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

Cannabis demand and use among veterans: A prospective examination

OBJECTIVE

Cannabis demand (i.e., relative value), assessed cross-sectionally via a hypothetical marijuana purchase task (MPT), has been associated with use, problems, and dependence symptoms, among others. However, limited work exists on the prospective stability of the MPT. Furthermore, cannabis demand among veterans endorsing cannabis use, and the prospective cyclical relationship between demand and use over time, have yet to be investigated.

METHOD

Two waves of data from a veteran sample (N = 133) reporting current (past 6-month) cannabis use were analyzed to assess stability in cannabis demand over 6 months. Autoregressive cross-lagged panel models (CLPMs) assessed the longitudinal associations between demand indices (i.e., intensity, Omax, Pmax, breakpoint) and cannabis use.

RESULTS

Baseline cannabis use predicted greater intensity (β = .32, p < .001), Omax (β = .37, p < .001), breakpoint (β = .28, p < .001), and Pmax (β = .21, p = .017) at 6 months. Conversely, baseline intensity (β = .14, p = .028), breakpoint (β = .12, p = .038), and Pmax (β = .12, p = .043), but not Omax, predicted greater use at 6 months. Only intensity demonstrated acceptable prospective reliability.

CONCLUSIONS

Cannabis demand demonstrated stability over 6 months in CLPM models, varying along with natural changes in cannabis use. Importantly, intensity, Pmax, and breakpoint displayed bidirectional predictive associations with cannabis use, and the prospective pathway from use to demand was consistently stronger. Test-retest reliability ranged from good to poor across indices. Findings highlight the value of assessing cannabis demand longitudinally, particularly among clinical samples, to determine how demand fluctuates in response to experimental manipulation, intervention, and treatment. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

E-cigarette Price Impacts legal and Black-Market Cigarette Purchasing Under a Hypothetical Reduced-Nicotine Cigarette Standard

INTRODUCTION

The Tobacco Control Act gives the U.S. Food and Drug Administration authority to establish a reduced-nicotine content standard in combusted cigarettes. This future potential regulation may pose a significant public health benefit; however, black markets may arise to meet demand for normal-nicotine content cigarettes among smokers unwilling to transition to or use an alternative product.

AIMS AND METHODS

We determined the behavioral-economic substitutability of illicit normal-nicotine content cigarettes and e-cigarettes for reduced-nicotine content cigarettes in a hypothetical reduced-nicotine regulatory market. Adult cigarette smokers were recruited online to complete hypothetical cigarette purchasing tasks for usual-brand cigarettes, reduced-nicotine content cigarettes, and illicit normal-nicotine content cigarettes, as well as a cross-commodity task in which reduced-nicotine content cigarettes were available across multiple prices and illicit cigarettes were concurrently available for $12/pack. Participants completed two three-item cross-commodity purchasing tasks in which e-cigarettes were available for $4/pod or $12/pod alongside reduced-nicotine content cigarettes and illicit cigarettes.

RESULTS

Usual-brand cigarette purchasing was greater than illicit normal-nicotine content cigarettes and less than reduced-nicotine content cigarettes. In the cross-commodity purchasing tasks, illicit cigarettes and e-cigarettes both served as economic substitutes for reduced-nicotine content cigarettes; however, when e-cigarettes were available for $4/pod, they were purchased at greater levels than illicit cigarettes and resulted in greater reductions in reduced-nicotine content cigarettes purchasing than when available for $12/pod.

CONCLUSIONS

These data suggest that some smokers are willing to engage in illicit cigarette purchasing in a reduced-nicotine regulatory environment, but e-cigarette availability at lower prices may reduce black-market engagement and shift behavior away from combusted cigarette use.

IMPLICATIONS

E-cigarettes available at low, but not high, prices were stronger substitutes for legal, reduced-nicotine content cigarettes than illegal, normal-nicotine content cigarettes in a hypothetical reduced-nicotine tobacco market. Our findings suggest the availability of relatively inexpensive e-cigarettes may reduce illicit cigarette purchasing and combusted cigarette use under a reduced-nicotine cigarette standard.

