Cocaine abstinence during the "critical period" of a contingency management trial predicts future abstinence in people with cocaine use disorder.

BACKGROUND: Contingency Management (CM) is being piloted as a treatment for stimulant use disorder in several US states, highlighting the need for treatment optimization. One important goal of optimization is decreasing drug use during the early stages of treatment, which has predicted success in other interventions. However, this "critical period" has not been reported in CM trials. The purpose of this analysis was to determine if, after accounting for baseline abstinence and incentive condition, abstinence in a CM trial for people with Cocaine Use Disorder (CUD) could be predicted by cocaine use during a first-week critical period. METHODS: Eighty-seven participants with CUD were randomized to receive contingent high or low value incentives for cocaine abstinence or were in a non-contingent control group. Generalized estimating equations (GEE) were used to analyze urine test results over 36 timepoints during the 12-week intervention. To assess for a critical period, the first three visits were included in the GEE as a covariate for remaining urine test results. RESULTS: Participants who provided more negative samples during the critical period were significantly more likely to produce a negative urine sample during the remainder of the trial, though some effects of group remained after controlling for the critical period. CONCLUSIONS: These results indicate that a critical period exists for CM trials, and it can explain a substantial amount of future performance. Early contact with an abstinence-contingent high magnitude alternative reinforcer may explain additional performance beyond the critical period, further justifying the use of high magnitude alternative reinforcers.

A systematic review of remotely delivered contingency management treatment for substance use.

BACKGROUND: Substance use and related consequences (e.g., impaired driving, injuries, disease transmission) continue to be major public health concerns. Contingency management (CM) is a highly effective treatment for substance use disorders. Yet CM remains vastly underutilized, in large part due to implementation barriers to in-person delivery. If feasible and effective, remote delivery of CM may reduce barriers at both the clinic- and patient-level, thus increasing reach and access to effective care. Here, we summarize data from a systematic review of studies reporting remote delivery of CM for substance use treatment. METHODS: We conducted a systematic review, reported according to PRISMA guidelines. The study team identified a total of 4358 articles after deduplication. Following title and abstract screening, full-text screening, and reference tracking, 39 studies met the eligibility criteria. We evaluated the methodological quality of the included studies using the Effective Public Health Practice Project Quality tool. RESULTS: Of 39 articles included in the review, most (n = 26) targeted cigarette smoking, with others focusing on alcohol (n = 9) or other substance use or targeting multiple substances (n = 4). Most remotely delivered CM studies focused on abstinence (n = 29), with others targeting substance use reduction (n = 2), intervention engagement (n = 5), and both abstinence and intervention engagement (n = 3). CM was associated with better outcomes (either abstinence, use reduction, or engagement), with increasingly more remotely delivered CM studies published in more recent years. Studies ranged from moderate to strong quality, with the majority (57.5 %) of studies being strong quality. CONCLUSIONS: Consistent with in-person CM, remotely delivered CM focusing on abstinence or use reduction from substances or engagement in substance use treatment services improves outcomes at the end of treatment compared to control conditions. Moreover, remotely delivered CM is feasible across a variety of digital delivery platforms (e.g., web, mobile, and wearable), with acceptability and reduced clinic and patient burden as technological advancements streamline monitoring and reinforcer delivery.

Interest in and perceived effectiveness of contingency management among alcohol drinkers using behavioral economic purchase tasks.

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. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A tribute to Howard Rachlin and his two-parameter discounting model: Reliable and flexible model fitting.

Delay discounting reflects the rate at which a reward loses its subjective value as a function of delay to that reward. Many models have been proposed to measure delay discounting, and many comparisons have been made among these models. We highlight the two-parameter delay discounting model popularized by Howard Rachlin by demonstrating two key practical features of the Rachlin model. The first feature is flexibility; the Rachlin model fits empirical discounting data closely. Second, when compared with other available two-parameter discounting models, the Rachlin model has the advantage that unique best estimates for parameters are easy to obtain across a wide variety of potential discounting patterns. We focus this work on this second feature in the context of maximum likelihood, showing the relative ease with which the Rachlin model can be utilized compared with the extreme care that must be used with other models for discounting data, focusing on two illustrative cases that pass checks for data validity. Both of these features are demonstrated via a reanalysis of discounting data the authors have previously used for model selection purposes.

