A Survey-Based Method to Evaluate Optimal Treatment Selection for Escape-Maintained Problem Behavior

Abstract

Geiger, Carr, and LeBlanc (2010) developed a decision-making model for escape-maintained problem behavior that could be used to guide the course of treatment selection. We used a digital survey to evaluate the model's potential usefulness. We presented novice and expert practitioners' written hypothetical scenarios and asked them to determine the optimal treatment in a given situation. Some participants were given the model, whereas others were instructed to use their best clinical judgment. Using logistic regression analyses, the general findings for our scenarios were the following: (a) experts without the aid of a decision model had better odds of selecting the optimal treatment than novices without the decision model, (b) experts with the decision model did not have greater odds of selecting optimal treatment than experts without the model, and (c) novices with the decision model did not have better odds of selecting the optimal treatment than novices without the decision model.Keywords Clinical decision-making . Escape-maintained problem behavior . Treatment models Social negative reinforcement, typically in the form of escape from instructions, has been reported to be the most common function of problem behavior for individuals with intellectual disabilities (Beavers, Iwata, & Lerman, 2013). Escape-maintained problem behavior might be especially prevalent in classroom settings where instructional tasks are given frequently (Lloyd, Weaver, & Staubitz, 2016). Classroom and school settings might also represent an environment where many behavior analysts practice or consult (Sugai et al., 2000). When escape is identified as a maintaining variable of problem behavior via functional analysis, the behavior analyst must determine the most appropriate course of function-based treatment. As noted by Geiger, Carr, and LeBlanc (2010), numerous functionbased interventions for problem behavior maintained by escape have been researched and implemented to good effect in routine clinical practice. These interventions are highly amenable to classroom settings and include, but are not limited to, (a) activity choice (e.g., Dyer, Dunlap, & Winterling, 1990), (b) curricular and instructional revision Bullet-Point Summary • Decision trees are simple, yet powerful, forms of multiple variable analyses that might be useful for behavior analysts in practice. However, their effectiveness may differ for novice and expert behavior analysts.• Geiger et al.'s (2010) decision tree was most useful for novice behavior analysts when hypothetical clinical scenarios were made simple.• Novice behavior analysts tend not to make optimal treatment decisions when hypothetical clinical scenarios increase in complexity.• Geiger et al.'s (2010) decision tree did not significantly change or influence treatment selection for expert behavior analysts.• Expert behavior analysts' treatment selections may be in line with optimal treatment without the aid of a decision-making model.• Decision trees might not be a suitable replacement for appropriat...

A Decision-Making Tool for Evaluating and Selecting Prompting Strategies

“…An important next step after developing a decision-making tool is to determine its ease of use, or the usability of the tool, by behavior analysts when they apply the tool to their work. Both the usability and utility of this decision-making tool was further evaluated in subsequent studies (Hoffmann et al, 2020 ; Saini et al, 2017 ), providing support for the benefits that such tools may offer behavior analysts when selecting interventions for their clients.…”