The Demand Curve Analyzer: Behavioral economic software for applied research

Hyperbolae

Hyperbolic relations between independent and dependent variables are ubiquitous in the experimental analysis of behavior, mentioned in over 150 articles in the Journal of the Experimental Analysis of Behavior. There are two principal forms of hyperbolae: The first describes the relation between response rate and reinforcement rate on variable-interval schedules of reinforcement; it rises asymptotically toward a maximum. The second describes the relation between the current equivalent value of an incentive and its delay or (im)probability; it falls from a maximum toward an asymptote of 0. Where do these come from? What do their parameters mean? How are they related? This article answers the first two questions and addresses the last.

Problematic mobile phone use as impulsive choice: Development and empirical verification of a reinforcer-pathology model

Problematic mobile phone use is characterized by its "impulsive" nature; users engage in it despite their negative attitude toward it. From a behavioral-economic perspective, this attitude-behavior discrepancy is generated by competing contingencies that involve smaller-sooner social reinforcers associated with mobile phone use and larger-later prosocial reinforcers potentially compromised by phone use. Based on this conceptualization, the reinforcer-pathology model of problematic mobile phone use is proposed, which posits that such phone use stems from excessive delay discounting of the social and prosocial reinforcers and/or excessive demand for the social reinforcers. A secondary data analysis of previously published studies was conducted, with the novel addition of principal component analysis and hierarchical cluster analysis of these data. The results generated evidence that supports the reinforcer-pathology model proposed in this article. Based on the theoretical analyses and accumulated empirical evidence, theory-driven prevention and intervention strategies for problematic mobile phone use are proposed. Overall, the reinforcer-pathology model of problematic mobile phone use provides a comprehensive framework for understanding and addressing this growing issue.

Machine Learning-Based Integration Develops a Macrophage-Related Index for Predicting Prognosis and Immunotherapy Response in Lung Adenocarcinoma

BACKGROUND

Macrophages play a critical role in tumor immune microenvironment (TIME) formation and cancer progression in lung adenocarcinoma (LUAD). However, few studies have comprehensively and systematically described the characteristics of macrophages in LUAD.

METHODS

This study identified macrophage-related markers with single-cell RNA sequencing data from the GSE189487 dataset. An integrative machine learning-based procedure based on 10 algorithms was developed to construct a macrophage-related index (MRI) in The Cancer Genome Atlas (TCGA), GSE30219, GSE31210, and GSE72094 datasets. Several algorithms were used to evaluate the associations of MRI with TIME and immunotherapy-related biomarkers. The role of MRI in predicting the immunotherapy response was evaluated with the GSE91061 dataset.

RESULTS

The optimal MRI constructed by the combination of the Lasso algorithm and plsRCox was an independent risk factor in LUAD and showed a stable and powerful performance in predicting the overall survival rate of patients with LUAD. Those with low MRI scores had a higher TIME score, a higher level of immune cells, a higher immunophenoscore, and a lower Tumor Immune Dysfunction and Exclusion (TIDE) score, indicating a better response to immunotherapy. The IC50 value of common drugs for chemotherapy and target therapy with low MRI scores was higher compared to high MRI scores. Moreover, the survival prediction nomogram, developed from MRI, had good potential for clinical application in predicting the 1-, 3-, and 5-year overall survival rate of LUAD.

CONCLUSION

Our study constructed for the first time a consensus MRI for LUAD with 10 machine learning algorithms. The MRI could be helpful for risk stratification, prognosis, and selection of treatment approach in LUAD.