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

RATIONALE

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

Hyperbolic modeling and assessment of hypothetical health behaviors during a viral outbreak using crowdsourced samples

The COVID-19 pandemic provided an opportunity to investigate factors related to public response to public health measures, which could help better prepare implementation of similar measures for inevitable future pandemics. To understand individual and environmental factors that influence likelihood in engaging in personal and public health measures, three crowdsourced convenience samples from Amazon Mechanical Turk (MTurk) completed likelihood-discounting tasks of engaging in health behaviors given a variety of hypothetical viral outbreak scenarios. Experiment 1 assessed likelihood of mask wearing for a novel virus. Experiment 2 assessed vaccination likelihood based on efficacy and cost. Experiment 3 assessed likelihood of seeking health care based on number of symptoms and cost of treatment. Volume-based measures and three-dimensional modeling were used to analyze hypothetical decision making. Hypothetical public and personal health participation increased as viral fatality increased and generally followed a hyperbolic function. Public health participation was moderated by political orientation and trust in science, whereas treatment-seeking was only moderated by income. Analytic methods used in this cross-sectional study predicted population-level outcomes that occurred later in the pandemic and can be extended to various health behaviors.

A Comprehensive Systematic Review of Procedures and Analyses Used in Basic and Preclinical Studies of Resurgence, 1970-2020

Resurgence is the return of a previously reinforced response as conditions worsen for an alternative response, such as the introduction of extinction, reductions in reinforcement, or punishment. As a procedure, resurgence has been used to model behavioral treatments and understand behavioral processes contributing both to relapse of problem behavior and flexibility during problem-solving. Identifying existing procedural and analytic methods arranged in basic/preclinical research could be used by basic and preclinical researchers to develop novel approaches to study resurgence, whereas translational and clinical researchers could identify potential approaches to combating relapse during behavioral interventions. Despite the study of resurgence for over half a century, there have been no systematic reviews of the basic/preclinical research on resurgence. To characterize the procedural and analytic methods used in basic/preclinical research on resurgence, we performed a systematic review consistent with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). We identified 120 articles consisting of 200 experiments that presented novel empirical research, examined operant behavior, and included standard elements of a resurgence procedure. We reported prevalence and trends in over 60 categories, including participant characteristics (e.g., species, sample size, disability), designs (e.g., single subject, group), procedural characteristics (e.g., responses, reinforcer types, control conditions), criteria defining resurgence (e.g., single test, multiple tests, relative to control), and analytic strategies (e.g., inferential statistics, quantitative analysis, visual inspection). We make some recommendations for future basic, preclinical, and clinical research based on our findings of this expanding literature.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40614-022-00361-y.

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).

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).

Extra-experimental scarcity impacts hypothetical operant demand: A natural SARS-CoV-2 eperiment

Behavioral economic demand models quantify the extent to which an organism defends its consumption of a commodity. Commodity purchase tasks permit humans a quick yet psychometrically sound approach to assessing commodity demand for various retail products. Operant behavioral economic literature suggests economy type (open vs closed) can significantly alter demand, yet this effect is largely undocumented in the commodity purchase task literature. In this study, we leveraged the market pressures for retail goods (hand lotion and sanitizer; paper towels and toilet paper; soda and water) resulting from SARS-CoV-2 into a natural experiment comparing within-subject demand across two time-points during the pandemic using a crowdsourced approach. Results suggest that hypothetical commodity purchase tasks are sensitive to extra-experimental market pressures (e.g., scarcity due to the closing of economies), adding additional confidence to the self-report nature of purchase task responding and providing further construct validity to these approaches.

Substance-related cross-commodity purchase tasks: A systematic review

OBJECTIVE

In the context of behavioral economics, drug use is a choice to which an individual may allocate responding despite the presence of alternative response possibilities. To examine the demand for a drug in an environment in which other drugs or nondrug alternatives are present, researchers often use a cross-commodity purchase task. These tasks allow participants to make choices across several reinforcers at varied unit prices and may elucidate behavioral economic patterns of substitutability and complementarity. The objective of this study was to conduct a systematic review of cross-commodity purchase task studies with human participants.

METHOD

Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we screened 46 full-text studies (from 456 total records obtained from PsycINFO and PubMed databases and reference list search), yielding a final sample of 35 studies.

RESULTS

The drug category with the largest number of studies assessed was tobacco and nicotine products. The most consistent economic relationships found were substitutability of traditional cigarettes by e-cigarettes and e-liquid, and both legal and illegal cannabis for the other; however, other substitutable and complementary relationships were observed (e.g., substitution of food for cigarettes, a complementary relationship between alcohol and cannabis).

