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Abstract Despite the efficacy of functional analyses in identifying the function of challenging behavior, clinicians report not always using them, partly due to safety concerns. Understanding how researchers employ safeguards to mitigate risks, particularly with dangerous topographies like self‐injurious behavior (SIB), is important to guide research and practice. However, the results of a scoping review of functional analyses of self‐injurious behavior conducted by Weeden et al. (2010) revealed that only 19.83% of publications included protections. We extended the work of Weeden et al. to determine whether reporting has improved. We observed increases in all but two types of protections reviewed by Weeden et al. Additionally, we included new protections not reported by Weeden et al. In total, 69.52% of the studies included at least one protective procedure and 44.39% specified that the protections were used for safety. It appears that reporting has increased since Weeden et al. called for improved descriptions of participant protections.

Abstract Behavior analysts have much to offer nonbehavioral professionals who work with the communities that we serve. Successful dissemination of behavior‐analytic technologies to these professionals could potentially improve their practice. Although the literature contains some exemplary examples of successful dissemination, our discipline would benefit from a blueprint for conducting this important work. In this article, I share our experiences disseminating behavioral technologies to educators, law enforcement officers, and health care providers who engage with neurodiverse individuals. These experiences form the basis of a recommended blueprint for dissemination, which awaits empirical support. After describing this tentative blueprint, I provide suggestions for future research on how best to disseminate our technologies to nonbehavioral professionals, the ideal content of those dissemination activities, and the conditions under which professionals may be more likely to embed our technologies into their best practices.

Abstract Literature concerning operant behavioral economics shows a strong preference for the coefficient of determination ( R 2 ) metric to (a) describe how well an applied model accounts for variance and (b) depict the quality of collected data. Yet R 2 is incompatible with nonlinear modeling. In this report, we provide an updated discussion of the concerns with R 2 . We first review recent articles that have been published in the Journal of the Experimental Analysis of Behavior that employ nonlinear models, noting recent trends in goodness‐of‐fit reporting, including the continued reliance on R 2 . We then examine the tendency for these metrics to bias against linear‐like patterns via a positive correlation between goodness of fit and the primary outputs of behavioral‐economic modeling. Mathematically, R 2 is systematically more stringent for lower values for discounting parameters (e.g., k ) in discounting studies and lower values for the elasticity parameter (α) in demand analysis. The study results suggest there may be heterogeneity in how this bias emerges in data sets of varied composition and origin. There are limitations when using any goodness‐of‐fit measure to assess the systematic nature of data in behavioral‐economic studies, and to address those we recommend the use of algorithms that test fundamental expectations of the data.

Abstract 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, P max ) 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).

Abstract Many researchers have tackled the question of how behavior is influenced by its outcomes. Some have adopted a nonmechanistic (functional) perspective that attempts to describe the influence of outcomes on behavior. Others have adopted a mechanistic (cognitive) perspective that attempts to explain the influence of outcomes on behavior. Orthogonal to this distinction, some have focused on the influence of outcomes that a behavior had in the past, whereas others also consider the influence of outcomes that a behavior might have in the future. In this article, we relate these different perspectives with the goal of reducing misunderstandings and fostering collaborations between researchers who adopt different perspectives on the common question of how behavior is influenced by its outcomes.

Abstract The literature offers few recommendations for sequencing exposure to treatment conditions with individuals with multiply maintained destructive behavior. Identifying relative preference for the functional reinforcers maintaining destructive behavior may be one means of guiding that decision. The present study presents a preliminary attempt at developing a robust relative preference and reinforcer assessment for individuals with multiply maintained destructive behavior. Guided and free‐choice trials were implemented in which participants chose between two multiple‐schedule arrangements, each of which programmed signaled periods of isolated reinforcer availability and unavailability. Consistent participant choice and responding during free‐choice trials was then used to thin the corresponding schedule of reinforcement. The results demonstrated a strong preference for one of the two functional reinforcers for all four participants, yet preferences differed across participants and were not well predicted by responding in prior analyses.

