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Abstract

Behavioral economic demand analyses that quantify the relationship between the consumption of a commodity and its price have proven useful in studying the reinforcing efficacy of many commodities, including drugs of abuse. An exponential equation proposed by Hursh and Silberberg (2008) has proven useful in quantifying the dissociable components of demand intensity and demand elasticity, but is limited as an analysis technique by the inability to correctly analyze consumption values of zero. We examined an exponentiated version of this equation that retains all the beneficial features of the original Hursh and Silberberg equation, but can accommodate consumption values of zero and improves its fit to the data. In Experiment 1, we compared the modified equation with the unmodified equation under different treatments of zero values in cigarette consumption data collected online from 272 participants. We found that the unmodified equation produces different results depending on how zeros are treated, while the exponentiated version incorporates zeros into the analysis, accounts for more variance, and is better able to estimate actual unconstrained consumption as reported by participants. In Experiment 2, we simulated 1,000 datasets with demand parameters known a priori and compared the equation fits. Results indicated that the exponentiated equation was better able to replicate the true values from which the test data were simulated. We conclude that an exponentiated version of the Hursh and Silberberg equation provides better fits to the data, is able to fit all consumption values including zero, and more accurately produces true parameter values. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

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... Elasticity (α)w as derivedu sing an exponentiated approach to Hursh &Silberberg's(2008) exponential demand equation (Koffarnus et al., 2015). Calculation of price elasticity wasderivedasfollows: Q = Q 0 × 10 k(e^(-αQ 0 C)-1) , where Q =q uantity consumed, Q 0 =d erivedi ntensity, k = ac onstant across individuals that denotes the range of the dependent variable (grams) in logarithmetic units, α =elasticity or the rate constant determining the rate of decline in logc onsumption based on increases in price, and C =c ost of the commodity (Koffarnus et al., 2015). ...
... Elasticity (α)w as derivedu sing an exponentiated approach to Hursh &Silberberg's(2008) exponential demand equation (Koffarnus et al., 2015). Calculation of price elasticity wasderivedasfollows: Q = Q 0 × 10 k(e^(-αQ 0 C)-1) , where Q =q uantity consumed, Q 0 =d erivedi ntensity, k = ac onstant across individuals that denotes the range of the dependent variable (grams) in logarithmetic units, α =elasticity or the rate constant determining the rate of decline in logc onsumption based on increases in price, and C =c ost of the commodity (Koffarnus et al., 2015). ...
... One possibility is that analytic differences drove the differences in the results. Specifically, the current study used an exponentiated curve equation (Koffarnus et al., 2015), adapted froman earlier single parameter exponential demand curve equation (Hursh &S ilberberg, 2008) to calculate elasticity.I nc ontrast, previous studies that found elasticity loaded on Persistence calculated it using twoparameter models (Hursh et al., 1988) that makeitqualitatively different mathematically. In other words, it maybethat the single-parameter exponential derivation generates an estimate of elasticity that is more closelyr elated to the starto ft he demand curve (intensity) and volume of expenditure (O max )than the point at which it becomes sensitive to price changes (P max )orits terminus, the price at which consumption is zero (breakpoint). ...
Article
Objective: A behavioral economic approach to cannabis misuse emphasizes a crucial role of high drug demand (i.e., reinforcing value), which may be measured using a marijuana purchase task (MPT). The multiple indices from this measure have been associated with cannabis misuse, but somewhat inconsistently, possibly because of task variability across studies. Based on recent qualitative research, the current study implemented an optimized MPT to examine the underlying factor structure and the relationship between cannabis demand and both cannabis misuse and motivation to change. Method: Participants were two independent samples of emerging adults who reported cannabis use and heavy episodic drinking in the last month, one Canadian (n = 396) and the other American (n = 275). Both were assessed using an MPT, the Cannabis Use Disorder Identification Test (CUDIT), the Marijuana Adverse Consequences Questionnaire (MACQ), and readiness to change items. Results: Principal component analyses of the MPT indices revealed the same two-factor latent structure in both samples, interpreted as Amplitude (intensity, Omax, elasticity) and Persistence (breakpoint, Pmax). Regressions revealed that Amplitude was significantly associated with CUDIT and MACQ in both samples. In the Canadian sample, Persistence was also significantly associated with CUDIT and MACQ, and both factors were associated with motivation to change. Conclusions: The optimized MPT generated a two-factor latent structure that was parallel across samples, and the Amplitude factor was consistently associated with cannabis misuse. The current findings indicate the robust relevance of behavioral economic demand for cannabis in relation to cannabis misuse but suggest that links to motivation may be sample-specific.
... $0.05, $0.10, $0.25, $0.50, $1.00, $1.50 $2.00, $3.00, $4.00, $5.00, $6.00, $8.00, $10.00, $15.00, $20.00, $30.00). These data were used to derive several measures of relative reinforcing efficacy (RRE) including: demand intensity (number of drinks consumed when drinks are free), O max (maximum expenditure, or the highest amount spent on alcohol), P max (price where demand becomes elastic, or the price at which O max is reached), breakpoint (price when consumption reaches zero), and essential value (inversely proportional to elasticity; Acuff and Murphy, 2017;Hursh and Silberberg, 2008;Koffarnus et al., 2015). Elasticity is described as the point at which demand becomes sensitive to changes in price, or elastic, and has been traditionally derived using an exponential equation. ...
... Elasticity is described as the point at which demand becomes sensitive to changes in price, or elastic, and has been traditionally derived using an exponential equation. We used the exponentiated demand equation (Koffarnus et al., 2015), which modified the Hursh and Silberberg (2008) equation to allow zero consumption in the curve fit (Koffarnus et al., 2015). The exponentiated demand equation can be written as: ...
... Elasticity is described as the point at which demand becomes sensitive to changes in price, or elastic, and has been traditionally derived using an exponential equation. We used the exponentiated demand equation (Koffarnus et al., 2015), which modified the Hursh and Silberberg (2008) equation to allow zero consumption in the curve fit (Koffarnus et al., 2015). The exponentiated demand equation can be written as: ...
Article
Background Pain may serve as an antecedent for alcohol use, increasing risk for hazardous drinking and associated consequences. Delayed onset muscle soreness (DOMS) induction produces clinically relevant but time-limited musculoskeletal pain. This study was conducted to determine whether DOMS induction on the dominant elbow flexors influenced alcohol demand using the Alcohol Purchase Task (APT). We hypothesized DOMS would increase alcohol demand relative to a sham control. Based on existing studies of pain self-medication, we expected DOMS-related increases in alcohol demand would be greatest in men. Methods Participants (N = 53; 57% women) were randomly assigned to a DOMS (eccentric exercise) or sham condition (concentric exercise). Participants completed the APT pre-exercise and 48 -hs post-exercise. Repeated measures GLM was used to characterize group by sex by time interactions on APT indices, including intensity, breakpoint, essential value (EV), Omax, and Pmax. Results The DOMS procedure significantly increased pain ratings at the elbow flexors. Men had significantly higher demand intensity than women across groups and time points. Significant interactive effects were detected for breakpoint and EV. From pre- to post-test, breakpoint significantly increased in men in the DOMS group. However, breakpoint and EV significantly decreased in women in the DOMS group. Conclusions Increased alcohol demand in men in the DOMS group was consistent with epidemiological data suggesting men are at higher risk for self-medicating pain with alcohol than women. However, decreased demand in women was unexpected. Taken together, results indicate DOMS induction may be a useful means to characterize pain as an antecedent for alcohol use.
... This model has demonstrated wide generality and precision in fitting demand curves (Hursh & Roma, 2013. It has been cited by over 500 publications, and both this model and its derivatives (Koffarnus, Franck, Stein, & Bickel, 2015) have become the standard for assessing operant demand in behavioral research. This report provides a novel implementation of the framework introduced by Hursh and Silberberg (2008), reviews the limitations of the EXPL model, and provides a revised approach that resolves these limitations. ...
... Third, and related to the earlier point, the rate constant  is inherently bound to the span parameter in the EXPL model. That is, the rate of change in consumption is jointly reflected by both  and k (Hursh, 2014 (Kaplan, Foster, et al., 2018;Koffarnus et al., 2015) and others have restricted analyses to overall aggregates across groups (i.e., consumption was averaged across groups and prices). Further, others have omitted the log transformation of consumption altogether, i.e. ...
... That is, the rate of change in consumption is jointly reflected by both  and k (Hursh, 2014 (Kaplan, Foster, et al., 2018;Koffarnus et al., 2015) and others have restricted analyses to overall aggregates across groups (i.e., consumption was averaged across groups and prices). Further, others have omitted the log transformation of consumption altogether, i.e. Koffarnus et al. (2015). Regardless of the approach, few firm guidelines exist for addressing zero consumption values and each of the approaches noted here presents with limitations. ...
Article
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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.
... Omax is calculated as the greatest single expenditure across the demand curve and Pmax was calculated as the price associated with this point of greatest expenditure [50]. Finally, alpha reflects the rate of change in elasticity across the demand curve (fit with an exponentiated function, as described elsewhere [61]). In other words, alpha reflects observed changes in the sensitivity of hypothetical consumption of alcohol as a function of price, with lower values of alpha corresponding to greater demand for alcohol [62]. ...
... In other words, alpha reflects observed changes in the sensitivity of hypothetical consumption of alcohol as a function of price, with lower values of alpha corresponding to greater demand for alcohol [62]. Finally, alpha reflects elasticity across the demand curve (fit with an exponentiated function, as described elsewhere [61]). In the cue-reactivity paradigm, differences scores of all outcomes (AUQ and urge question) were calculated for both the alcohol and neutral condition (i.e., condition minus baseline). ...
