were more willing to self-isolate 2 months following the onset of the pandemic, supporting the view that willingness to isolate from others is a dynamic process. Finally, Experiment 3 evaluated willingness to socially distance and introduced a hypothetical timescale to evaluate common trends with the real-world temporal dynamics observed in Experiments 1 and 2. Results showed similar trends in the data, supporting the use of hypothetical scenarios within probability discounting tasks in future behavior analytic research related to public health.

Using crowdsourcing to study the differential effects of cross-drug withdrawal for cigarettes and opioids in a behavioral economic demand framework

Smoking rates among those who use prescribed or recreational opioids are significantly higher than the general population. Hypothesized neuropharmacological interactions between opioids and nicotine may contribute to this pattern of polysubstance use, especially during withdrawal. However, little research has examined how the withdrawal of one substance may affect the consumption of the other (i.e., cross-drug withdrawal effects). Behavioral economic demand tasks (e.g., hypothetical purchase tasks) can be used to quickly assess the value of a drug. Crowdsourcing can be a convenient tool to gain preliminary insight into different processes in substance valuation that may otherwise be impossible or prohibitively difficult to study. The purpose of the present study was to provide a preliminary examination of the effects of hypothetical withdrawal of cigarettes and opioids on the consumption of those drugs among polysubstance users. Amazon Mechanical Turk workers who reported daily smoking and at least monthly opioid use completed a series of hypothetical purchase tasks for doses of opioids and cigarettes under various withdrawal conditions. Sensitivity to the price of both drugs decreased when under withdrawal for either, indicating a higher drug value of cigarettes and opioids due to effects of cross-drug withdrawal. Nicotine and opioid dependence severity, impulsive choice, and riskiness were also positively related to drug purchasing. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Alcohol demand as a predictor of drinking behavior in the natural environment

BACKGROUND AND AIMS

Alcohol demand, a measure of alcohol's reinforcing value, is associated with greater alcohol consumption and alcohol-related problems. Although alcohol demand has primarily been evaluated as a 'trait-like', individual difference measure, recent evidence indicates that demand exhibits meaningful short-term fluctuations. We aimed to determine whether moment-to-moment fluctuations in alcohol demand in individuals' natural drinking environments predicted drinking occurrence, drinking continuation, and drinking quantity.

DESIGN

Observational study.

SETTING

Individuals' natural drinking environments in Columbia, Missouri, USA.

PARTICIPANTS

Eighty-nine young adults (56% female; mean age = 24.8) participated from November 2018 to October 2020. Participants reported 14.5 drinking days [standard deviation (SD = 8.1)] and 4.1 drinks per occasion (SD = 2.5) during ecological momentary assessment (EMA).

MEASUREMENTS

Participants completed the alcohol purchase task at baseline. Following this, participants reported on their alcohol demand (breakpoint, O_max , intensity) and drinking behavior during EMA at daily, timed prompts from 6 p.m. to 2 a.m. They provided breathalyzer samples using a BACtrack Mobile® Pro. Models tested concurrent and prospective (lagged) associations between alcohol demand and drinking occurrence and drinking continuation after drinking initiation. Additional models tested concurrent associations between demand and breath alcohol concentrations (BrACs).

FINDINGS

Higher alcohol demand was associated with higher odds of drinking and continued drinking for all demand indices at the momentary [odds ratio (OR) = 1.27-1.56, ps ≤ 0.03] and day-level (OR = 2.14-3.39, ps < 0.001). Additionally, lagged demand predicted higher odds of drinking occurrence and continuation at the following prompt (OR = 1.32-1.53, ps ≤ 0.004). Higher alcohol demand was associated with higher BrACs at the momentary (bs = 0.0011-0.0026, ps ≤ 0.03) and day-level (bs = 0.0053-0.0062, ps < 0.001). At the person-level, findings varied depending on the demand measure.

CONCLUSIONS

Alcohol demand appears to be associated with both when and how much individuals drink in their natural drinking environments. Elevations in alcohol demand appear to be associated with increased likelihood of drinking and continuing to drink, and greater total alcohol consumption, both within and across drinking days.

