Optimizing Dimensions of Reinforcement to Enhance Behavioral Interventions

Project Summary/Abstract Over 2 million people in the United States with intellectual and developmental disabilities (IDD) engage in some form of severe problem behavior (SPB; self-injury, aggression; Crocker et al., 2006). Behavioral treatments for SPB are predicated on identifying effective reinforcers that increase appropriate behavior and

maintain low levels of SPB. Unfortunately, the reinforcing efficacy of putative reinforcers identified using typical clinical approaches often diminish over time or are not suitable for varied real-world application (e.g., Roane et al., 1998). There are important dimensions of reinforcement that have been discovered in basic behavioral

research that have not yet been translated into applied practice. Such dimensions move beyond simple measures of relative reinforcing value typically assayed in clinical domains via stimulus preference assessments (Fisher et al., 1992) and related methodologies (e.g.; Lee et al., 2008; Leon et al., 2021;

Hagopian et al., 2020), and instead focus on the conditions under which, and how quickly, the effects of reinforcement are established, maximized, and diminished. These dimensions of reinforcement interact with schedule arrangements and response requirements to yield patterns of schedule performance that ultimately

determine the conditional effectiveness of a given reinforcer on which behavioral interventions may be predicated. We posit that a multivariate analysis of these dimensions can enhance our understanding of the stimulus properties of various reinforcers and operant contingencies used within behavioral interventions for

SPB. This may allow practitioners to disentangle relative reinforcer value from variables related to sensorimotor performance and changes in motivation related to time, satiation, and other factors. Based on our recent research findings, pilot assessment data, and clinical experience, this proposal describes an enhanced

methodology leveraging a quantitative model of schedule performance (Mathematical Principles of Reinforcement; Killeen, 1994) to identify effective and durable reinforcers for use within behavioral interventions using a translational-treatment approach. In addition to the practical benefits of identifying more

effective and durable reinforcers, this work will also advance knowledge on the underpinnings of response strength and behavioral persistence of schedule-controlled behavior, which will have scientific value. Using a translational-treatment approach, we will seek to identify (1) specific schedule arrangements that maximize

responding (which directly impacts interventions predicated on response competition) and (2) reinforcers that are associated with minimal resurgence (i.e., the recurrence of a previously eliminated response when the reinforcement conditions for an alternative response are worsened) following reinforcement omission errors.