... These outcomes were derived using the beezdemand R package [62]. Equations were fit using the exponentiated approach described elsewhere [61]. ...
Article
Preclinical studies support an important role of dopamine D3 receptors (DRD3s) in alcohol use disorder (AUD). In animals, voluntary alcohol consumption increases DRD3 expression, and pharmacological blockade of DRD3s attenuates alcohol self-administration and reinstatement of alcohol seeking. However, these findings have yet to be translated in humans. This study used positron emission tomography (PET) and [11C]-(+)-PHNO to compare receptor levels in several dopamine D2 receptor (DRD2) and DRD3 regions of interest between AUD subjects in early abstinence (n = 17; 6.59 ± 4.14 days of abstinence) and healthy controls (n = 18). We recruited non-treatment seeking subjects meeting DSM-5 criteria for AUD. We examined the relationship between DRD2/3 levels and both alcohol craving and alcohol motivation/wanting, using a cue reactivity procedure and an intravenous alcohol self-administration (IVASA) paradigm, respectively. [11C]-(+)-PHNO binding levels in AUD subjects were significantly lower than binding in HCs when looking at all DRD2/3 ROIs jointly (Wilk’s Λ = .58, F(6,28) =3.33, p = 0.013, η2p = 0.42), however there were no region-specific differences. Binding values demonstrate −12.3% and −16.1% lower [11C]-(+)-PHNO binding in the SMST and SN respectively, though these differences did not withstand Bonferroni corrections. There was a positive association between [11C]-(+)-PHNO binding in the SN (almost exclusively reflective of DRD3) and alpha (lower values reflect higher alcohol demand) in the APT after Bonferroni corrections (r = 0.66, p = 0.0080). This demonstrates that AUD subjects with lower DRD3 levels in the SN exhibit increased demand for alcohol. These results replicate previous findings demonstrating reduced DRD2/3 levels while also supporting a lack of DRD3 upregulation and potential downregulation in early abstinent AUD. Furthermore, the finding that binding in the SN is associated with alcohol demand warrants further examination.
... They enhanced the precision by using the Grey-Markov model, which is a mixture of the GM (1,1) and a Markov model " [1]". Koffarnus et al. (2015) studied the exponential equations proposed by Hursh and Silberberg (2008), which are useful for estimating components for demand density and demand elasticity but are limited by the inability to correctly analyze zero consumption values, where it was concluded that the exponential form of Hursh and Silberberg equations can fit the data best, and fitting with all consumption values including zero, and creates more accurate parameter values " [2]". Halburd (2017) studied that an entropic functional (δ-entropy) was appropriated for the descript ion of dynamical characteristics of ergodic systems on spaces of intermediate volume growth, and introduced the Grigorchuk group as the typical and most famous case for such a space of intermediate growth. ...
... They enhanced the precision by using the Grey-Markov model, which is a mixture of the GM (1,1) and a Markov model " [1]". Koffarnus et al. (2015) studied the exponential equations proposed by Hursh and Silberberg (2008), which are useful for estimating components for demand density and demand elasticity but are limited by the inability to correctly analyze zero consumption values, where it was concluded that the exponential form of Hursh and Silberberg equations can fit the data best, and fitting with all consumption values including zero, and creates more accurate parameter values " [2]". Halburd (2017) studied that an entropic functional (δ-entropy) was appropriated for the descript ion of dynamical characteristics of ergodic systems on spaces of intermediate volume growth, and introduced the Grigorchuk group as the typical and most famous case for such a space of intermediate growth. ...
Article
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Objective: The objective of this paper is to estimate the Modified Exponential Growth model using Maximum Entropy method compact with Fourier Series Residual, and applied this model to review the gap between the actual and expected prices of OPEC basket of crude oil. Method: This paper presented the method of Maximum Entropy using Fourier Series Residual. The first step was generated four samples of size (10, 15, 20, 25) based on modified exponential growth model using the simulation technique. The second step compared the fitting modified exponential growth model using methods of Maximum Entropy (ME) and Modified Maximum Entropy (MME) depending on Mean Absolute Percentage Error (MAPE) and Root Mean Squares Error (RMSE). We applied (ME) and (MME) on real data selected from the prices of crude oil for the period from June 2018 to June 2019. Result: According to each method used and for the four generated models, the result showed that the best method is Modified Maximum Entropy (MME).
... They enhanced the precision by using the Grey-Markov model, which is a mixture of the GM (1,1) and a Markov model " [1]". Koffarnus et al. (2015) studied the exponential equations proposed by Hursh and Silberberg (2008), which are useful for estimating components for demand density and demand elasticity but are limited by the inability to correctly analyze zero consumption values, where it was concluded that the exponential form of Hursh and Silberberg equations can fit the data best, and fitting with all consumption values including zero, and creates more accurate parameter values " [2]". Halburd (2017) studied that an entropic functional (δ-entropy) was appropriated for the descript ion of dynamical characteristics of ergodic systems on spaces of intermediate volume growth, and introduced the Grigorchuk group as the typical and most famous case for such a space of intermediate growth. ...
... They enhanced the precision by using the Grey-Markov model, which is a mixture of the GM (1,1) and a Markov model " [1]". Koffarnus et al. (2015) studied the exponential equations proposed by Hursh and Silberberg (2008), which are useful for estimating components for demand density and demand elasticity but are limited by the inability to correctly analyze zero consumption values, where it was concluded that the exponential form of Hursh and Silberberg equations can fit the data best, and fitting with all consumption values including zero, and creates more accurate parameter values " [2]". Halburd (2017) studied that an entropic functional (δ-entropy) was appropriated for the descript ion of dynamical characteristics of ergodic systems on spaces of intermediate volume growth, and introduced the Grigorchuk group as the typical and most famous case for such a space of intermediate growth. ...
Article
Full-text available
The objective of this paper is to estimate the Modified Exponential Growth model using Maximum Entropy method compact with Fourier Series Residual, and applied this model to review the gap between the actual and expected prices of OPEC basket of crude oil. Method: This paper presented the method of Maximum Entropy using Fourier Series Residual. The first step was generated four samples of size (10, 15, 20, 25) based on modified exponential growth model using the simulation technique. The second step compared the fitting modified exponential growth model using methods of Maximum Entropy $(ME)$ and Modified Maximum Entropy (MME) depending on Mean Absolute Percentage Error (MAPE) and Root Mean Squares Error (RMSE). We applied $(ME)$ and (MME) on real data selected from the prices of crude oil for the period from June 2018 to June 2019. Result: According to each method used and for the four generated models, the result showed that the best method is Modified Maximum Entropy (MME).
... The Kirby Delay Discounting task was selected because temporal (delay) discounting has been widely studied in relation to obesity and overweight status and other impulsivity-related clinical conditions (Vainik et al., 2013(Vainik et al., , 2018Volkow and Baler, 2015;Barlow et al., 2016;Yang et al., 2018). The discount factor k, or the rate at which people discount future rewards, can measured accurately with very brief tasks (Koffarnus et al., 2015). The primary outcome of a delay discounting task is the discount rate, with larger values of k indicating increased impatience and preference for rewards that are available immediately. ...
... The term "risk" has many meanings that have been operationalized in different ways; we refer here to a formal economic notion of variability in the outcomes of monetary prospects. Like delay discounting, risk can be measured accurately with very brief tasks (Koffarnus et al., 2015). Risk variables are considered potential predictors or moderators of behavioral or health outcomes; to our knowledge, they have not been studied as outcomes. ...
Article
Full-text available
Obesity and diabetes are known to be related to cognitive abilities. The Core Neuropsychological Measures for Obesity and Diabetes Trials Project aimed to identify the key cognitive and perceptual domains in which performance can influence treatment outcomes, including predicting, mediating, and moderating treatment outcome and to generate neuropsychological batteries comprised of well-validated, easy-to-administer tests that best measure these key domains. The ultimate goal is to facilitate inclusion of neuropsychological measures in clinical studies and trials so that we can gather more information on potential mediators of obesity and diabetes treatment outcomes. We will present the rationale for the project and three options for the neuropsychological batteries to satisfy varying time and other administration constraints. Future directions are discussed. Preprint version of the document is available at https://osf.io/preprints/nutrixiv/7jygx/.
... Participants were instructed to answer as though all purchased items would be consumed the week they were purchased, that they had to rely upon income/savings they had at the time of the task, that they had no access to substances other than what was offered in the task, and that they should plan to consume all purchased items within the same week and could not stockpile or sell them. Primary outcomes from the hypothetical purchase task were demand intensity or (Q 0 : the estimated consumption of a commodity when the unit price equals zero), demand elasticity (α: the sensitivity of consumption to changes in unit price), output maximum (O max : the maximum output or expenditure at P max ), and price maximum (P max : the price associated with unit elasticity; Koffarnus et al., 2015). ...