A neuroeconomic signature of opioid craving: How fluctuations in craving bias drug-related and nondrug-related value

How does craving bias decisions to pursue drugs over other valuable, and healthier, alternatives in addiction? To address this question, we measured the in-the-moment economic decisions of people with opioid use disorder as they experienced craving, shortly after receiving their scheduled opioid maintenance medication and ~24 h later. We found that higher cravers had higher drug-related valuation, and that moments of higher craving within-person also led to higher drug-related valuation. When experiencing increased opioid craving, participants were willing to pay more for personalized consumer items and foods more closely related to their drug use, but not for alternative "nondrug-related" but equally desirable options. This selective increase in value with craving was greater when the drug-related options were offered in higher quantities and was separable from the effects of other fluctuating psychological states like negative mood. These findings suggest that craving narrows and focuses economic motivation toward the object of craving by selectively and multiplicatively amplifying perceived value along a "drug relatedness" dimension.

Commodity Recommendation Model Integrating User Psychological Data Analysis

E-commerce recommendation plays an irreplaceable role in alleviating product information overload and improving consumers' personalized experience and sales conversion rate. According to the idea of recommendation, e-commerce recommendation can be divided into two types: recommendation based on correlation and recommendation based on causality. The former, such as collaborative filtering and other recommendation methods, is highly dependent on data; the latter, such as product recommendation based on consumer psychology, has great superiority in new product recommendation due to the introduction of such domain knowledge as consumer psychology in the recommendation. In this paper, we select three representative consumer psychologies of "consumer motivation," "consumer attitude," and "consumer interest" to explore the recommendation of products with multiple consumer psychologies. On the one hand, according to the theory of consumption psychology and the need of e-commerce recommendation, some product-store attributes are selected as attribute variables. A comprehensive comparison and analysis of the patterns presented by multiple consumer psychology in product recommendations are conducted, and the patterns of multiple consumer psychology product recommendations are analyzed from two perspectives: recommendation stability and recommendation result patterns, respectively, and the reasons for them are analyzed. It is clear that the recommendation method based on dual consumption psychology and triple consumption psychology can also effectively achieve product recommendation. In this paper, we compare and analyze the difference in recommendation accuracy between single consumption psychology, dual consumption psychology, and triple consumption psychology and find that compared with single consumption psychology, product recommendation based on dual consumption psychology and triple consumption psychology can basically improve the accuracy of product recommendation, and the accuracy of dual consumption psychology is generally higher than that of triple consumption psychology, among which the accuracy of product recommendation based on dual consumption motivation-attitude psychology is the highest.

(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).

Effects of Very Low Nicotine Content Cigarette use on Cigarette Reinforcement among Smokers with Serious Mental Illness

BACKGROUND

Among people without psychiatric disorders who smoke, very low nicotine content (VLNC) cigarette use reduces cigarette reinforcement. Whether this is true of people with serious mental illness (SMI) who smoke is unknown. Using a hypothetical purchase task, we compared the effects of 6-week use of VLNC versus normal nicotine content (NNC) cigarettes on study cigarette and usual brand (UB) cigarette reinforcement among people with SMI who smoke.

METHODS

After a baseline period of UB cigarette use, participants with SMI (n = 58) were randomized to use NNC cigarettes (15.8 mg nicotine/g tobacco) or VLNC cigarettes (0.4 mg/g) for 6 weeks. At Week 6, they completed the CPT for both their assigned study cigarette and UB. The groups were compared on demand intensity (number of cigarettes purchased at no cost) and elasticity (rate of decline in demand as price increases) using extra sum-of-squares F-tests. The effects of treatment on demand indices while controlling for covariates were assessed using hierarchical regression.

RESULTS

At Week 6, intensity of demand for study cigarettes was lower and elasticity was higher for the VLNC group relative to the NNC group (p < 0.0001). Furthermore, intensity of demand for UB cigarettes was lower for participants in the VLNC group relative to participants in the NNC group (p < 0.01). When controlling for baseline cigarettes per day, intensity remained significantly different for study cigarettes and usual brand cigarettes at Week 6.

CONCLUSION

A nicotine reduction policy may reduce cigarette reinforcement in this vulnerable population.

