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

Abstract

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.

Evaluating caregivers arrangement of infant sleeping environments in the home

“…This could have influenced the lack of participation observed. Future investigations could incorporate simulated purchase tasks (e.g., Traxler et al, 2023) to empirically derive the pay schedule and amount of money to be arranged contingent upon arranging safe infant sleeping environments. Finally, our CM arrangement provided a dense schedule of reinforcement with a high-quality reinforcer (i.e., money), and it is unknown whether caregiver performance would continue to be maintained if the schedule was thinned.…”

Cost-inclusive research on health psychology interventions: Why, how, and what next.

“…Many of us may rightly object that when certain third-party funders examine CIR findings, outcomes are not considered seriously, only costs—costs of HPIs we have created, refined, and studied for decades. Many of us also feel remorse if costs are a barrier to the adoption of effective treatments (Traxler et al, 2023). It may be helpful to realize that, although HPIs equivalent in outcomes but lower in costs are preferred by funders, CIR findings can recommend spending more funds on HPIs that have been shown to be more costly but also significantly more effective and beneficial (Gatner et al, 2022; Linehan et al, 1999).…”

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

“…Because of the complexity of the data and models, fitting demand data using log 10 -scaled parameters allows for achieving lower tolerances and better fits to the data (Kaplan et al, 2021;Rzeszutek, Franck et al, 2022;Rzeszutek, Gipson-Reichardt, et al, 2022;Traxler et al, 2022). This does not transform the response variable but only the scale in which the parameter is expressed (and thus, optimized).…”

“…Higher intensity and lower price sensitivity of a substance have been associated with higher levels of substance use (González‐Roz et al, 2019; Martínez‐Loredo et al, 2021; Strickland et al, 2020) and are predictive of treatment outcomes (González‐Roz et al, 2020; Schwartz et al, 2021). While a staple in substance use research, demand can also be used to model various behaviors such as likelihood to deposit money for alcohol treatment (Traxler et al, 2022), public health behaviors during a pandemic (Strickland, Reed, et al, 2022), and demand for various commodities (Schwartz & Hursh, 2022).…”