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

Abstract

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.

Interpretation(s) of essential value in operant demand

“…This framework, an experimental translation of microeconomics, has been used by various teams to explore how an operant behavioral economic account can be extended to choices related to health outcomes (e.g., Bickel et al, 2016; Reed et al, 2022; for a review, see Hursh, 2000), the consumption of addictive substances (e.g., Acuff et al, 2020; Amlung et al, 2015; González‐Roz et al, 2019), and other forms of risky or unsafe choices, such as unprotected sexual behavior (Harsin et al, 2021; Strickland et al, 2020) or nonadherence to prescribed medication regimens (Jarmolowicz et al, 2020). This approach has also been directed to various other forms of health and wellness initiatives, such as COVID‐19 vaccination (Hursh et al, 2020; Strickland et al, 2022), healthy tanning practices (Becirevic et al, 2017; Reed et al, 2016), and choices related to behavioral therapies (e.g., demand for evidence‐based practices; Gilroy et al, 2022; Gilroy & Feck, 2022; Gilroy & Picardo, 2022) and the reinforcing effects of elements included in such therapies (e.g., schedules of reinforcement; Gilroy, Ford, et al, 2019; Gilroy, Waits, et al, 2021).…”

Social media sites users' choice between utilitarian and informational reinforcers assessed using temporal discounting

“…Although studies have recently been published that apply the concepts of utilitarian and informational reinforcement in behavior analysisbased therapy contexts, smartphone and social network dependence behaviors have not yet been taken into account. Therefore, the present study aims to contribute to the growing literature on IR in economic research (47,48). Extant research has primarily focused on the exploration of smartphone dependence (16,49,50).…”