Behavioral economic interactions between cannabis and alcohol purchasing: Associations with disordered use

As cannabis policy changes, there is an urgent need to understand interactions between cannabis and alcohol couse. An online sample of 711 adult past-month cannabis and alcohol users completed both single-item hypothetical purchasing tasks for cannabis and alcohol and cross-commodity purchasing tasks assessing adjusting-price cannabis with concurrently available, fixed-price alcohol, and vice versa. Participants provided information about cannabis and alcohol use patterns, and completed the Alcohol and Cannabis Use Disorder Identification Tests (AUDIT and CUDIT, respectively). Group data showed that cannabis and alcohol served as complements (as the price of the adjusting-price commodity increased, consumption of both commodities decreased). However, individual data showed substantial variability with nontrivial proportions showing patterns of complementarity, substitution, and independence. More negative slopes (greater complementarity) for fixed-price cannabis and alcohol were both associated with greater self-reported drug consumption and CUDIT and AUDIT scores. The negative relation between cross-price slope and CUDIT/AUDIT score indicates that individuals who treat cannabis and alcohol more as complements are more likely to experience disordered use. Based on these cross-commodity purchasing data, when both cannabis and alcohol are concurrently available at low prices, both may be used at high levels, whereas limiting consumption of one commodity (e.g., through increased price) may reduce consumption of the other. These data show the importance of examining individual participant analyses of behavioral economic drug interactions and suggest that manipulation of cost (e.g., through taxes) or cosale restrictions are potential public health regulatory mechanisms for reducing alcohol and cannabis use and couse behaviors. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A Brief Introduction to Human Behavioral Pharmacology: Methods, Design Considerations and Ethics

Human behavioral pharmacology methods have been used to rigorously evaluate the effects of a range of centrally acting drugs in humans under controlled conditions for decades. Methods like drug self-administration and drug discrimination have been adapted from nonhuman laboratory animal models. Because humans have the capacity to communicate verbally, self-report methods are also commonly used to understand drug effects. This perspective article provides an overview of these traditional human behavioral pharmacology methods and introduces some novel methodologies that have more recently been adapted for use in the field. Design (e.g., using placebo controls, testing multiple doses) and ethical (e.g., avoiding enrollment of individuals seeking treatment, determining capacity to consent) considerations that must be addressed when conducting these types of studies are also described.

Cannabis Use Disorder: A Behavioral Economic Perspective

Purpose of Review

To explore relations between behavioral economic demand for cannabis and cannabis use disorder (CUD). Prior reviews have focused on drug demand in relation to use outcomes more generally. Complementing and enhancing prior work synthesizing research on cannabis demand, the present review endeavors to determine whether specific demand indices derived from the marijuana purchase task are most reliably related to CUD. Additionally, sociodemographic characteristics of participants in these studies were reviewed to identify whether certain populations were underrepresented in behavioral economic cannabis research.

Recent Findings

Behavioral economic demand is related to CUD; intensity and elasticity of cannabis demand were consistently associated with CUD diagnosis and severity. However, frequently, only select demand indices were assessed or reported, precluding the ability to confirm which indices are superior for denoting CUD risk. Further, most studies enrolled samples that were predominately young adults, Caucasian, and male.

Summary

As CUD becomes more prevalent in the wake of cannabis legalization, identification of robust predictors of CUD risk is paramount. Cannabis demand is consistently associated with CUD; however, individual indices of import in this relationship remain ambiguous. Subsequent research is needed to confirm index-specific markers of disordered cannabis use, and whether links between demand and CUD generalize across diverse populations.

Behavioral economic methods to inform infectious disease response: Prevention, testing, and vaccination in the COVID-19 pandemic

The role of human behavior to thwart transmission of infectious diseases like COVID-19 is evident. Psychological and behavioral science are key areas to understand decision-making processes underlying engagement in preventive health behaviors. Here we adapt well validated methods from behavioral economic discounting and demand frameworks to evaluate variables (e.g., delay, cost, probability) known to impact health behavior engagement. We examine the contribution of these mechanisms within a broader response class of behaviors reflecting adherence to public health recommendations made during the COVID-19 pandemic. Four crowdsourced samples (total N = 1,366) completed individual experiments probing a response class including social (physical) distancing, facemask wearing, COVID-19 testing, and COVID-19 vaccination. We also measure the extent to which choice architecture manipulations (e.g., framing, opt-in/opt-out) may promote (or discourage) behavior engagement. We find that people are more likely to socially distance when specified activities are framed as high risk, that facemask use during social interaction decreases systematically with greater social relationship, that describing delay until testing (rather than delay until results) increases testing likelihood, and that framing vaccine safety in a positive valence improves vaccine acceptance. These findings collectively emphasize the flexibility of methods from diverse areas of behavioral science for informing public health crisis management.