Article
Full-text available
Initial experiences with drugs may influence an individual's motivations for continued use. This study evaluated the relationship between subjective effects elicited by an individual's first use of alcohol or cannabis, Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) alcohol use disorder (AUD) or cannabis use disorder (CUD) severity, and behavioral economic demand for alcohol or cannabis. Self-reports of initial subjective effects associated with drugs were analyzed for N = 463 participants whose first substance use was either alcohol or cannabis. The likelihood that a particular subjective effect at the time of first use was associated with current AUD/CUD was assessed using ordinal logistic regression with subjective effects as predictors of DSM-5 severity. Behavioral economic demand was assessed using a hypothetical purchase task in which participants indicated their hypothetical consumption of alcohol or cannabis as a function of price. Significant associations were observed for initial subjective effects elicited by alcohol or cannabis and increased DSM-5 severity: (alcohol) relief (OR = 2.52 [95% CI 1.51-4.25], p = .0005) and (cannabis) energetic (OR = 2.31 [95% CI 3.27-55.5], p = .0004). The mean (± SEM) Pmax value for the alcohol subgroup endorsing relief ($96.22 ± $26.48) was significantly greater than the Pmax value for the alcohol subgroup not endorsing relief ($33.81 ± $12.93), t(237) = 2.276, p = .0237. These results suggest that the initial subjective effects associated with a given substance may predict the development and/or severity of substance misuse and substance use disorders (SUDs). These findings are consistent with anecdotal reports that persons with SUD feel energized by the use of substances whereas persons without SUD do not report experiencing such subjective effects upon first use. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
... We used the following exponentiated equation 36 to derive relevant demand measures: ...
Article
Background Cigarette smoking continues to be a major health concern and remains the leading preventable cause of death in the U.S. Recent efforts have been made to determine the potential health and policy benefits of reducing nicotine in combustible cigarettes. The degree to which changes in blood nicotine relate to measures of the abuse liability of reduced-nicotine cigarettes is unknown. The current study examined the relation between blood nicotine and behavioral economic demand measures of cigarettes differing in nicotine content. Methods Using a within-subject design, participants smoked a single cigarette during each experimental session. Cigarettes included the participant’s usual-brand cigarette and SPECTRUM investigational cigarette differing in nicotine level (mg of nicotine to g of tobacco; 15.8mg/g, 5.2mg/g, 2.4mg/g, 1.3mg/g, and 0.4mg/g). During each session, blood was collected at multiple timepoints and behavioral economic demand was assessed. Nonlinear mixed-effects models were used to estimate differences derived intensity (Q0) and change in elasticity (α). Results Measures related to blood nicotine decreased in an orderly fashion related to nicotine level and significantly predicted change in elasticity (α), but not derived intensity. No differences in demand parameters between the usual brand and 15.8mg/g cigarettes were observed. However, αwas significantly higher (lower valuation) for 0.4mg/g than 15.8mg/g cigarettes. Conclusions The lowest nicotine level (0.4mg/g) corresponded with the lowest abuse liability (α) compared to the full-strength control (15.8mg/g), with the 1.3mg/g level also resulting in low abuse liability. Implications This is the first study examining the relative contributions of nicotine content in cigarettes and blood nicotine levels on the behavioral economic demand abuse liability of cigarettes ranging in nicotine content. Our results suggest blood nicotine and nicotine content both predict behavioral economic demand abuse liability. In addition, our results suggest a nicotine content of 1.3mg/g or lower may be effective at reducing cigarette uptake among first-time (naïve) smokers. Our results largely conform to previous findings suggesting a very low nicotine content cigarette maintains lower abuse liability than full-strength cigarettes.
... All demand indicators were observed, except elasticity which was derived via the exponentiated version of the Hursh and Silberberg (2008) formula to accommodate for zero demand (see Koffarnus et al. 2015: Q = Q0 × 10 k ( e − − α Q0C−1 ). A k value of 2.28 (i.e., obtained by subtracting mean log 10 consumption at the lowest price from mean log 10 consumption at the highest price) was fixed. ...
Article
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RationaleBehavioral economics has shown that single-item demand indicators are promising for capturing crucial aspects of nicotine reinforcement. It is suggested that brief breakpoint measures perform comparably to full-length demand indices in characterizing nicotine dependence; however, there have been no thorough assessments of their validity in clinical settings.Objectives This study aimed to assess the validity and accuracy of a single-item breakpoint in informing on tobacco demand.Methods The sample consisted of 88 treatment-seeking smokers (% males = 70.5%) enrolled in substance use treatment. Participants provided data on smoking characteristics and completed the Fagerström Test for Nicotine Dependence, a single-item breakpoint measure and a 14-item cigarette purchase task (CPT). Hierarchical regressions were performed to compare the predictive capability of a single-item breakpoint and full-length tobacco demand indicators in determining nicotine addiction severity.ResultsThe single-item breakpoint was significantly correlated with all indices stemmed from the CPT and both latent factors (all r values = .250–.368). Neither the brief breakpoint nor the full-length breakpoint significantly predicted nicotine dependence. After controlling for sex and smoking variables, factor 2 [β = .565, p < .001] and its observed variables Omax [β = .279, p = .006], 1/elasticity [β = .340, p = .001], and intensity [β = .551, p < .001], robustly predicted nicotine dependence severity.Conclusions Our findings do not support the validity of single-item breakpoint measures for characterizing nicotine dependence in substance users. In a bid to foster translational research, brief demand measures capturing Omax, intensity, and elasticity should be developed.
... Further advancements came in 2008, when Hursh and Silberberg proposed a new exponential version of the equation, which included a parameter (α) to scale the elasticity of demand (Hursh & Silberberg, 2008). This equation was also an improvement as it permitted description of the slope across the entire demand curve (Kaplan et al., 2019); however, as the equation includes a logarithmic transformation, it necessitates that any zero values be omitted or replaced with arbitrary nonzero values (Jacobs & Bickel, 1999;Koffarnus et al., 2015). Replacing zero values with 0.1 can be problematic as the logarithmic transformation leads to inflation, which may result in inaccurate modeling of demand data (Kaplan et al., 2019). ...
Article
Cannabis use is prevalent and concerns about cannabis misuse are increasing. A reinforcer pathology approach emphasizes the roles of drug reinforcing value (demand) and overvaluation of immediate rewards (delay discounting [DD]) in drug use but has been applied to a lesser extent to cannabis. The present study investigated the independent and interactive roles of these processes in relation to cannabis misuse in a community sample of adult cannabis users (N = 324; 44.8% female; Mage = 33.25). Participants completed a Marijuana Purchase Task (MPT), the Monetary Choice Questionnaire (MCQ), and the Cannabis Use Disorder Identification Test-Revised (CUDIT-R) to assess demand, DD, and cannabis misuse, respectively. Zero-order correlations revealed significant associations between CUDIT-R scores and both the demand indices (|rs | = .21-.56, p < .01-.001) and DD (r = .21, p < .01). In multivariate analyses, lower elasticity (i.e., price insensitivity) was robustly associated with higher CUDIT-R scores, while other demand indicators did not explain additional unique variance. However, as elasticity, intensity, and Omax exhibited robust zero-order intercorrelations, shared variance appeared to drive the association. An interactive relationship between elasticity and DD was not significant. These findings indicate that cannabis misuse is associated with both cannabis demand, particularly as measured by insensitivity to escalating costs, and immediate reward orientation, but the relationship was not synergistic. These results support a reinforcer pathology approach to cannabis misuse and, although causality cannot be inferred cross-sectionally, suggest that evaluating the longitudinal significance of these indicators is warranted. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
... On HPTs, participants indicate the amount of a drug they would purchase, or the probability of purchase, at a series of increasing prices (Roma et al., 2016). There are multiple models that can then be used to fit the resulting demand curves (Hursh and Silberberg, 2008;Koffarnus et al., 2015;Gilroy et al., 2020) to provide demand indices such as Q 0 , demand at a price of zero, and α, the rate of change in the demand curve's slope. ...
Article
Background Behavioral economics provides a framework in which to understand choice and motivation in the field of substance use disorders. Hypothetical purchase tasks (HPT), which indicate the amount or probability of purchasing substances at different prices, have been suggested as a clinical tool that can help predict future substance use and identify targets for intervention. Methods Hypothetical demand for heroin, cocaine, and benzodiazepines was assessed at baseline and after six-months in 52 opioid-agonist treatment patients. The results were analyzed using a novel exponential demand equation (normalized zero-bounded exponential model [ZBEn]) that uses a log-like transform that accommodates zero consumption values. Results Demand for these drugs was well described by the ZBEn model. After six months, demand intensity for heroin was decreased and demand metrics for cocaine and benzodiazepines increased. Multiple demand curve indices at baseline predicted the percentage of drug-positive urinalysis results at follow-up, even after controlling for covariates. Additionally, participants were divided into High and Low baseline demand groups for each drug based on demand indices. Participants with High demand at baseline for 8 out of 9 groups had significantly more drug-positive urine samples in the subsequent 6-month period. Conclusions This report provides evidence that demand assessment is predictive of future substance use and could help guide treatment planning at intake. These results also demonstrated that the ZBEn model provides good fits to consumption data and allows for sensitive statistical analyses.
... Intensity, O max , P max , and breakpoint were generated using an observed values approach. Elasticity was estimated using an exponentiated demand curve Equation 1 proposed by Koffarnus et al. (2015). ...
Article
Objective: The purpose of this secondary analysis is to analyze whether both of the processes of the reinforcer pathology model (delay discounting and demand) are predictors of relapse up to 12-month follow-up in a sample of abstinent smokers who received a smoking cessation treatment. Method: Participants were 202 abstinent smokers who completed the delay discounting task and the cigarette purchase task. In order to analyze the smoking relapse predictors and the impact of time to relapse, Kaplan-Meier curves, log-rank test, and Cox regression analysis were carried out. Results: Fewer years of regular smoking (HR = .79, p = .014), as well as higher delay discounting (HR AUClogd = .80, p = .019) and intensity of demand (HR = 1.26, p = .019) were associated with a higher likelihood of smoking relapse. These variables were associated with a faster relapse. Conclusions: High delay discounting and intensity of demand were associated with a higher risk of relapse after quitting smoking. These findings highlight the importance of adapting treatment strategies for these two variables (delay discounting and cigarette demand), which might confer protective risk against smoking relapse. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
... For example, the equation can distinguish between a subject's response output for reward when costs are near-zero (Q 0 ) and the extent to which a subject will defend its levels of reward consumption as costs increases (elasticity or α). Importantly, task and equation variants continue to be developed to better model economic demand data (Koffarnus, Franck, Stein, & Bickel, 2015). Nevertheless, a close conceptual correspondence already has been successfully demonstrated for this quantitative framework in research with laboratory animals and humans (Strickland & Lacy, 2020) to examine motivation to respond for, and associated reinforcing effectiveness of, a variety of commonly abused drugs, including cocaine (O'Connor, Aston-Jones, & James, 2021), ethanol (Kim & Kearns, 2019), fentanyl (McConnell et al., 2021), and nicotine (Powell, Beckmann, Marusich, & Gipson, 2020), to name just a few recent examples. ...
