Modeling Subtypes of Automatically Reinforced Self-Injurious Behavior with the Evolutionary Theory of Behavior Dynamics

The subtypes of automatically reinforced self-injurious behavior (ASIB) delineated by Hagopian and colleagues (Hagopian et al., 2015; 2017) demonstrated how functional-analysis (FA) outcomes may predict the efficacy of various treatments. However, the mechanisms underlying the different patterns of responding obtained during FAs and corresponding differences in treatment efficacy have remained unclear. A central cause of this lack of clarity is that some proposed mechanisms, such as differences in the reinforcing efficacy of the products of ASIB, are difficult to manipulate. One solution may be to model subtypes of ASIB using mathematical models of behavior in which all aspects of the behavior can be controlled. In the current study, we used the evolutionary theory of behavior dynamics (ETBD; McDowell, 2019) to model the subtypes of ASIB, evaluate predictions of treatment efficacy, and replicate recent research aiming to test explanations for subtype differences. Implications for future research related to ASIB are discussed.