Interpretation(s) of essential value in operant demand

The operant demand framework has achieved high levels of adoption as an approach to quantify how various ecological factors influence choice. A central goal of the framework proposed by Hursh and Silberburg (2008) was to isolate the "essential value" of reinforcers-namely, their effects on behavior given various contextual factors. The effect of reinforcers on behavior is a phenomenon that is expected to vary as a function of reinforcer magnitude/dosage (i.e., units of reinforcement), price (i.e., schedule requirements), the intensity of demand (i.e., consumption in free operant conditions), the availability of reinforcers (i.e., supply, presence of alternatives), and the individual's current and historical context. This technical report provides a historical summary of the concept, describes the quantitative basis for essential value in the framework of Hursh and Silberburg (2008), reviews prior attempts to extract a generalizable index of essential value, and presents a newer formulation using exact solution that provides a more succinct and durable index. Proofs and solutions are provided to clarify the bases for novel and existing representations of essential value. Recommendations are provided to improve the precision and accuracy of behavioral economic metrics as well as support consensus regarding their interpretation in the operant demand framework.

Using an experimental tobacco marketplace to pilot test the substitutability of JUUL e-cigarettes and other alternative nicotine and tobacco products for conventional cigarettes among vulnerable populations

The Experimental Tobacco Marketplace (ETM) is an online research marketplace where increasing the cost of cigarettes is used to investigate the substitutability of other fixed-price tobacco products such as electronic nicotine delivery systems (ENDS). The ETM is useful for modeling effects of potential policy changes on use of various concurrently available products. To our knowledge, the ETM has not been used to investigate substitutability of newer generation e-cigarettes or populations at increased risk for smoking, heavy smoking, nicotine dependence, and smoking-attributable adverse effects. In the current pilot study, participants were 30 adult daily smokers with socioeconomic disadvantage or comorbid psychiatric conditions (substance-use disorder or mental illness). In each session, cigarette prices increased ($0.12, $0.25, $0.50, $1.00. and $2.00 per cigarette) while prices for alternative products remained fixed. Across three ETM sessions, either all products, all products except little cigars and cigarillos (LCCs), or all products except ENDS (JUUL e-cigarettes) were available. Linear regression was performed on individual participant data using log-transformed cigarette price to determine demand and substitution. Cigarette demand decreased as price increased across sessions (significantly non-zero slopes, ps ≤ 0.0001). When all products were available, ENDS substitution increased as cigarette price increased (significantly non-zero slope, p = .016). When LCCs were unavailable, ENDS again were a significant substitute (p = .008). When ENDS were unavailable, LCCs did not substitute (ps ≥ 0.48). In all sessions, participants rarely purchased other products (e.g., snus). Overall, ENDS were the most robust substitute for cigarettes, further underscoring the potential importance of ENDS availability on the impact of tobacco regulatory policies.

Reinforcer pathology of internet-related behaviors among college students: Data from six countries

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) 2022 APA, all rights reserved).

Combined Working Memory Training and Transcranial Magnetic Stimulation Demonstrates Low Feasibility and Potentially Worse Outcomes on Delay to Smoking and Cognitive Tasks: A Randomized 2 × 2 Factorial Design Pilot and Feasibility Study

INTRODUCTION

Repetitive Transcranial Magnetic Stimulation (rTMS) has shown promising results in treating several Substance Use Disorders including Tobacco Use Disorder. However, questions remain regarding how to optimize treatment outcomes. Enhancement of working memory by rTMS is a potential therapeutic mechanism. The current pilot study examined whether rTMS plus a cognitive training program could enhance the effects of rTMS on smoking behaviors using a controlled, factorial design.

AIMS AND METHODS

We hypothesized that cognitive training plus stimulation would improve control over smoking behaviors, resulting in enhanced cognitive performance and increased latency to smoke on a delay to smoking analog task. Using a 2 × 2 factorial design, nicotine dependent smokers (n = 43) were randomized to receive 10 sessions of active (10 Hz) or sham rTMS delivered to the left dorsolateral prefrontal cortex, plus active or sham working memory training (WMT) prior to and following stimulation.