Chapter
Behavioral pharmacology has been aided significantly by the development of innovative cognitive tasks designed to examine complex behavioral processes in laboratory animals. Performance outcomes under these conditions have provided key metrics of drug action which serve to supplement traditional in vivo assays of physiologic and behavioral effects of psychoactive drugs. This chapter provides a primer of cognitive tasks designed to assay different aspects of complex behavior, including learning, cognitive flexibility, memory, attention, motivation, and impulsivity. Both capstone studies and recent publications are highlighted throughout to illustrate task value for two distinct but often interconnected translational strategies. First, task performance in laboratory animals can be utilized to elucidate how drugs of abuse affect complex behavioral processes. Here, the expectation is that adverse effects on such processes will have predictive relevance to consequences that will be experienced by humans. Second, these same task outcomes can be used to evaluate candidate therapeutics. In this case, the extent to which drug doses with medicinal value perturb task performance can contribute critical information for a more complete safety profile appraisal and advance the process of medications development. Methodological and theoretical considerations are discussed and include an emphasis on determining selectivity in drug action on complex behavioral processes.
... 2 Reanalysis using the Koffarnus et al. (2015) exponentiated demand equation without replacement of zero consumption values yielded the same outcomes with respect to percent change in α as a function of age cohort. Given that individual-level values of the range parameter (k) were below 1.8 for more than half of the participants, we chose to report the findings using Equation 1 (Hursh & Silberberg, 2008). ...
Article
Background College students affiliated with fraternity and sorority, or “Greek” life represent a known high-risk group for alcohol consumption and related consequences, but little is known about demand for alcohol in this population. The current study examined behavioral economic demand for alcohol in a sample of Greek life-affiliated undergraduate students using the alcohol purchase task (APT) and a novel variation of the APT that included a fixed-price, nonalcoholic alternative (APT Choice). Methods Participants (n = 229) completed the APT, APT Choice, Alcohol Use Disorders Identification Test (AUDIT), and Daily Drinking Questionnaire (DDQ). Group demand indices were calculated for the entire sample and then separately for participants who met or did not meet the legal drinking age (21+ or underage, respectively). Independent-sample t tests assessed whether there were any significant differences between the two age cohorts in the percent change in each behavioral economic index from the APT to APT Choice. Tests of correlation evaluated the construct validity of the demand indices from both hypothetical purchase tasks. Results Descriptive statistics on alcohol use in this Greek-affiliated sample revealed “hazardous” drinking scores, with AUDIT-C scores exceeding the threshold of alcohol misuse. These measures were significantly correlated with demand indices from both APT conditions, and demand was inversely related to price; however, demand for alcohol was reduced when a nonalcoholic alternative was available. Both age cohorts reported a reduction in BP1 (highest price of nonzero consumption) and an increase in α (rate of change in elasticity), but these changes were significantly greater among underage participants. Conclusions Although Greek life-affiliated students demonstrate high demand for alcohol, the concurrent availability of a nonalcoholic alternative reduces alcohol demand, particularly for underage students. These findings suggest that nonalcoholic options may enhance the effectiveness of increasing alcohol prices to reduce alcohol consumption among students at higher risk for alcohol use.
... have flourished over the past decade. This growth stems from the development [1] and refinement [2] of rapid assessment methods with key advances in the quantitative methods used to evaluate demand data [3,4]. These demand methods are used to characterize the consumption of a good across a range of prices or constraints on consumption, a goal of behavioral scientists dating back to at least the 1970s in the cardinal work on demand conducted by Howard Rachlin [5]. ...
... α was derived by fitting the consumption data to the exponentiated demand equation (1) in GraphPad Prism 8 (La Jolla, California) using the exponentiated demand analyses template. 32,33 The equation states: ...
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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), P max (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 P max, and 18–24 year olds displayed higher breakpoints. Participants with low income displayed higher intensity, and lower P max 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.
... The cross-price demand function measures the relationship between the fixed price commodity (Sacc/EtOH) and the changing price commodity (nicotine), assessed by the interaction constant I. Positive I values indicate a complementary relationship between the two commodities, while negative I values indicate a substitutionary relationship (Hursh and Roma, 2016). The nicotine ownprice demand curve was fit by exponentiating the original Hursh and Silberberg demand equation (Hursh and Roma, 2013) as proposed by Koffarnus et al. (2015), that provides better fits for data sets that include zeros: ...
Article
Background Preclinical models simulating adolescent substance use leading to increased vulnerability for substance use disorders in adulthood are needed. Here, we utilized a model of alcohol and nicotine co-use to assess adult addiction vulnerability following adolescent alcohol exposure. Methods: In Experiment 1, adolescent (PND30) male and female Sprague-Dawley rats received 25% ethanol (EtOH) or a control solution via oral gavage every 8 hours, for 2 days. In young adulthood, animals were tested with a 2-bottle choice between H20 and 15% EtOH or 0.2% saccharin/15% EtOH, followed by co-use of oral Sacc/EtOH and operant-based i.v. nicotine (0.03 mg/kg/infusion) self-administration. In Experiment 2, adolescents received control gavage, EtOH gavage, or no-gavage, and were tested in young adulthood in a 2-bottle choice between H20 and 15% EtOH, Sacc/EtOH, or 0.2% saccharin. Results In Experiment 1, the adolescent EtOH gavage reduced adult EtOH consumption in the 2-bottle choice, but not during the co-use phase. During co-use, Sacc/EtOH served as an economic substitute for nicotine. In Experiment 2, the control gavage increased adult EtOH drinking relative to the no-gavage control group, an effect that was mitigated in the EtOH gavage group. In both experiments, treatment group differences in EtOH consumption were largely driven by males. Conclusions EtOH administration via oral gavage in adolescence decreased EtOH consumption in adulthood without affecting EtOH and nicotine co-use. Inclusion of a no-gavage control in Experiment 2 revealed that the gavage procedure increased adult EtOH intake and that including EtOH in the gavage buffered against the effect.
... and round-trip time cost to purchase each 0.1-oz (UP: 3-120 min). To maximize demand curve fit (in log/log space) when including zero consumption values and to use all UP/consumption pairwise data, a fixed value of 10 was added to all raw consumption data (Koffarnus et al., 2015) so log 10 of zero values would equal 1. Demand curves were fit for each subject in GraphPad Prism v.6 using the formula (Winger and Hursh, 1995): Y = log(L) * exp (-a * X ); where L=intensity, a=elasticity, X=unit price, and Y=consumption. ...
Article
Background Despite medicalization and legalization of marijuana use, factors influencing demand for marijuana among persons living with HIV (PLWH) are incompletely understood. This knowledge gap undermines effective clinical management and policies. This study used demand curve simulation methods to address these issues. Methods Marijuana-using PLWH (N = 119) completed experimental tasks to simulate amount of marijuana purchasing/use across different costs (money or time), and likelihood of reselling marijuana or marijuana therapeutic-use registration card in relation to profits. Additional simulations assessed purchasing of marijuana relative to other drug and non-drug goods. Results Simulated marijuana use decreased as money and time costs increased. Consumption was greater for participants with more severe Cannabis Use Disorder (CUD) and anxiety, intermediate pain levels, and past 90-day opioid use. Whereas few participants chose to sell their registration card, marijuana resale (diversion) steeply increased with profit. Likelihood of seeking marijuana therapeutic-use certification decreased in relation to registration card money cost, having to visit more physicians to get a signature, and delay to receiving the card, and increased with duration of certification. Participants who reported recent opioid use were more likely to seek certification. Consumption of several commodities assessed was independent of marijuana. Conclusions Simulated marijuana use was related to participants’ clinical profile (CUD, anxiety and pain symptoms, recent opioid use), and unrelated to purchasing other goods. Likelihood of seeking marijuana therapeutic-use registration was affected by several types of costs and recent opioid use. Participants were unlikely to divert registration cards. We discuss clinical and policy implications of these findings.
... Because in-vivo laboratory studies using state-based APTs are qualitatively different from trait-based assessments indices [10,11,24,25], experimental studies using state-based APT versions were excluded. Also, data on elasticity of demand were only included when calculated through the two most widely used formulae [26,27]. When the same sample was used in more than one study, the study providing more information and a higher number of participants was retained. ...
Article
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, the Egger's and the 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), Omax (i.e., maximum expenditure), Pmax (i.e., price associated to Omax), and breakpoint (i.e., price at which consumption ceases). Results All alcohol demand indices were significantly associated with all alcohol‐related outcomes (|r|= .132 ‐ .494), except Pmax, which was significantly associated with alcohol‐related problems only (r = .064). The greatest associations were evinced between intensity in relation to alcohol use, hazardous drinking and heavy drinking, and between Omax 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 Omax are the most relevant indices to account for alcohol involvement.
