Extending stimulus preference assessment with the operant demand framework

Reinforcer value moderates response magnitude and persistence during extinction: A randomized trial

Extinction bursts, or temporary increases in rates and intensities of behavior during extinction, can preclude the inclusion of extinction in intervention packages meant to suppress severe challenging behavior. To identify underlying behavioral mechanisms responsible for response persistence and bursting, 69 adults with developmental disabilities completed a low-stakes translational investigation employing a 2 × 2 factorial, crossed, and randomized matched blocks design, with batched randomization logic. In each of the four test groups, we made distinct antecedent manipulations with two value parameters commonly studied through behavioral economics (i.e., demand intensity, Pmax) and evaluated the extent to which each of these manipulations influenced target responding during extinction. Although we found statistically significant differences attributable to both parameters, variations in reinforcer consumption relative to demand intensity were most influential across all dependent variables. This outcome implicates consumption relative to demand intensity as both a mitigating and exacerbating preextinction factor that influences the prevalence of adverse collateral extinction effects (e.g., bursts).

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.

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.