RESULTS

Contrary to hypotheses, we observed a significant interaction effect, indicating that combining the two active interventions (rTMS+WMT) resulted in worse performance on the smoking analog task (B = -33.0, 95% CI = -64.39, -1.61, p < .05), compared to delivering either intervention alone. Additionally, although active rTMS (compared to sham rTMS) improved letter-sequencing performance (B = 1.23, 95% CI = 0.08-2.38, p < .05), and active WMT (compared to sham WMT) improved back-digit task performance (B = 1.53, 95% CI = 0.02-3.05, p < .05), combining interventions worsened the effect of each on a back-digit task (B = -3.01, 95% CI = -5.96, -0.052, p < .05).

CONCLUSIONS

These preliminary findings indicate potential iatrogenic effects of combining rTMS and this working memory training intervention and underscore the need for rigorous evaluation of substance specific conceptual frameworks when selecting future combination interventions.

IMPLICATIONS

Counter to hypothesis, this study found no additional benefit of adding a working memory training program to a rTMS protocol in a sample of daily smokers. The combination condition (active rTMS + active training) resulted in worse performance on a delay to smoking analog task and a measure of working memory performance compared to delivering either intervention alone. These preliminary findings inform strategies for optimizing rTMS in smokers and highlight the need for future studies to consider several key components of candidate combination interventions, including effects on regulation of substance use.

CLINICAL TRIAL REGISTRATION (IF ANY)

The trial was registered at ClinicalTrials.gov (NCT03337113).

Decreased excitability of leptin-sensitive anterior insula pyramidal neurons in a rat model of compulsive food demand

Compulsive eating is an overlapping construct with binge eating that shares many characteristics with substance use 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 intermittent access to a preferred diet. These findings warrant further study of whether behavioral economics analysis of compulsive eating can impact disordered eating outcomes in humans and of the translational relevance of a leptin-sensitive anterior insular circuit implicated in these behaviors.

Applications of operant demand to treatment selection II: Covariance of evidence strength and treatment consumption

Evidence-based practices (EBPs) are a critical component of effective and ethical service delivery. Clinicians in the behavioral sciences regularly advocate for the use of therapies and interventions based on the strength and breadth of scientific evidence. However, caregiver choices related to specific behavior therapies are seldom based solely on the degree (or the presence) of scientific evidence. This study applied methods from the Operant Demand Framework to characterize caregiver choices when concurrently available behavior therapies varied in terms of unit price and levels of evidence. Four Hypothetical Treatment Purchase Tasks were designed to evaluate how relative differences in scientific evidence between behavior therapies influenced the demand for, and substitutability of, EBPs. Results from 106 caregivers recruited from the Amazon Mechanical Turk platform indicated that low-, moderate-, and high-evidence treatment choices all functioned as substitutes for a high-evidence (i.e., well-established) behavior therapy. A main effect was observed for the level of evidence, whereby the strength of evidence appeared to moderate the degree to which respective treatments functioned as substitutes. These results extend the literature on the factors associated with treatment choices, and specifically, highlight how differences in the degree of scientific evidence influence choice when deciding between behavior therapies. These results are discussed in the context of more effectively advocating for the use of EBPs with mainstream and lay audiences.

Hidden equivalence in the operant demand framework: A review and evaluation of multiple methods for evaluating nonconsumption

Operant translations of behavioral economic concepts and principles have enhanced the ability of researchers to characterize the effects of reinforcers on behavior. Operant behavioral economic models of choice (i.e., Operant Demand) have been particularly useful in evaluating how the consumption of reinforcers is affected by various ecological factors (e.g., price, limited resources). Prevailing perspectives in the Operant Demand Framework are derived from the framework presented in Hursh and Silberberg (2008). Few dispute the utility of this framework and model, though debate continues regarding how to address the challenges associated with logarithmic scaling. At present, there are competing views regarding the handling of nonconsumption (i.e., 0 consumption values) and under which situations that alternative restatements of this framework are recommended. The purpose of this report was to review the shared mathematical bases for the Hursh and Silberberg and Koffarnus et al. (2015) models and how each can accommodate nonconsumption values. Simulations derived from those featured in Koffarnus et al. were used to conduct tests of equivalence between modeling strategies while controlling for interpretations of residual error as well as the absolute lower limit. Simulations and proofs were provided to illustrate how neither the Hursh and Silberberg nor Koffarnus et al. models can characterize demand at 0 and how both ultimately arrive at the same upper and lower limits. These findings are discussed, and recommendations are provided to build consensus related to zero consumption values in the Operant Demand Framework.