... In contrast, elasticity (i.e., sensitivity of consumption to increases in costs) was derived using both mean and individual consumption data in GraphPad Prism (v8, GraphPad Inc.). Nonlinear regression was used to fit and derive parameters from an exponentiated demand equation (Koffarnus et al. 2015): Y = Q 0 * 10 k(e −aQ0C −1) , where Y = quantity consumed at a given price, Q 0 = quantity consumed at zero price, k = a constant reflecting the range of consumption values across individuals, α = demand elasticity parameter reflecting the rate of consumption decline based on increases in price, and C = the cost of the alcohol. The k parameter was defined as 4 based on the best fit to the mean baseline demand (R 2 = 0.99). ...
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Rationale Pharmacotherapies are an important clinical strategy for treating alcohol use disorder and an understanding of their functional mechanisms can inform optimal use. Behavioral economics provides a translational platform that may advance our understanding of the motivational impacts of pharmacotherapies. Objectives This secondary analysis study examined the effect of topiramate, a promising pharmacotherapy for treating alcohol use disorder, on two behavioral economic domains, the reinforcing value of alcohol (alcohol demand and alcohol-specific monetary expenditures) and delayed reward discounting (preference for smaller immediate rewards over larger delayed rewards). Methods A double-blind randomized placebo-controlled study (n = 99) was conducted with non-treatment seeking heavy drinkers, comparing topiramate (target dose of 200 mg/day titrated for 3 weeks and remained at the target dose for 2 weeks) to matched placebo. Results We found that compared to placebo, topiramate reduced the reinforcing value of alcohol, as shown by a reduction in two alcohol demand indices (intensity and Omax), money spent per week on alcohol and an almost a 50% increase in days without expenditures on alcohol from baseline. Directionally consistent patterns were also present for breakpoint and elasticity (ps = .08). No significant effects were found for delayed reward discounting. Conclusions This study provides evidence that topiramate reduces alcohol’s reinforcing value as measured by alcohol demand and alcohol expenditure. More broadly, these findings support the utility of behavioral economics for understanding how medications reduce alcohol use.
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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.
Article
E-cigarette use is prohibited in most smoke-free environments. The effect of this policy on tobacco consumption could be examined using the Experimental Tobacco Marketplace (ETM). The ETM allows observation of policy on smokers' purchasing behavior under conditions that simulate "real-world" circumstances. A within-subject design was used to evaluate the effect of workplace policy (Vaping Allowed vs. Not Allowed) and nicotine concentration (24 mg/mL vs. 0 mg/mL) on tobacco product consumption. Participants (n = 31) completed one sampling and two ETM/workplace sessions per week for 2 weeks. During the sampling session, participants were given an e-cigarette with a 2-day supply of a commercially available e-liquid of their preferred flavor. Before purchasing, participants were informed whether e-cigarette use was permitted. During the four ETM sessions, participants purchased for the following 24 hr, including the 4-hr work shift that started immediately after buying products in the ETM. The workplace session consisted of data entry tasks in a mock office environment. Participants could use any purchased tobacco products during two 15-min breaks. Condition order was counterbalanced. The results show that permitting E-cigarette use in the workplace increased e-liquid purchase on average, but nicotine concentration had no effect on e-liquid demand. Cigarette demand was unaltered across conditions. The present study suggests that allowing e-cigarette use in the workplace would increase demand for e-liquid regardless of nicotine strength. However, it would not change conventional cigarette demand. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Article
Objective: Behavioral economic (BE) approaches to understanding and reducing risky drinking among college students are well established, but little is known about the generalizability of prior findings to peers who currently are not traditional college students and are more difficult to reach for assessment and intervention. This cross-sectional survey investigated whether drinking practices and negative consequences were associated with greater alcohol demand, alcohol reward value, and delay discounting in this target population. Method: Community-dwelling emerging adult drinkers aged 21 to 29 (N = 357) were recruited using Respondent-Driven Sampling adapted to a digital platform (Mage = 23.6 years, 64% women). Peers recruited peers in an iterative fashion. Participants completed a web-based survey of drinking practices, negative alcohol-related consequences, and BE measures of alcohol demand, alcohol reward value, and delay discounting. Results: Regression analyses supported the study hypotheses. Higher alcohol demand (intensity and elasticity) predicted higher drinks per drinking day, more past-month drinking days, and more negative consequences. Higher alcohol reward value (discretionary alcohol spending and alcohol-involved activities) and stronger preference for sooner smaller versus later larger rewards predicted select drinking risk variables in the hypothesized direction (p < .05). Conclusions: BE risk characteristics were generalized to community-dwelling emerging adult risky drinkers, with the most consistent associations found between alcohol demand and drinking risk measures. The findings lay a foundation for extending successful BE interventions with college drinkers to this underserved population. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Article
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) 2021 APA, all rights reserved).
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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.
Article
Background Adolescence is a period of psychological and neural development in which harms associated with cannabis use may be heightened. We hypothesised that adolescent who use cannabis (adolescentsWUC) would have steeper delay discounting (preference for immediate over future rewards) and greater demand (relative valuation) for cannabis than adults who use cannabis (adultsWUC). Methods This cross-sectional study, part of the ‘CannTeen’ project, compared adultsWUC (n=71, 26-29 years old) and adolescentsWUC (n=76, 16-17 years old), and gender- and age-matched adolescent (n=63) and adult (n=64) controls. AdolescentsWUC and adultsWUC used cannabis 1-7 days/week and were matched on cannabis use frequency (4 days/week). The Monetary Choice Questionnaire assessed delay discounting. A modified Marijuana Purchase Task (MPT) assessed cannabis demand in adolescentsWUC and adultsWUC. The MPT yielded five indices: intensity (amount of cannabis used at zero cost), Omax (total peak expenditure), Pmax (price at peak expenditure), breakpoint (cost at which cannabis demand is suppressed to zero) and elasticity (degree to which cannabis use decreases with increasing price). Analyses were adjusted for covariates of gender, socioeconomic status, other illicit drug use. Results Both adolescentsWUC and adultsWUC had steeper delay discounting than controls (F(1,254)=9.13, p=0.003, ηp²=0.04), with no significant age effect or interaction. AdolescentsWUC showed higher intensity (F(1,138)=9.76, p=0.002, ηp²=0.07) and lower elasticity (F(1,138)=15.25, p<0.001, ηp²=0.10) than adultsWUC. There were no significant differences in Pmax, Omax or breakpoint. Conclusion Individuals who use cannabis prefer immediate rewards more than controls. AdolescentsWUC, compared to adultsWUC, may be in a high-risk category with diminished sensitivity to cannabis price increases and a greater consumption of cannabis when it is free.
Article
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.
Article
Background Anger and anger‐related traits have been related to alcohol use in both cross‐sectional and prospective studies. However, only a small number of studies have experimentally manipulated anger to examine whether the manipulation of anger influences alcohol craving or the relative reinforcing value of alcohol. Methods Participants (N = 231) recruited through Amazon’s MTurk were randomly assigned to a provocation condition or a neutral condition prior to completing both the Alcohol Purchase Task and a self‐report measure of alcohol craving. Linear regression analyses were conducted to examine the effects of the anger induction, trait hostility, frequency of alcohol use in the past month, and relevant demographic characteristics (gender, age, income) on alcohol craving and indices of alcohol demand. Results Participants assigned to the provocation condition had greater PMax (B = 0.17, p = 0.012) and breakpoint (B = 0.18, p = 0.006) values, less elastic demand (B = −0.15, p = 0.020), and lower drinking intensity (B = −0.14, p = 0.025) than participants assigned to the neutral condition. Trait hostility was positively related to OMax (B = 0.22, p = 0.001), intensity of demand (B = 0.27, p < 0.001), and subjective alcohol craving posttask (B = 0.32, p < 0.001), but did not moderate the relationship between condition and outcomes. Conclusions Although most persistence indices of alcohol demand were sensitive to the anger induction, we did not observe higher scores on amplitude indices or subjective craving in the provocation condition relative to the neutral condition. Further investigation into the role which anger plays in alcohol use is warranted.
Article
Background Behavioral economic theory predicts decisions to drink are cost benefit analyses, and heavy episodic drinking occurs when benefits outweigh costs. Social interaction is a known benefit associated with alcohol use. Although heavy drinking is typically considered more likely during more social drinking events, people who drink heavily in isolation tend to report greater severity of use. This study explicitly disaggregates between-person and within-person effects of sociality on heavy episodic drinking and examines behavioral economic moderators. Methods We used day-level survey data over an 18-week period in a community adult sample recruited through crowdsourcing (mTurk; N = 223). Behavioral economic indices were examined to determine if macro person-level variables (alcohol demand, delay discounting, proportionate alcohol-related reinforcement [R-ratio]) interact with event-level social context to predict heavy drinking episodes. Results Mixed effect models indicated significant between-person and within-person social context associations. Specifically, people with a higher proportion of total drinking occasions in social contexts had decreased odds of heavy drinking, whereas being in a social context for a specific drinking occasion was associated with increased odds of heavy drinking. Person-level R-Ratio, demand elasticity, and breakpoint variables interacted with social context to predict heavy episodic drinking, such that the event-level social context association was stronger when R-Ratios, alcohol price insensitivity, and demand breakpoints were high. Conclusions These results demonstrate an ecological fallacy, in which the size and direction of effects were divergent at different levels of analysis, and highlight the potential for merging behavioral economic variables with proximal contextual effects to predict heavy drinking.