A systematic review and meta-analysis of delay discounting and cannabis use

Delay discounting reflects the systematic reduction in the value of a consequence by delay to delivery. Theoretical and empirical work suggests that delay discounting is a key behavioral mechanism underlying substance use disorder. Existing work on cannabis use, however, is mixed with many studies reporting null results. The purpose of this review was to provide an in-depth assessment of the association between delay discounting and cannabis use. We conducted metaregression analyses to determine the omnibus correlation between delay discounting and cannabis use, and to evaluate task-based and sample-based moderators. Studies included evaluated an association between delay discounting and cannabis quantity-frequency or severity measures in human participants (27 studies, 61 effect sizes, 24,782 participants). A robust variance estimation method was used to account for dependence among effect sizes. A significant, but small, omnibus effect was observed (r = .082) in which greater cannabis use frequency or severity was associated with greater discounting. Incentive structure and outcome type were each significant moderators in a multiple moderator model such that incentivized tasks correlated with severity measures showed stronger associations (r = .234) than hypothetical tasks correlated with quantity-frequency measures (r = .029). Comparisons to historic effect size data supported the hypothesis that, at present, the relationship between cannabis use and delay discounting appears empirically smaller than for other substances. Future work should explore theoretical rationales explaining this modest relationship involving cannabis use and delay discounting, such as reflecting the smaller magnitude of perceived long-term clinical outcomes associated with cannabis compared to other substances. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

At-Risk Drinking, Operant Demand, and Cross-Commodity Discounting as Predictors of Drunk Driving in Underage College Women

Behavioral economics offers unique tools for assessing value and motivation associated with college drinking. Tasks that model changes in consumption as a function of price (operant demand) or the decline in an outcome's subjective value as a function of time-to-occurrence (delay discounting) provide valuable information that may efficiently supplement clinical screening instruments when characterizing alcohol use severity. The first aim of this investigation was to examine the extent to which at-risk drinking, operant demand for alcohol, and single- and cross-commodity discounting of money and alcohol predict adverse consequences of past-month drinking in underage college women (N = 72). The second aim was to determine whether these clinical and behavioral economic measures could significantly predict the odds of past-month drunk driving, a serious public health concern due to the increasing prevalence of heavy episodic drinking among women in their first 1 - 2 years of college. Results showed that higher scores on the consumption factor of the Alcohol Use Disorder Identification Test (AUDIT-C), greater Persistence (consumption amidst constraint) and Amplitude (maximum consumption) of demand, as well as lower rates of discounting for choices between receiving alcohol now or double the amount after a delay (choosing the larger amount of alcohol even when it is delayed) significantly predicted adverse consequences of past-month drinking. Moreover, scores on the AUDIT-C, Amplitude of demand, and higher rates of discounting for choices between receiving alcohol now and money later (choosing immediately available alcohol at the expense of double the equivalent in delayed money) significantly predicted past-month drunk driving. We contend that operant demand along with single- and cross-commodity discounting can be viewed as intersecting measures of reinforcer value with clinical relevance to college women.

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.

Concurrent validity of the Alcohol Purchase Task for measuring the reinforcing efficacy of alcohol: an updated systematic review and meta-analysis

BACKGROUND AND AIMS

An early meta-analysis testing the concurrent validity of the Alcohol Purchase Task (APT), a measure of alcohol's relative reinforcing value, reported mixed associations, but predated a large number of studies. This systematic review and meta-analysis sought to: (1) estimate the relationships between trait-based alcohol demand indices from the APT and multiple alcohol indicators, (2) test several moderators and (3) analyze small study effects.

METHODS

A meta-analysis of 50 cross-sectional studies in four databases (n = 18 466, females = 43.32%). Sex, year of publication, number of APT prices and index transformations (logarithmic, square root or none) were considered as moderators. Small study effects were examined by using the Begg-Mazumdar, Egger's and Duval & Tweedie's trim-and-fill tests. Alcohol indicators were quantity of alcohol use, number of heavy drinking episodes, alcohol-related problems and hazardous drinking. APT indices were intensity (i.e. consumption at zero cost), elasticity (i.e. sensitivity to increases in costs), O_max (i.e. maximum expenditure), P_max (i.e. price associated to O_max ) and breakpoint (i.e. price at which consumption ceases).