Notes on demand: Conceptual and empirical benefits of applying Rachlin's discounting equation to demand data.

OBJECTIVE: Howard Rachlin wrote extensively on how value diminishes in a hyperbolic form, and he contributed to understanding choice processes between different commodities as a molar pattern of behavior. The field of behavioral economic demand has been dominated by exponential decay functions, indicating that decreases in consumption of a commodity are best fit by exponential functions. Because of the success of Rachlin's equation at describing how hyperbolic decay affects the value of a commodity across various factors (e.g., delay, probability, social distance), we attempted to extend his equation to behavioral economic demand data for alcohol and opioids. METHOD: Rachlin's discounting equation was applied to estimate consumption on alcohol purchase task data and nonhuman drug demand data. We compared results of his equation to the exponentiated demand equation using both a mixed-effects modeling approach and a two-stage approach. RESULTS: Rachlin's equation provided better fits to consumption data than the exponentiated equation for both mixed-effects and two-stage modeling. We also found that traditional demand metrics, such as Pmax, can be derived analytically when using Rachlin's equation. Certain metrics derived from Rachlin's equation appeared to be related to clinical covariates in ways similar to the exponentiated equation. CONCLUSIONS: Rachlin's equation better described demand data than did the exponentiated equation, indicating that demand for a commodity may decrease hyperbolically rather than exponentially. Other benefits of his equation are that it does not have the same pitfalls as the current exponential equations and is relatively straightforward in its conceptualization when applied to demand data. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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

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

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

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

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

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

Blood Nicotine Predicts the Behavioral Economic Abuse Liability of Reduced-Nicotine Cigarettes.

BACKGROUND: Cigarette smoking continues to be a major health concern and remains the leading preventable cause of death in the US. 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; 15.8 mg/g, 5.2 mg/g, 2.4 mg/g, 1.3 mg/g, and 0.4 mg/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 in derived intensity (Q0) and change in elasticity (α). RESULTS: Measures of 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, α was 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.

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

Behavioral economic demand methodology is increasingly being used in various fields such as substance use and consumer behavior analysis. Traditional analytical techniques to fitting demand data have proven useful yet some of these approaches require preprocessing of data, ignore dependence in the data, and present statistical limitations. We term these approaches "fit to group" and "two stage" with the former interested in group or population level estimates and the latter interested in individual subject estimates. As an extension to these regression techniques, mixed-effect (or multilevel) modeling can serve as an improvement over these traditional methods. Notable benefits include providing simultaneous group (i.e., population) level estimates (with more accurate standard errors) and individual level predictions while accommodating the inclusion of "nonsystematic" response sets and covariates. These models can also accommodate complex experimental designs including repeated measures. The goal of this article is to introduce and provide a high-level overview of mixed-effects modeling techniques applied to behavioral economic demand data. We compare and contrast results from traditional techniques to that of the mixed-effects models across two datasets differing in species and experimental design. We discuss the relative benefits and drawbacks of these approaches and provide access to statistical code and data to support the analytical replicability of the comparisons. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40614-021-00299-7.

Remotely administered incentive-based treatment for alcohol use disorder with participant-funded incentives is effective but less accessible to low-income participants.