Article
Background Although heavy alcohol consumption and maladaptive eating behaviors have been shown to co‐occur among college students, less is known about the co‐occurrence of these behaviors in a more diverse community‐dwelling, emerging adult sample. The purpose of this study was to: (i) identify classes of emerging adults by their reported alcohol consumption patterns, food addiction symptoms, and body mass index; and (ii) determine whether these classes differed on indices of behavioral economic reinforcer pathology (e.g., environmental reward deprivation, impulsivity, alcohol demand). Method Emerging adult participants were recruited as part of a study on risky alcohol use (n = 602; 47% white, 41.5% Black; mean age = 22.63, SD = 1.03). Participants completed questionnaires on alcohol and food‐related risk factors and underwent anthropometric assessment. Results Latent profile analysis suggested a four‐profile solution: a moderate alcohol severity, overweight profile (Profile 1; n = 424, 70.4%), a moderate alcohol severity, moderate food addiction + obese profile (Profile 2; n = 93, 15.4%), a high alcohol severity, high food addiction + obese profile (Profile 3; n = 44, 7.3%), and a high alcohol severity, overweight profile (Profile 4; n = 41, 6.8%). Individuals in Profile 1 reported significantly lower levels of environmental reward deprivation than either Profile 2 or 3, and participants in Profile 3 reported significantly higher environmental reward deprivation than those in Profile 4 (p < 0.001). Profile 4 demonstrated significantly higher alcohol demand intensity and Omax and lower demand elasticity than Profile 1, Profile 2, or Profile 3. Profile 4 also demonstrated significantly greater proportionate substance‐related reinforcement than Profile 1 (p < 0.001) and Profile 2 (p = 0.004). Conclusion Maladaptive eating patterns and alcohol consumption may share common risk factors for reinforcer pathology including environmental reward deprivation, impulsivity, and elevated alcohol demand.
Article
Introduction Cigarette demand, or relative value, can be assessed via analysis of performance on a hypothetical behavioral economic cigarette purchase task (CPT). Substance purchase tasks are highly amenable to manipulation, namely, external stimuli, instructional changes, or acute stressors. In this regard, the current secondary analysis evaluates the role a novel, computerized stress induction paradigm, the Contextual-Frustration Intolerance Typing Task (C-FiTT), plays in eliciting varying levels of stress and resulting demand. Method Daily smokers (n = 484) completed a computerized internet-based distress provocation task wherein they were randomly assigned to one of five distress conditions: combination of task difficulty (low or high difficulty) with neutral or withdrawal cues, and a neutral control group. Tobacco demand was assessed immediately following the distress task using the hypothetical CPT. Results The C-FiTT distress-induction task significantly increased key cigarette demand indices, including price at maximum expenditure (Pmax) and first price where consumption was suppressed to zero (breakpoint). Moreover, demand increased with severity of C-FiTT condition, with the high-difficulty condition resulting in significantly higher breakpoint and Pmax, compared to other conditions. C-FiTT condition was not related to a significant increase in Omax, intensity, or elasticity. Discussion The novel C-FiTT paradigm produced comparable effects on tobacco demand relative to in vivo withdrawal induction, indicating that C-FiTT is a viable procedure by which to influence demand. Reduction of internal and external stressors may be effective in lowering motivation for tobacco. These results highlight the importance of state distress in tobacco demand, and offer a potential avenue for intervention.
Article
Problematic internet use (PIU) is of increasing concern to society and is correlated with negative behavioral and health issues. Human laboratory procedures to assess economic demand for internet use may be useful in translational efforts to better understand PIU and to assess potential treatments. One such procedure involves hypothetical purchases of access to internet use. Little is known about how such hypothetical purchases relate to actual behavior. In the current study, we assessed the correlation between measures of demand via an internet purchase task (IPT) and breakpoints on a progressive ratio (PR) schedule (n = 52). Participants responded on a computer-based task on an escalating work requirement that resulted in 30-s of access to their internet-enabled smartphone. We found a statistically significant correlation between demand intensity (Qo) and total responses (r(29) = .83, p < .001), and between Omax (maximum response expenditure) and total responses (r(29) = .34, p = .03) on the PR schedule. We did not find a relationship between measures of demand elasticity and measures of PR behavior. Because Omax is reflective of both demand and elasticity and Q0 is primarily influenced by demand alone, the results of this study indicate that demand intensity of internet use may be a better predictor of real-world behavior than other measures of demand. These results suggest that demand intensity for internet access may be a valuable proxy for behavior-based measures in the assessment and treatment of PIU.
Article
Aims The Experimental Medicine Approach offers a unique perspective to determine clinical behavior change by engaging a target underlying the cause of a disorder. The present work engaged a novel target of addiction, Reinforcer Pathology, in two studies to test changes in behavior among individuals with cocaine use disorder. Methods In Study 1, n = 44 participants engaged the temporal window with episodic future thinking (EFT), a positive prospection exercise. Changes in temporal view and cocaine valuation were tested using delay discounting and behavioral economic demand, respectively. Additionally, a computational model assessed the relative reliance on the near- and far-sighted systems during EFT. In Study 2, n = 71 engaged the temporal window with a negatively-valenced hurricane scenario to test the opposite effects on window length and cocaine valuation. Results Results demonstrated systematic and symmetrical engagement of the behavioral target. Study 1 robustly replicated previous work, wherein EFT lengthened the temporal window and decreased cocaine valuation. Moreover, EFT increased the weighting of the modeled far-sighted system, increasing the relative impact of long-term discounting decisions. Study 2 produced opposite outcomes, shortened temporal window and increased cocaine valuation. Conclusions This approximately equal and opposite reaction to the manipulations supports reinforcer pathology theory and implicates the temporal window over which rewards are valued as a target to be pushed and pulled to produce clinically meaningful behavior change. Using the Experimental Medicine Approach as a guide, future work should identify new potential interventions to engage reinforcer pathology and use the clinically relevant outcomes as a litmus test for mechanism.
Article
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.
Article
Research has demonstrated that repeated engagement in low-effort behaviors that are associated with immediate reward, such as Internet use, can result in a pathological reinforcement process in which the behavior is increasingly selected over other activities due, in part, to a low availability of alternative activities and to a strong preference for immediate rather than delayed rewards (delay discounting). However, this reinforcer pathology model has not been generalized to other Internet-related behaviors, such as online gaming or smartphone use. Given the widespread availability of these technologies, it is also important to examine whether reinforcer pathology of Internet-related behaviors is culturally universal or culture-specific. The current study examines relations between behavioral economic constructs (Internet demand, delay discounting, and alternative reinforcement) and Internet-related addictive behaviors (harmful Internet use, smartphone use, online gaming, and Internet sexual behavior) in a cross-sectional sample of college students (N = 1,406) from six different countries (Argentina, Australia, India, Malaysia, the United Kingdom, and the United States). Using structural equation modeling, Internet demand was associated with harmful Internet use, smartphone use, and online gaming; delay discounting was associated with harmful smartphone use; and alternative reinforcement was associated with harmful Internet and smartphone use. The models were partially invariant across countries. However, mean levels of behavioral economic variables differed across countries, country-level gross domestic product, person-level income, and sex at birth. Results support behavioral economic theory and highlight the importance of considering both individual and country-level sociocultural contextual factors in models for understanding harmful engagement with Internet-related behaviors. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Article
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, 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.
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Here's a link to the full text via Springer: https://rdcu.be/cpmmm 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 paper 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.
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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).
Cigarette smokers show excessive delay discounting (devaluation of delayed rewards), which may contribute to tobacco use disorder. Episodic future thinking (EFT), or mental simulation of future events, has been shown to reduce both delay discounting and laboratory smoking behavior. Traditionally, EFT involves vividly imagining positive future events. In this preliminary investigation, we examined the effects of EFT specifically about smoking-related illness (SRI) on delay discounting, cigarette craving, and behavioral economic demand for cigarettes. In a 2 (episodic thinking) × 2 (smoking-related illness) factorial design, we randomly assigned smokers from Amazon Mechanical Turk to one of two EFT groups: EFT alone or EFT + SRI; or one of two episodic “recent” thinking (ERT) control groups: ERT alone or ERT + SRI. Both EFT groups generated and imagined positive future events, while both ERT groups imagined real events from the recent past. Both EFT + SRI and ERT + SRI groups imagined these events while also experiencing SRI symptoms. Participants then completed assessments of delay discounting, cigarette craving, and measures of cigarette demand. We observed significant main effects on delay discounting of both EFT (reduced discounting) and SRI (increased discounting), as well as significant main effects of both EFT and SRI on cigarette craving (in both cases, reduced craving). No significant main effect of EFT was observed on cigarette demand measures, although we observed a main effect of SRI on quantity of demand when cigarettes were free (Q0) (reduced demand). In all analyses, we observed no significant EFT × SRT interactions, indicating that these variables operate independently of one another. These methods may be adapted for use in clinical treatment to aid in smoking cessation interventions.
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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.
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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.
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Hypothetical purchase tasks are a widely used tool to determine the reinforcing value of commodities, especially commodities which are difficult to deliver experimentally. Amazon Mechanical Turk users (N = 375) completed two novel hypothetical purchase tasks (quantity of purchase and probability of purchase) and other measures to estimate how much an individual values the opportunity to exercise in a gym. We examined correlations between demand indices generated by each task and measures related to physical activity. In addition, we compared rates of systematic and nonsystematic responding between the two tasks. Exploratory analyses of demand indices and measures of physical activity suggest initial evidence of construct validity for each task. When accounting for an order effect, the probability of purchase task generated significantly lower rates of nonsystematic responding compared to the quantity of purchase task (2.87% vs. 14.6%, respectively). We discuss how these results may inform improved construction of future hypothetical purchase tasks and implications for using likelihood and quantity purchase tasks.