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.

Extending stimulus preference assessment with the operant demand framework

This study extended earlier research on stimulus preference (SP) and reinforcer efficacy (RE) using the behavioral economic concept of elasticity. The elasticity of demand for different items can be used to simultaneously compare RE across stimuli and schedules of reinforcement. Highly preferred stimuli were identified via SP assessments and evaluated using progressive-ratio reinforcer assessments. Reinforcers were then evaluated across the ranges of elasticity in individual reinforcer evaluations. Results indicated that schedules associated with the ranges of elasticity (e.g., inelastic vs. elastic) corresponded with rates of the targeted behavior (i.e., work) and these trends were consistent with behavioral economic predictions. These findings encourage further inquiry and replication of operant demand methods to identify potential boundary conditions for stimuli identified using SP assessments. Discussion is provided regarding the efficiency of reinforcer assessment and the utility of schedules found to exist in the elastic and inelastic ranges.

Using Demand Curves to Quantify the Reinforcing Value of Social and Solitary Drinking

BACKGROUND

Young adults typically drink in social settings and report high levels of episodic heavy drinking despite a range of adverse consequences. Behavioral economics posits that this may reflect a reinforcer pathology in which alcohol is overvalued relative to other reinforcers. Theoretically, the value of alcohol is related to both the direct pharmacological effects of alcohol (euphoria, sedation) and the associated social reinforcement, but to date no studies have differentiated the value of social vs. solitary drinking. The current study examines two modified hypothetical alcohol purchase tasks (APTs), one explicitly social and one explicitly solitary, in order to quantify the reward value of social vs. solitary drinking and to determine whether there are unique clinical correlates of solitary alcohol demand.

METHODS

Participants were young adults (N = 274, Mage  = 25.15, SD = 4.10) recruited from Mturk and from a university subject pool. Participants completed a solitary and social APT, in addition to measures of alcohol consumption and problems.

RESULTS

Participants reported significantly greater demand in the social APT compared to the solitary APT across all demand indices. Elevated solitary and social demand were associated with elevated levels of alcohol use and problems. Using a residualized change approach, solitary demand amplitude (maximum consumption and expenditure) and persistence (price sensitivity) contributed additional variance above and beyond their social APT composite counterparts in predicting typical drinks per week and the self-care, academic/occupational, and physical dependence subscales of the YAACQ.

CONCLUSIONS

The presence of peers increases alcohol demand compared to a solitary scenario, and greater relative solitary drinking demand may be a risk factor for greater alcohol consumption and problems.

Behavioral economics and coping-related drinking motives in trauma exposed drinkers: Implications for the self-medication hypothesis

Behavioral economic theory can help researchers understand complex behavior by considering the availability and economic value associated with an individual's choices. This study explored how behavioral economic constructs relate to alcohol consumption and alcohol problems in a sample of trauma-exposed young adults. We further explored whether these behavioral economic constructs explained unique variance in alcohol outcomes beyond coping-related drinking motives. Participants were 91 trauma-exposed young adults who reported recent alcohol consumption (M_age = 26.53, female = 36.26%, non-White = 41.75%). Participants were recruited through Amazon Mechanical Turk. Questionnaires measured alcohol consumption, problems, and motives for use, as well as alcohol demand, delay discounting, future orientation, and access to environmental reward. Future orientation (ΔR2 = .05, p = .03) and delay discounting (ΔR2 = .04, p = .05) explained unique variance in alcohol problems after controlling for coping-related drinking motives. Further, alcohol demand indices (ΔR2s = .04-.10, ps = .00-.05) explained unique variance in alcohol consumption after controlling for coping-related drinking. Both coping motives and behavioral economic variables contribute to alcohol consumption and alcohol-related consequences among trauma-exposed young adults. Findings suggest that, beyond coping motives, behavioral economics may play a meaningful role in understanding alcohol misuse. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