The delivery of monetary incentives contingent on verified abstinence is an effective treatment for alcohol use disorder. However, incentive cost has often been cited as a barrier to delivering this type of treatment. In the present randomized parallel groups trial, we systematically replicated a previous trial we conducted that employed remote alcohol monitoring and incentive delivery to promote abstinence from alcohol, but with the additional requirement for participants to partially self-fund their abstinence incentives. Treatment-seeking participants with alcohol use disorder (n = 92) who met inclusion criteria (n = 36) were randomized to either a Contingent or Noncontingent group (n = 18 each). Those not meeting inclusion criteria included 15 participants who agreed to the deposit requirement but failed to make the deposit payment. The Contingent group received nearly immediate monetary incentives each day they remotely provided negative breathalyzer samples. The Noncontingent group received matched incentives each day they successfully provided samples independent of alcohol content. Days abstinent in the Contingent group were 86%, which was significantly higher than the 44% recorded in the Noncontingent group, corresponding to an odds ratio of 8.2. Exploratory analyses revealed that the deposit requirement prevented participation in those with lower incomes and those with greater alcohol use. These results support the efficacy of this remotely deliverable alcohol abstinence reinforcement incentive intervention with a deposit requirement. However, the requirement to provide a monetary deposit to self-fund abstinence incentives may prevent those with greater alcohol use and/or those experiencing extreme poverty from participating in the intervention. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Choice Bundling Increases Valuation of Delayed Losses More Than Gains in Cigarette Smokers.

Choice bundling, in which a single choice produces a series of repeating consequences over time, increases valuation of delayed monetary and non-monetary gains. Interventions derived from this manipulation may be an effective method for mitigating the elevated delay discounting rates observed in cigarette smokers. No prior work, however, has investigated whether the effects of choice bundling generalize to reward losses. In the present study, an online panel of cigarette smokers (N = 302), recruited using survey firms Ipsos and InnovateMR, completed assessments for either monetary gains or losses (randomly assigned). In Step 1, participants completed a delay-discounting task to establish Effective Delay 50 (ED50), or the delay required for an outcome to lose half of its value. In Step 2, participants completed three conditions of an adjusting-amount task, choosing between a smaller, sooner (SS) adjusting amount and a larger, later (LL) fixed amount. The bundle size (i.e., number of consequences) was manipulated across conditions, where a single choice produced either 1 (control), 3, or 9 consequences over time (ascending/descending order counterbalanced). The delay to the first LL amount in each condition, as well as the intervals between all additional SS and LL amounts (where applicable), were set to individual participants' ED50 values from Step 1 to control for differences in discounting of gains and losses. Results from Step 1 showed significantly higher ED50 values (i.e., less discounting) for losses compared to gains (p < 0.001). Results from Step 2 showed that choice bundling significantly increased valuation of both LL gains and losses (p < 0.001), although effects were significantly greater for losses (p < 0.01). Sensitivity analyses replicated these conclusions. Future research should examine the potential clinical utility of choice bundling, such as development of motivational interventions that emphasize both the bundled health gains associated with smoking cessation and the health losses associated with continued smoking.

Effects of Reduced-Nicotine Cigarettes Across Regulatory Environments in the Experimental Tobacco Marketplace: A Randomized Trial.

INTRODUCTION: Cigarette smoking remains the leading preventable cause of death in the United States. Recent efforts have explored the potential health and policy benefits of reducing nicotine, an addictive component, in combustible cigarettes. To date, an experimental, prospective analysis directly comparing the effects of varying regulatory environments on purchases of multiple products has yet to be conducted. The present study compared real purchasing of conventional cigarettes, reduced-nicotine cigarettes, and a variety of other nicotine and tobacco products across a range of regulatory environments. METHODS: Participants were assigned to one of five groups, each associated with a different nicotine level (mg of nicotine to g of tobacco) in SPECTRUM investigational cigarettes (15.8, 5.2, 2.4, 1.3, and 0.4 mg/g). Across sessions, participants made real purchases for nicotine/tobacco products in an Experimental Tobacco Marketplace. Each session corresponded with a distinct regulatory environment wherein different nicotine/tobacco products were available for purchase. RESULTS: Our results suggest that the primary drivers of cigarette and nicotine purchasing are regulatory environment and the presence/absence of alternative nicotine and tobacco products. Perhaps surprisingly, nicotine level does not appear to be such a driver of purchasing behavior under these experimental conditions. Investigational cigarette purchasing is lowest when other preferred combustible products are available and highest when investigational cigarettes are the only combustible product available for purchase. CONCLUSIONS: If a reduced-nicotine policy is implemented, great care should be taken in determining and making available less-harmful nicotine/tobacco products as the availability of preferred combustible products may result in undesirable levels of purchasing. IMPLICATIONS: This is the first experimental study investigating different potential regulatory effects related to a reduced-nicotine policy by examining purchasing across a range of nicotine/tobacco products. Our results suggest the presence of affordable, highly preferred combustible products is likely to maintain tobacco purchasing at undesirable levels. To promote switching to less-harmful products, affordable alternate nicotine and tobacco products should be readily available. Finally, our results suggest that the availability of noncigarette products, not cigarette nicotine level, will most likely affect purchasing of reduced-nicotine cigarettes.