RESULTS

All alcohol demand indices were significantly associated with all alcohol-related outcomes (r = 0.132-0.494), except P_max , which was significantly associated with alcohol-related problems only (r = 0.064)_. The greatest associations were evinced between intensity in relation to alcohol use, hazardous drinking and heavy drinking and between O_max and alcohol use. All the tested moderators emerged as significant moderators. Evidence of small-study effects was limited.

CONCLUSIONS

The Alcohol Purchase Task appears to have concurrent validity in alcohol research. Intensity and O_max are the most relevant indices to account for alcohol involvement.

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.

The Illegal Experimental Tobacco Marketplace I: Effects of Vaping Product Bans

OBJECTIVES

Banning vaping products may have unintended outcomes, such as increased demand for illegal products. This study experimentally examined the effects of a vaping ban and a flavored vaping ban on the probability of purchasing illicit vaping products, and factors affecting purchasing from a hypothetical illegal marketplace.

METHODS

A crowdsourced sample of exclusive cigarette smokers, exclusive e-cigarette users, and frequent dual users (n = 150) completed hypothetical purchasing trials in an Experimental Tobacco Marketplace under three conditions (no ban, vaping ban, and flavored vaping ban). Participants chose to purchase in a hypothetical legal experimental tobacco marketplace (LETM) or illegal experimental tobacco marketplace (IETM). Vaping products were available in each marketplace depending on the condition. Other tobacco products were always available in the LETM. A hypothetical illicit purchase task with five fine amounts assessed the effect of monetary penalties.

RESULTS

Participants from all groups were more likely to purchase from the IETM when product availability in the LETM was more restricted, with e-cigarette users being most affected. The likelihood of purchasing illegal products was systematically decreased as monetary penalties associated with the IETM increased, with e-cigarette users showing greater persistence in defending their illicit purchases.

CONCLUSIONS

Restricting vaping products from the marketplace may shift preference towards purchasing vaping products in the illegal marketplace. Nevertheless, penalties imposed on consumer's behavior might be effective in preventing illicit trade. The IETM is a methodological extension that supports the utility and flexibility of the ETM as a framework for understanding the impact of different tobacco regulatory policies.

IMPLICATIONS

This study suggests that limiting or banning vaping products as a possible strategy to reduce the adverse effects of vaping products could result in some tobacco-users seeking banned products from illegal sources. Monetary fines were shown to reduce illegal purchases. Therefore, policymakers should consider implementing strategies that may mitigate illegal purchases.

An evaluation of fixed and randomized price sequence on the alcohol purchase task

Factors influencing drug consumption can be effectively evaluated in the context of behavioral economic demand. Specifically, hypothetical purchase tasks (HPTs) allow for estimated drug consumption at a range of prices in which drug administration is not ethically or feasibly possible. With the marked increase of HPTs in behavioral research, understanding methodological influences on responding is paramount. One such methodological consideration is the price sequence, which can be presented in a fixed, ascending order or a randomized sequence. This study compared fixed and fully randomized sequence order with college student drinkers using a within-subjects design. Self-reported consumption revealed that despite some small differences between the fixed and random sequences, consumption preferences were highly similar, regardless of presentation order. These results suggest participants are likely not anchoring their responses to the prior price on a fixed-order sequence. We conclude with a discussion on how these findings provide implications for HPTs and future research. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Behavioral economics and safe sex: Examining condom use decisions from a reinforcer pathology framework

Condom use substantially reduces unwanted pregnancies and sexually transmitted infections. While condom availability is a significant public health priority, effects of condom availability constraints remain relatively under-researched. The limited research on condom availability suggests two major barriers to use: (1) effort/costs and (2) delay to access. To date, we are aware of no study that explores both demand for and discounting of condom availability; the focus of this study was to account for condom decisions using a reinforcement pathology framework. This study used a condom purchase task and the Sexual Delay Discounting Task to quantify behavioral economics of condom use. Low sexual discounting was associated with higher willingness to engage unprotected sex. Demand metrics suggest participants indicating abstinence at condom breakpoint were willing to pay nearly double for condoms relative to individuals indicating unprotected sex at breakpoint. Finally, we grouped participants into reinforcement pathology risk groups based on their discounting and demand indices; these groups significantly differed in self-reported number of sexual partners, unprotected sexual partners, and Sexual Desire scores. This study demonstrates the value of behavioral economic approaches to public health concerns, and further underscores the translational benefits of quantitative metrics to shed novel light on risky health decisions.

