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.

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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.