CONCLUSIONS

We discuss the implications of the results of this review from a treatment and harm reduction standpoint, highlight areas for future research particularly among drug categories with few studies and evaluating ecological validity of hypothetical measures, and make best practice recommendations for future cross-commodity drug-related purchase task research. (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.

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.

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).

Validity of a little cigars/cigarillos purchase task in dual users of cigars and cigarettes

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 h at increasing prices. We calculated four observed demand indices: intensity (consumption at $0), breakpoint (price after which consumption reaches 0), O_max (maximum daily expenditure), and P_max (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 P_max 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.

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.

Applications of operant demand to treatment selection III: Consumer behavior analysis of treatment choice

Behavior analysts and psychologists advocate for the use of therapies and strategies based on credible, scientific evidence. Researchers and clinicians regularly advocate for Evidence-based Practices (EBPs) over questionable "alternatives" because caregivers seldom choose interventions based on scientific evidence alone. This study applied methods and concepts from Consumer Behavior Analysis to conduct a reinforcer-based evaluation of the consequences that influence treatment choices. Hypothetical Treatment Purchase Tasks (HTPTs) were designed to evaluate how utilitarian (UR; i.e., the efficacy of treatment) and informational sources of reinforcement (IR; i.e., community support for treatment) jointly influence treatment-related choices. A total of 104 caregivers were recruited using the Amazon Mechanical Turk (MTurk) framework to complete two HTPTs. Results indicated that caregivers overall favored treatments with greater IR over those with greater UR, suggesting that indirect contingencies for treatment choices exerted greater overall influence than the direct contingencies of treatment choices (i.e., efficacy). This finding extends the literature on treatment choice by providing a reinforcer-based perspective on why 'fad', questionable, and pseudoscientific practices can achieve and maintain high levels of adoption by caregivers. This work concludes with a discussion of Consumer Behavior Analysis and how reinforcer-based interpretations of choice can be used to improve efforts to support and advocate for evidence-based child behavior treatments.

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.

Dynamic effects of dietary protein restriction on body weights, food consumption, and protein preference in C57BL/6J and Fgf21-KO mice

Single-case experimental designs (SCEDs) are rarely used in behavioral neuroscience despite their potential benefits. The current study used a SCED to evaluate the effects of dietary protein restriction in C57BL/6J and Fgf21-knockout (KO) mice on body weight, food consumption, and protein preference and changes in those outcome measures were quantified using multilevel linear models. In C57BL/6J mice, rate of weight gain was lower and food consumption and protein preference higher during periods of low (4% kcal) protein diet feeding compared to periods of normal (18% kcal) protein diet feeding. In Fgf21-KO mice, who do not produce the liver-derived hormone FGF21, rate of weight gain and protein preference were not substantially affected by diet although food consumption was slightly higher during periods of low protein diet than periods of normal protein diet. These results demonstrate that protein restriction dynamically regulates physiological and behavioral responses at the individual mouse level and that FGF21 is necessary for those responses. Further, the current results demonstrate how a SCED can be used in behavioral neuroscience research, which entails both scientific and practical benefits.

Applications of operant demand to treatment selection I: Characterizing demand for evidence-based practices

Various treatment approaches have been determined efficacious for improving child behavior outcomes. Despite a variety of evidence-based options, consumers often disregard empirically supported treatments to pursue alternatives that lack empirical support, such as 'fad' therapies. The choice to pursue therapies lacking empirical support has been considered a 'gamble' on therapeutic outcomes and this form of risky choice has historically been explained using various cognitive heuristics and biases. This report translates quantitative analyses from the Operant Demand Framework to characterize how caregivers of children with behavioral issues consume treatment services. The Operant Demand Framework is presented, its utility for characterizing patterns of treatment consumption is discussed, and a preliminary application of cross-price analyses of demand is performed to illustrate how various factors jointly influence treatment-related choice. Results indicated that caregivers endorsing interest in receiving behavioral parent training regularly pursued pseudoscientific alternatives as a functional substitute for an established therapy, despite explicit language stating a lack of evidence. These findings question the presumption of rationality in models of treatment choice and degree to which scientific evidence influences the consumption of therapies. This report concludes with a discussion of Consumer Behavior Analysis and how quantitative analyses of behavior can be used to better understand factors that enhance or detract from the dissemination of evidence-based practices.

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

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

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.