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.

Integrating Operant and Cognitive Behavioral Economics to Inform Infectious Disease Response: Prevention, Testing, and Vaccination in the COVID-19 Pandemic

The role of human behavior to thwart transmission of infectious diseases like COVID-19 is evident. Yet, many areas of psychological and behavioral science are limited in the ability to mobilize to address exponential spread or provide easily translatable findings for policymakers. Here we describe how integrating methods from operant and cognitive approaches to behavioral economics can provide robust policy relevant data. Adapting well validated methods from behavioral economic discounting and demand frameworks, we evaluate in four crowdsourced samples (total N = 1,366) behavioral mechanisms underlying engagement in preventive health behaviors. We find that people are more likely to social distance when specified activities are framed as high risk, that describing delay until testing (rather than delay until results) increases testing likelihood, and that framing vaccine safety in a positive valence improves vaccine acceptance. These findings collectively emphasize the flexibility of methods from diverse areas of behavioral science for informing public health crisis management.

Quantifying the Impact of Public Perceptions on Vaccine Acceptance Using Behavioral Economics

This study was conducted to evaluate the impact of public perceptions of vaccine safety and efficacy on intent to seek COVID-19 vaccination using hypothetical vaccine acceptance scenarios. The behavioral economic methodology could be used to inform future public health vaccination campaigns designed to influence public perceptions and improve public acceptance of the vaccine. In June 2020, 534 respondents completed online validated behavioral economic procedures adapted to evaluate COVID-19 vaccine demand in relation to a hypothetical development process and efficacy. An exponential demand function was used to describe the proportion of participants accepting the vaccine at each efficacy. Linear mixed effect models evaluated development process and individual characteristic effects on minimum required vaccine efficacy required for vaccine acceptance. The rapid development process scenario increased the rate of decline in acceptance with reductions in efficacy. At 50% efficacy, 68.8% of respondents would seek the standard vaccine, and 58.8% would seek the rapid developed vaccine. Rapid vaccine development increased the minimum required efficacy for vaccine acceptance by over 9 percentage points, γ = 9.36, p < 0.001. Past-3-year flu vaccination, γ = −23.00, p < 0.001, and male respondents, γ = −4.98, p = 0.037, accepted lower efficacy. Respondents reporting greater conspiracy beliefs, γ = 0.39, p < 0.001, and political conservatism, γ = 0.32, p < 0.001, required higher efficacy. Male, γ = −4.43, p = 0.013, and more conservative, γ = −0.09, p = 0.039, respondents showed smaller changes in minimum required efficacy by development process. Information on the vaccine development process, vaccine efficacy, and individual differences impact the proportion of respondents reporting COVID-19 vaccination intentions. Behavioral economics provides an empirical method to estimate vaccine demand to target subpopulations resistant to vaccination.

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).

Concurrent validity of the alcohol purchase task in relation to alcohol involvement: protocol for a systematic review and meta-analysis

INTRODUCTION

Alcohol demand, as measured by an alcohol purchase task (APT), provides a multidimensional assessment of the relative reinforcing efficacy of alcohol. The objective of this meta-analysis is to critically appraise the existing literature on the concurrent validity of the APT by meta-analysing the cross-sectional relationships between indices of the APT (ie, breakpoint, O_max, P_max, elasticity and intensity) and alcohol-related measures. It also aims to examine methodological procedures used to obtain APT indices and individual variables as potential moderators on the assessed estimations.

METHODS AND ANALYSIS

A comprehensive literature search conducted from inception to April 2020 will be conducted in the PubMed, PsycINFO, Web of Science and Scopus databases. Two authors will independently screen and extract data from articles using a predefined protocol search and extraction forms. Disagreements will be resolved through discussion with two additional reviewers. All results will be tabulated, and a random-effect meta-analysis will be conducted. Participants' sex, number of prices and APT methodological procedures will be examined as potential moderators on the observed effect sizes.

ETHICS AND DISSEMINATION

Results of this meta-analysis will characterise the concurrent validity of the APT in the existing literature. Further, the results are anticipated to provide evidence on which index (or indices) is most robustly associated with alcohol use and severity. Ethics approval was not required for this study and the results will be published in a peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

CRD42019137512.

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.