Abstract Although scientific endeavors strive to be objective, they are the work of individuals whose unique perspectives and experiences influence their research and interpretations of the world and data. Much has been said and written lately about the need to embed cultural responsiveness in behavior analysis and the need to enhance diversity in the field. In fact, similar conversations are taking place in many areas of science. Despite the current buzz, many behavioral researchers may be left wondering what they can do or whether it is incumbent on them to act. For the field of behavior analysis to move toward adopting the values of diversity, equity, inclusion, and access, members of the scientific community must actively engage in behaviors that foster inclusive and safe learning environments for students, engage in collaborative work, and incorporate culturally responsive research and mentorship practices. This article will describe some current practices, showcase exemplars of culturally responsive research and mentorship, and provide resources for researchers and mentors.

Abstract Behavioral momentum theory (BMT) provides a theoretical and methodological framework for understanding how differentially maintained operant responding resists disruption. A common way to test operant resistance involves contingencies with suppressive effects, such as extinction or prefeeding. Other contingencies with known suppressive effects, such as response‐cost procedures arranged as point‐loss or increases in response force, remain untested as disruptive events within the BMT framework. In the present set of three experiments, responding of humans was maintained by point accumulation programmed according to a multiple variable‐interval (VI) VI schedule with different reinforcement rates in either of two components. Subsequently, subtracting a point following each response (Experiment 1) or increasing the force required for the response to be registered (Experiments 2 and 3 decreased response rates, but responding was less disrupted in the component associated with the higher reinforcement rate. The point‐loss contingency and increased response force similarly affected response rates by suppressing responding and human persistence, replicating previous findings with humans and nonhuman animals when other types of disruptive events (e.g., extinction and prefeeding) were investigated. The present findings moreover extend the generality of the effects of reinforcement rate on persistence, and thus BMT, extending the analysis of resistance to two well‐known manipulations used to reduce responding in the experimental analysis of behavior.

Abstract Basic and retrospective translational research has shown that the magnitude of resurgence is determined by the size of the decrease in alternative reinforcement, with larger decreases producing more resurgence. However, this finding has not been evaluated prospectively with a clinical population. In Experiment 1, five participants experienced a fixed progression of reinforcement schedule‐thinning steps during treatment of their destructive behavior. Resurgence occurred infrequently across steps and participants, and when resurgence did occur, its clinical meaningfulness was often minimal. In Experiment 2, five new participants experienced these same schedule‐thinning steps but in a counterbalanced order. Resurgence occurred most often and was generally largest with larger decreases in alternative reinforcement programmed earlier in the evaluation. Large decreases in alternative reinforcement may be more problematic clinically when they occur earlier in treatment. Whether larger transitions can be recommended in the clinic following the success of smaller ones will require additional research.

Abstract Resurgence refers to the relapse of a target behavior following the worsening of a source of alternative reinforcement that was made available during response elimination. Most laboratory analyses of resurgence have used a combination of extinction and alternative reinforcement to reduce target behavior. In contingency‐management treatments for alcohol use disorder, however, alcohol use is not placed on extinction. Instead, participants voluntarily abstain from alcohol use to access nondrug alternative reinforcers. Inasmuch, additional laboratory research on resurgence following voluntary abstinence is warranted. The present experiment evaluated resurgence of rats' ethanol seeking following voluntary abstinence produced by differential reinforcement of other behavior (DRO). Lever pressing produced ethanol reinforcers during baseline phases. During DRO phases, lever pressing continued to produce ethanol and food reinforcers were delivered according to resetting DRO schedules. Ethanol and food reinforcers were suspended during resurgence test phases to evaluate resurgence following voluntary abstinence. Lever pressing was elevated during baseline phases and occurred at near‐zero rates during DRO phases. During the resurgence test phases, lever pressing increased, despite that it no longer produced ethanol. The procedure introduced here may help researchers better understand the variables that affect voluntary abstinence from ethanol seeking and resurgence following voluntary abstinence.