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Rationale Reinforcer pathology (RP) is a theoretical model based on two processes: delay discounting (DD) and drug demand. Given that RP has been shown to have a predictive value on smoking behaviors, several studies have explored which interventions can reduce RP. Consistent with the RP framework, episodic future thinking (EFT) has shown effects on treatment outcomes and RP processes. The vast majority of studies that assess the effects of EFT on RP consist of experimental studies, and no previous research has tested these effects in a clinical sample of smokers. Objectives The primary aim of this study was to assess the effects of EFT on RP throughout the course of a smoking cessation intervention in smokers with substance use disorders (SUDs). Methods Participants were randomized to cognitive behavior therapy (CBT) + EFT (n = 39) or CBT + EFT + contingency management (n = 33). Cotinine, frequency of EFT practices, cigarette purchase task (CPT), and DD were evaluated in treatment sessions. Mixed-effects model repeated measures analysis was used to explore DD and CPT in-treatment changes as a function of EFT practices and cotinine levels. Results Greater practice of the EFT component significantly reduced cigarette demand (p < .020) as well as DD (p = .003). Additionally, a greater reduction in cotinine levels coupled with greater EFT practice led to a greater decrease in cigarette demand (p < .014). Conclusions EFT reduced the two facets of RP in treatment-seeking smokers with SUDs.
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Compulsive eating is an overlapping construct with binge eating and shares many characteristics with substance abuse disorders. Compulsive eating may impact millions of Americans; presenting in some cases of binge eating disorders, overweight/obesity, and among individuals who have not yet been diagnosed with a recognized eating disorder. To study the behavioral and neurobiological underpinnings of compulsive eating, we employ a published rodent model using cyclic intermittent access to a palatable diet to develop a self-imposed binge-withdrawal cycle. Here, we further validated this model of compulsive eating in female Wistar rats, through the lens of behavioral economic analyses, and observed heightened demand intensity, inelasticity and essential value as well as increased food-seeking during extinction. Using electrophysiological recordings in the anterior insular cortex, a region previously implicated in modulating compulsive-like eating in intermittent access models, we observed functional adaptations of pyramidal neurons. Within the same neurons, application of leptin led to further functional adaptations, suggesting a previously understudied, extrahypothalamic role of leptin in modulating feeding-related cortical circuits. Collectively, the findings suggest that leptin may modulate food-related motivation or decision-making via a plastic cortical circuit that is influenced by intermitted access to a preferred diet. These findings warrant further study for whether the behavioral economics of compulsive eating behavior can impact disordered eating outcomes in humans, and whether there is translational relevance of a leptin-sensitive anterior insular circuit implicated in these behaviors.
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Hypothetical purchase tasks (HPTs) and operant demand analyses provide a promising methodology to determine how consumers value new products. This study used a demand analysis to determine value differences between Apple or Fitbit smartwatches and those same watches with hypothetical “added‐value” features. There were no differences between baseline smartwatches and those with additional features. However, participants who owned Apple products had significantly higher demand for Apple smartwatches, while this difference did not exist for Fitbit users. HPTs and demand analyses were sensitive enough to determine differences related to brand loyalty, but did not detect differences in added‐value of hypothetical features.
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Introduction Hypothetical purchase tasks have been widely used to assess the reinforcing value of tobacco products. However, a task has not yet been validated for little cigars and cigarillos (LCCs), a popular tobacco product class among vulnerable populations. This study sought to validate the LCC Purchase Task (LCCPT) in a sample of experienced LCC smokers. Methods Data were collected from 65 young adult (18-34 years) LCC and cigarette dual users (78.5% male) in Connecticut (2018-2020). Participants completed the usual-brand LCCPT for consumption in 24 hours at increasing prices. We calculated four observed demand indices: intensity (consumption at $0), breakpoint (price after which consumption reaches 0), Omax (maximum daily expenditure), and Pmax (price at which daily expenditure was maximized). Two indices were estimated from demand curves: Q0 (predicted consumption as price approaches $0) and price-sensitivity (sensitivity to price increases). Spearman correlations and multivariable regressions examined the associations between demand indices, self-reported cigar use, and dependence. Results Correlations were in expected directions. All indices except breakpoint and Pmax were positively correlated with use, and all indices were correlated with multiple measures of dependence. Overall, greater demand and expenditure for LCCs and lower sensitivity to price changes were correlated with greater use and dependence. In regression analyses intensity and price-sensitivity showed the strongest relationships with use and dependence. Conclusions The validity of the LCCPT was supported in a sample of experienced LCC smokers. This instrument can be incorporated into other protocols to assess the abuse liability of LCCs.
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Individual participant data meta‐analysis is a frequently used method to combine and contrast data from multiple independent studies. Bayesian hierarchical models are increasingly used to appropriately take into account potential heterogeneity between studies. In this paper, we propose a Bayesian hierarchical model for individual participant data generated from the Cigarette Purchase Task (CPT). Data from the CPT details how demand for cigarettes varies as a function of price, which is usually described as an exponential demand curve. As opposed to the conventional random‐effects meta‐analysis methods, Bayesian hierarchical models are able to estimate both the study‐specific and population‐level parameters simultaneously without relying on the normality assumptions. We applied the proposed model to a meta‐analysis with baseline CPT data from six studies and compared the results from the proposed model and a two‐step conventional random‐effects meta‐analysis approach. We conducted extensive simulation studies to investigate the performance of the proposed approach and discussed the benefits of using the Bayesian hierarchical model for individual participant data meta‐analysis of demand curves.
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Contingency management (CM), in which financial incentives are provided upon verification of abstinence from alcohol, cigarettes, and/or illicit substances, is one of the most highly effective and empirically supported treatments for substance use disorders. However, the financial cost of implementation has been identified as a major barrier to implementation of this treatment. The purpose of this study was to develop behavioral economic purchase tasks to assess interest in CM as a function of treatment cost and perceived effectiveness of CM as a function of abstinence incentive size in alcohol drinkers. Alcohol drinkers recruited from Amazon Mechanical Turk (MTurk) completed behavioral economic purchase tasks measuring demand for CM based on targeted abstinence intervals and treatment effectiveness and alcohol use disorder severity assessments. Nonlinear mixed-effects modeling was used to fit demand curves and assess the relationship between individual characteristics and demand metrics for CM. Results reveal that participants reported higher probability of remaining abstinent from drinking when offered larger incentives and required larger incentives when duration of abstinence required to earn the incentive was increased. Additionally, willingness to pay for treatment increased as effectiveness of treatment increased. Abstinence interval and treatment effectiveness are important features to consider when developing effective CM for widespread use, as these variables affected participants’ likelihood of being abstinent and their interest in treatment. Future work will validate these assessments with actual treatment outcomes and determine predictors of CM treatment effectiveness.
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The field of behavioral economics has made important inroads into the understanding of substance use disorders through the concept of reinforcer pathology. Reinforcer pathology refers to the joint effects of (a) the persistently high valuation of a reinforcer, broadly defined to include tangible commodities and experiences, and/or (b) the excessive preference for the immediate acquisition or consumption of a commodity despite long-term negative outcomes. From this perspective, reinforcer pathology results from the recursive interactions of endogenous person-level variables and exogenous environment-level factors. The current review describes the basic principles of behavioral economics that are central to reinforcer pathology, the processes that engender reinforcer pathology, and the approaches and procedures that can repair reinforcement pathologies. The overall goal of this review is to present a new understanding of substance use disorders as viewed by recent advances in behavioral economics.
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The application of economics principles to the analysis of behavior has yielded novel insights on value and choice across contexts ranging from laboratory animal research to clinical populations to national trends of global impact. Recent innovations in demand curve methods provide a credible means of quantitatively comparing qualitatively different reinforcers as well as quantifying the choice relations between concurrently available reinforcers. The potential of the behavioral economic approach to inform public policy is illustrated with examples from basic research, pre-clinical behavioral pharmacology, and clinical drug abuse research as well as emerging applications to public transportation and social behavior. Behavioral Economics can serve as a broadly applicable conceptual, methodological, and analytical framework for the development and evaluation of empirical public policy.
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Introduction: Varenicline (Chantix®) is an efficacious first-line medication for smoking cessation. Studies suggest that one mechanism by which varenicline facilitates sustained smoking abstinence is by reducing the likelihood of relapse to smoking when a lapse, or slip, occurs during a quit attempt. The present study extends this line of research by conducting a prospective laboratory study to examine the relapse prevention effects of varenicline following a programmed lapse. Methods: Daily smokers (N = 47) completed a 5-week outpatient study in which they were randomized to receive varenicline or placebo. The first week was a medication induction period that was immediately followed by a 4-week quit attempt. A programmed lapse (2 cigarettes smoked in the laboratory) occurred on the second day of the quit attempt. Results: Participants receiving varenicline were slower to relapse and had greater total abstinence rates following lapse exposure. Participants in the varenicline group rated lapse cigarettes lower on measures of reward and intoxication and showed increased behavioral economic demand elasticity for cigarettes (reduced cigarette purchasing at higher prices) compared with those receiving placebo. Conclusions: These results demonstrate a relapse prevention effect of varenicline following smoking lapse exposure and suggest that an attenuation of reward from smoking and the blunting of subjective effects of smoking may underlie and/or contribute to this effect.