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

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

Timeline Followback Self-Reports Underestimate Alcohol Use Prior to Successful Contingency Management Treatment.

AIMS: Alcohol consumption is a modifiable and plausible risk factor for age-related cognitive decline but more longitudinal studies investigating the association are needed. Our aims were to estimate associations of adult-life alcohol consumption and consumption patterns with age-related cognitive decline. METHODS: We investigated the associations of self-reported adult-life weekly alcohol consumption and weekly extreme binge drinking (≥10 units on the same occasion) with changes in test scores on an identical validated test of intelligence completed in early adulthood and late midlife in 2498 Danish men from the Lifestyle and Cognition Follow-up study 2015. Analyses were adjusted for year of birth, retest interval, baseline IQ, education and smoking. RESULTS: Men with adult-life alcohol consumption of more than 28 units/week had a larger decline in IQ scores from early adulthood to late midlife than men consuming 1-14 units/week (B29-35units/week = -3.6; P < 0.001). Likewise, a 1-year increase in weekly extreme binge drinking was associated with a 0.12-point decline in IQ scores (P < 0.001). Weekly extreme binge drinking explained more variance in IQ changes than average weekly consumption. In analyses including mutual adjustment of weekly extreme binge drinking and average weekly alcohol consumption, the estimated IQ decline associated with extreme binge drinking was largely unaffected, whereas the association with weekly alcohol consumption became non-significant. CONCLUSIONS: Adult-life heavy alcohol consumption and extreme binge drinking appear to be associated with larger cognitive decline in men. Moreover, extreme binge drinking may be more important than weekly alcohol consumption in relation to cognitive decline.

Reinforcer pathology: Common neural substrates for delay discounting and snack purchasing in prediabetics.

Reinforcer pathology theory stipulates that individuals with both (a) high preference for smaller, immediate over larger, delayed rewards; and (b) high demand for unhealthy commodities are uniquely susceptible to poor health outcomes. Specifically, two behavioral economic tasks (delay discounting, assessing preference for smaller, immediate or larger, delayed rewards; and purchasing, assessing purchases of commodities over changes in price) have been independently associated with conditions such as overweight/obesity and problem substance use. In the present study, we examined possible shared neural regions involved in the processes of delay discounting and demand for snack foods in a prediabetic sample. Fifty-four participants completed both of these tasks. Conjunction between delay discounting and purchasing task results indicates substantial common neural substrates recruited during these two tasks, consistent with interpretations of executive control, interoception, and attention, in the prefrontal cortex, insula, and frontoparietal cortex (superior/middle frontal cortex and superior/inferior parietal lobules), respectively. Collectively, these results suggest possible neural substrates in which the two behavioral risk factors of reinforcer pathology may interact during real-world decision-making in prediabetes.

The effects of extended-release injectable naltrexone and incentives for opiate abstinence in heroin-dependent adults in a model therapeutic workplace: A randomized trial.

