Prevalence of relapse of automatically maintained behavior resulting from context changes

A retrospective analysis of the relation between resurgence and renewal of behavior targeted for reduction

Functional communication training (FCT) is an evidence-based treatment for behavior targeted for reduction that often combines extinction for target responses and arranges functionally equivalent reinforcement for alternative behavior. Long-term effectiveness of FCT can become compromised when transitioning from clinic to nonclinic contexts or thinning reinforcement schedules for appropriate behavior. Such increases in targeted behavior have been conceptualized as renewal and resurgence, respectively. The relation between resurgence and renewal has yet to be reported. Therefore, the present report retrospectively analyzed the relation between renewal and resurgence in data collected when implementing FCT with children diagnosed with developmental disabilities. We found no relation when evaluating all 34 individuals assessed for resurgence and renewal or a subset of individuals exhibiting both resurgence and renewal. These findings suggest that one form of relapse may not be predictive of another form of relapse.

The Promises and Possibilities of Artificial Intelligence in the Delivery of Behavior Analytic Services

Artificial intelligence (AI) has begun to affect nearly every aspect of our daily lives and nearly every industry and profession. Many readers of this journal likely work in one or more areas of behavioral health. For readers who work in behavioral health and who are interested in AI, the purpose of this article is to highlight the pervasiveness of AI research being conducted around many facets of behavioral health service delivery. To do this, we first provide a brief overview of some of the areas within AI and the types of problems each area of AI attempts to solve. We then outline the prototypical client journey in behavioral healthcare beginning with diagnosis/assessment and ending with intervention withdrawal or ongoing monitoring. Next, for each stage in the client journey, we highlight several areas that parallel existing behavior analytic practice where researchers have begun to use AI, often to improve the efficiency of service delivery or to learn new things that improve the effectiveness of behavioral health services. Finally, for those whose appetite has been whet for getting involved with AI, we close by describing three roles they might consider trying out and that parallel the three main domains of behavior analysis. These three roles are an AI tool designer (akin to EAB), AI tool implementer (akin to ABA), or AI tool supporter (akin to practice).

Further evidence of renewal in automatically maintained behavior

Renewal is a relapse phenomenon that refers to the recurrence of a previously reduced behavior following a change in stimulus conditions. Muething et al. (2022) examined the phenomenology of renewal among individuals with automatically maintained challenging behavior treated at an outpatient clinic. We replicated their findings by retrospectively examining renewal across various topographies of automatically maintained behavior treated at an inpatient hospital, and we extended their work by also examining differences across subtypes of automatically maintained self-injurious behavior. The prevalence of renewal was comparable to that observed by Muething et al., supporting the notion that automatically maintained challenging behavior is susceptible to relapse phenomena. Furthermore, renewal was twice as likely to occur for individuals with Subtype 2 versus Subtype 1 self-injurious behavior, providing additional evidence of behavioral differentiation between subtypes. Our findings suggest that even after apparent stability in treatment, practitioners should remain vigilant for the recurrence of automatically maintained behavior during generalization.

Expanding a laboratory model for evaluating relapse of caregiver nonadherence

Caregiver adherence to treatment plans is likely maintained by negative reinforcement and can contact extinction when child responding relapses. When caregiver adherence contacts extinction, caregiver nonadherence, such as reinforcing their child's challenging behavior, relapses, threatening treatment efficacy. Previous laboratory models demonstrating the relapse of caregiver nonadherence only evaluated treatment for behavior maintained by social-positive reinforcement, not that maintained by social-negative reinforcement. These models only measured caregiver nonadherence as discrete events, which cannot capture the magnitude of each error. The present study was an evaluation of the relapse of caregiver nonadherence during simulated treatments for escape-maintained challenging behavior. First, caregivers placed demands in a home-like setting and a research confederate responded to these demands in a manner mimicking clinical clients. Next, caregivers were taught to implement treatment in a clinical setting and the confederate's behavior gradually improved. Last, caregivers returned to the home-like setting and confederate challenging behavior relapsed. Nonadherence relapsed for all caregivers, demonstrating the need for additional research on methods for mitigating caregiver relapse during treatment of children's challenging behavior and the usefulness of the proposed measurement system for future research.