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A relatively small percentage of humans who are exposed to drugs of abuse eventually become addicted to or dependent on those drugs. These individual differences in likelihood of developing drug addiction may reflect behavioral, neurobiological or genetic correlates of drug addiction and are therefore important to model. Behavioral economic measures of demand establish functions whose overall elasticity (rate of decrease in consumption as price increases) reflects the reinforcing effectiveness of various stimuli, including drugs. Using these demand functions, we determined the reinforcing effectiveness of five drugs of abuse (cocaine, remifentanil, ketamine, methohexital and ethanol) in 10 rhesus monkeys with histories of intravenous drug-taking. There was a continuum of reinforcing effectiveness across the five drugs, with cocaine and remifentanil showing the most reinforcing effectiveness. There was also a continuum of sensitivity of the monkeys; two of the 10 animals, in particular, showed greater demand for the drugs than did the remaining eight monkeys. In addition, monkeys that demonstrated greater demand for one drug tended to show greater demand for all drugs but did not show a similar relatively greater demand for sucrose pellets. These findings suggest that the tendency to find drugs to be reinforcing is a general one, not restricted to particular drugs and also, that a minority of animals show a substantially enhanced sensitivity to the reinforcing effects of drugs. The possibility that differences in responsiveness to the reinforcing effects of drugs may form the basis of individual differences in drug-taking in humans should be considered.
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One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for 8 standard statistical tests: (1) the difference between independent means, (2) the significance of a product-moment correlation, (3) the difference between independent rs, (4) the sign test, (5) the difference between independent proportions, (6) chi-square tests for goodness of fit and contingency tables, (7) 1-way analysis of variance (ANOVA), and (8) the significance of a multiple or multiple partial correlation.
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The strength of a rat's eating reflex correlates with hunger level when strength is measured by the response frequency that precedes eating (B. F. Skinner, 1932a, 1932b). On the basis of this finding, Skinner argued response frequency could index reflex strength. Subsequent work documented difficulties with this notion because responding was affected not only by the strengthening properties of the reinforcer but also by the rate-shaping effects of the schedule. This article obviates this problem by measuring strength via methods from behavioral economics. This approach uses demand curves to map how reinforcer consumption changes with changes in the "price" different ratio schedules impose. An exponential equation is used to model these demand curves. The value of this exponential's rate constant is used to scale the strength or essential value of a reinforcer, independent of the scalar dimensions of the reinforcer. Essential value determines the consumption level to be expected at particular prices and the response level that will occur to support that consumption. This approach permits comparing reinforcers that differ in kind, contributing toward the goal of scaling reinforcer value.
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Behavioral economic demand curves (Hursh, Raslear, Shurtleff, Bauman, & Simmons, 1988) are innovative approaches to characterize the relationships between consumption of a substance and its price. In this article, we investigate common analytical issues in the use of behavioral economic demand curves, which can cause inconsistent interpretations of demand curves, and then we provide methodological suggestions to address those analytical issues. We first demonstrate that log transformation with different added values for handling zeros changes model parameter estimates dramatically. Second, demand curves are often analyzed using an overparameterized model that results in an inefficient use of the available data and a lack of assessment of the variability among individuals. To address these issues, we apply a nonlinear mixed effects model based on multivariate error structures that has not been used previously to analyze behavioral economic demand curves in the literature. We also propose analytical formulas for the relevant standard errors of derived values such as P max, O max, and elasticity. The proposed model stabilizes the derived values regardless of using different added increments and provides substantially smaller standard errors. We illustrate the data analysis procedure using data from a relative reinforcement efficacy study of simulated marijuana purchasing.
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Introduction: Cigarette demand, or the change in cigarette consumption as a function of price, is a measure of reinforcement that is associated with level of tobacco dependence and other clinically relevant measures, but the effects of experimentally controlled income on real-world cigarette consumption have not been examined. Methods: In this study, income available for cigarette purchases was manipulated to assess the effect on cigarette demand. Tobacco-dependent cigarette smokers (n = 15) who smoked 10-40 cigarettes per day completed a series of cigarette purchasing tasks under a variety of income conditions meant to mimic different weekly cigarette budgets: $280, approximately $127, $70, or approximately $32 per week. Prices of $0.12, $0.25, $0.50, and $1.00 per cigarette were assessed in each income condition. Participants were instructed to purchase as many cigarettes as they would like for the next week and to only consume cigarettes purchased in the context of the study. One price in 1 income condition was randomly chosen to be "real," and the cigarettes and the excess money in the budget for that condition were given to the participant. Results: Results indicate that demand elasticity was negatively correlated with income. Demand intensity (consumption at low prices) was unrelated to income condition and remained high across incomes. Conclusions: These results indicate that the amount of income that is available for cigarette purchases has a large effect on cigarette consumption, but only at high prices.
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This paper proposes an extension of generalized linear models to the analysis of longitudinal data. We introduce a class of estimating equations that give consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence. The estimating equations are derived without specifying the joint distribution of a subject's observations yet they reduce to the score equations for niultivariate Gaussian outcomes. Asymptotic theory is presented for the general class of estimators. Specific cases in which we assume independence, m-dependence and exchangeable correlation structures from each subject are discussed. Efficiency of the pioposecl estimators in two simple situations is considered. The approach is closely related to quasi-likelihood.
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Aims: Novel methods in behavioral economics permit the systematic assessment of the relationship between cigarette consumption and price. Towards informing tax policy, the goals of this study were to conduct a high-resolution analysis of cigarette demand in a large sample of adult smokers and to use the data to estimate the effects of tax increases in 10 US States. Design: In-person descriptive survey assessment. Setting: Academic departments at three universities. Participants: Adult daily smokers (i.e. more than five cigarettes/day; 18+ years old; ≥8th grade education); n = 1056. Measurements: Estimated cigarette demand, demographics, expired carbon monoxide. Findings: The cigarette demand curve exhibited highly variable levels of price sensitivity, especially in the form of 'left-digit effects' (i.e. very high price sensitivity as pack prices transitioned from one whole number to the next; e.g. $5.80-6/pack). A $1 tax increase in the 10 states was projected to reduce the economic burden of smoking by an average of $530.6 million (range: $93.6-976.5 million) and increase gross tax revenue by an average of 162% (range: 114-247%). Conclusions: Tobacco price sensitivity is non-linear across the demand curve and in particular for pack-level left-digit price transitions. Tax increases in US states with similar price and tax rates to the sample are projected to result in substantial decreases in smoking-related costs and substantial increases in tax revenues.
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Substance abusers, including cocaine abusers, discount delayed rewards to a greater extent than do matched controls. In the current experiment, individual differences in discounting of delayed rewards in rats (choice of one immediate over three delayed sucrose pellets) were assessed for associations with demand for either sucrose pellets or an intravenous dose of 0.1 mg/kg/infusion cocaine. Twenty-four male Sprague Dawley rats were split into three groups based on sensitivity to delay to reinforcement. Then, demand for sucrose pellets and cocaine was determined across a range of fixed-ratio values. Delay discounting was then reassessed to determine the stability of this measure over the course of the experiment. Individual differences in impulsive choice were positively associated with elasticity of demand for cocaine, a measure of reinforcer value, indicating that rats having higher discount rates also valued cocaine more. Impulsive choice was not associated with the level of cocaine consumption as price approached 0 or with any parameter associated with demand for sucrose. Individual sensitivity to delay was correlated with the initial assessment when reassessed at the end of the experiment, although impulsive choice increased for this cohort of rats as a whole. These findings suggest that impulsive choice in rats is positively associated with valuation of cocaine, but not sucrose.
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This study examined whether continued access to methamphetamine or food reinforcement changed economic demand for both. The relationship between demand elasticity and cue-induced reinstatement was also determined. Male Long-Evans rats were lever pressed under increasing fixed-ratio requirements for either food pellets or methamphetamine (20 μg/50 μl infusion). For two groups, demand curves were obtained before and after continued access (12 days, 2-h sessions) to the reinforcer under a fixed-ratio 3 schedule. A third group was given continued access to methamphetamine between determinations of food demand and a fourth group abstained from methamphetamine between determinations. All groups underwent extinction sessions, followed by a cue-induced reinstatement test. Although food demand was less elastic than methamphetamine demand, continued access to methamphetamine shifted the methamphetamine demand curve upward and the food demand curve downward. In some rats, methamphetamine demand also became less elastic. Continued access to food had no effect on food demand. Reinstatement was higher after continued access to methamphetamine relative to food. For methamphetamine, elasticity and reinstatement measures were correlated. Continued access to methamphetamine, but not food, alters demand in ways suggestive of methamphetamine accruing reinforcing strength. Demand elasticity thus provides a useful measure of abuse liability that may predict future relapse to renewed drug-seeking and drug use.
Article
Considerable basic and clinical research supports a behavioral economic conceptualization of alcohol and drug dependence. One behavioral economic approach to assess motivation for a drug is the use of demand curves, or quantitative representations of drug consumption and drug-reinforced responding across a range of prices. This study used a hypothetical alcohol purchase task to generate demand curves, and examined whether the resulting demand curve parameters predicted drinking outcomes following a brief intervention. Participants were 51 college student drinkers (67% female; 94% Caucasian; drinks/week: M=24.57, S.D.=8.77) who completed a brief alcohol intervention. Consistent with predictions, a number of demand curve indices significantly predicted post-intervention alcohol use and frequency of heavy drinking episodes, even after controlling for baseline drinking and other pertinent covariates. Most prominently, O(max) (i.e., maximum alcohol expenditure) and breakpoint (i.e., sensitivity of consumption to increasing price) predicted greater drinking at 6-month post-intervention follow-up. These results indicate that a behavioral economic measure of alcohol demand may have utility in characterizing the malleability of alcohol consumption. Moreover, these results support the utility of translating experimental assays of reinforcement into clinical research.