AIM: To determine whether extended-release injectable naltrexone (XR-NTX), incentives for opiate abstinence, and their combination reduce opiate use compared to a usual care control and whether the combination reduces opiate use compared to either treatment alone. DESIGN: Randomized 2 × 2 single-site controlled trial conducted from November 2012 through May 2016. After a detoxification and oral naltrexone induction, participants were assigned to a Usual Care, Abstinence Incentives, XR-NTX, or XR-NTX plus Abstinence Incentives group for a six-month intervention period. SETTING: A model therapeutic workplace where participants could work on automated computer programs that targeted job-skills training for 4 h every weekday for 24 weeks and earn about $10 per hour. PARTICIPANTS: 84 heroin-dependent adults who were unemployed and medically approved for naltrexone. Most participants were male (71.4%), African American (80.1%), and cocaine dependent (71.4%). MEASUREMENTS: The primary outcome measure was the percentage of urine samples negative for opiates that were collected at once weekly assessments (24 per participant) that were not part of the intervention and for which participants were paid $10 for completing. INTERVENTION: Participants who attended the workplace provided thrice-weekly urine samples. Abstinence Incentives participants had to provide opiate-free urine samples to maintain maximum pay. XR-NTX participants received one injection every 4 weeks and were required to take injections in order to work and to maintain maximum pay. Usual Care participants were not offered XR-NTX and opiate urinalysis results did not affect pay. FINDINGS: A large percentage (65 of 149; 43.6%) of individuals failed the induction protocol required for randomization and to be eligible to receive XR-NTX. When missing urine samples were considered positive, there was no significant interaction between XR-NTX and Abstinence Incentives. XR-NTX plus Abstinence Incentives participants provided significantly more opiate-negative samples (81.3%, SD 39.0%) than XR-NTX participants (64.5%, SD 47.9%; aOR 10.4, 95% CI 1.3-85.5; P = .030). When urine samples were not replaced, there was a significant interaction between XR-NTX and Abstinence Incentives (aOR 77.0, 95% CI 1.3-4432;P = 0.036); XR-NTX plus Abstinence Incentives participants provided significantly more opiate-negative samples (99.6%, SD 0.1%) than XR-NTX participants (85.0%, SD 35.7%; aOR 147.6, 95% CI 6.3-3472; P = 0.002), Abstinence Incentives participants (91.9%, SD 27.3%; aOR 121.7, 95% CI 4.8-3067; P =0.004), and Usual Care participants (78.7%, SD 41.0%; aOR 233.4, 95% CI 9.4-5814; P <.001). No other group differences were significant. CONCLUSION: XR-NTX plus incentives for opiate abstinence increased opiate abstinence, but XR-NTX alone did not. XR-NTX can promote opiate abstinence when it is combined with incentives for opiate abstinence in a model therapeutic workplace.

An overview of Bayesian reasoning in the analysis of delay-discounting data.

Statistical inference (including interval estimation and model selection) is increasingly used in the analysis of behavioral data. As with many other fields, statistical approaches for these analyses traditionally use classical (i.e., frequentist) methods. Interpreting classical intervals and p-values correctly can be burdensome and counterintuitive. By contrast, Bayesian methods treat data, parameters, and hypotheses as random quantities and use rules of conditional probability to produce direct probabilistic statements about models and parameters given observed study data. In this work, we reanalyze two data sets using Bayesian procedures. We precede the analyses with an overview of the Bayesian paradigm. The first study reanalyzes data from a recent study of controls, heavy smokers, and individuals with alcohol and/or cocaine substance use disorder, and focuses on Bayesian hypothesis testing for covariates and interval estimation for discounting rates among various substance use disorder profiles. The second example analyzes hypothetical environmental delay-discounting data. This example focuses on using historical data to establish prior distributions for parameters while allowing subjective expert opinion to govern the prior distribution on model preference. We review the subjective nature of specifying Bayesian prior distributions but also review established methods to standardize the generation of priors and remove subjective influence while still taking advantage of the interpretive advantages of Bayesian analyses. We present the Bayesian approach as an alternative paradigm for statistical inference and discuss its strengths and weaknesses.

The R package beezdemand: Behavioral Economic Easy Demand.

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