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

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

An Evaluation of Operant Behavioural Economics in Functional Communication Training for Severe Problem Behaviour

Objective: This single-case experiment examined the use of behavioural economic concepts in a function-based treatment for problem behaviour. Methods: Behavioural economic analyses were used to evaluate the strength of functions of problem behaviour and this information was used to inform elements of function-based treatment for one child with a neurodevelopmental disorder. Results: Findings from this experiment indicated that the incorporation of behavioural economic measures resulted in positive treatment effects that were maintained throughout all phases of the evaluation, including those implemented by caregivers. Conclusions: These results suggest that behavioural economic concepts and procedures can be successful adjuncts to evidence-based assessments and treatments for problem behaviour.

Bidding for delayed rewards: Accumulation as delay discounting, delay discounting as regulation, demand functions as corollary

In the accumulation paradigm animals press one manipulandum to accumulate pellets or seconds of access to food, and then press another manipulandum, or run some distance, to collect it. The accumulation may be interpreted as delay discounting, with the animals adjusting the distal amount to compensate for its distance or delay. The amount accumulated before being collected is a linear function of the distance or time that the experimental paradigm stipulates for collecting it. That linear function follows from the Unit-Price/Unit-Amount axiom. The inverse of the linear compensation functions gives a delay-discount hyperbola. The advantages of the accumulation paradigm and analytic framework for delay discounting studies are noted. Compensation functions are then derived from a behavioral regulation model, which generalizes them to contexts where the individual's budget for response cost becomes over-taxed. In turn, such compensation/regulation models lead directly to representative demand functions. In sum, regulation models provide a theoretical grounding for demand functions, compensation functions, and delay discounting hyperbolas. The parameter that links them is the unit amount k, the slope of the compensation function and of the discount function, the setpoint for consumption in a regulation model, and the ideal quantity consumed at minimal price in a demand analysis.

Furthering Open Science in Behavior Analysis: An Introduction and Tutorial for Using GitHub in Research

Open and transparent practices in scholarly research are increasingly encouraged by academic journals and funding agencies. Various elements of behavior analytic research are communicated transparently, though it is not common practice to archive study materials to support future replications. This tutorial presents a review of the Transparent and Open Practices guidelines provided by the Open Science Foundation and provides instructions on how behavior analysts can use GitHub transparency in research across multiple levels. GitHub is presented as a service that can be used to publicly archive various elements of research and is uniquely suited to research that is technical, data driven, and collaborative. The GitHub platform is reviewed, and the steps necessary to create an account, initialize repositories, archive study files, and synchronize changes to remote repositories are described in several examples. Implications of increased calls for transparency and modern statistical methods are discussed with regard to behavior analysis, and archiving platforms such as GitHub are reviewed as one means of supporting transparent research.

The R package beezdemand: Behavioral Economic Easy Demand

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

Replication Research, Publication Bias, and Applied Behavior Analysis

The "replication crisis" describes recent difficulties in replicating studies in various scientific fields, most notably psychology. The available evidence primarily documents replication failures for group research designs. However, we argue that contingencies of publication bias that led to the "replication crisis" also operate on applied behavior analysis (ABA) researchers who use single-case research designs (SCRD). This bias strongly favors publication of SCRD studies that show strong experimental effect, and disfavors publication of studies that show less robust effect. The resulting research literature may unjustifiably inflate confidence about intervention effects, limit researchers' ability to delineate intervention boundary conditions, and diminish the credibility of our science. To counter problems of publication bias in ABA, we recommend that journals that publish SCRD research establish journal standards for publication of noneffect studies; that our research community adopt open sharing of SCRD protocols and data; and that members of our community routinely publish systematic literature reviews that include gray (i.e., unpublished) research.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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