Association for Behavior Analysis International

Behavior analysis provides a framework to understand how behavior emerges and is maintained in dynamic environments. This poster extends these principles to verbal interactions, framing them as behavior-environment interactions shaped by selection and adaptation. Like other forms of behavior, verbal interactions can be examined through established behavioral concepts such as matching and resurgence, offering fresh insights into communication dynamics. Grounded in evolutionary biology, this analysis investigates how verbal behavior adapts to environmental and social influences, including the actions of conversational partners. By taking a molar, multiscale perspective (Baum, 2018), this work builds on Skinner’s foundational ideas from Selection by Consequences (1981) and Verbal Behavior (1957), emphasizing the parallels between verbal and nonverbal behavior. By analyzing verbal interactions within an evolutionary framework, this poster highlights the adaptive nature of communication and the pivotal role of environmental and social factors in shaping verbal behavior. This approach broadens our understanding of how language evolves and functions within social contexts.

Behavior analysts have noted concerns about the acceptability of behavioral treatments among the public and a subsequent lack of implementation. One factor that may influence acceptability is the conceptual framework implicit in the described treatment. Studies that have evaluated conceptual frameworks have often manipulated treatment activities simultaneously, surveyed only undergraduate students, and were largely published between the late 1960s and 80s. This study sought to provide a current and isolated evaluation of conceptual framework on acceptability ratings of psychological treatment descriptions among the public. Participants were adults in the US recruited via Prolific. Using a between-groups design (n=95), we presented brief vignettes describing symptoms of anxiety and depression and subsequent proposed treatments that were described from either a behavioral or cognitive conceptual framework. Participants completed the Treatment Acceptability Questionnaire after each vignette. All vignettes were rated as acceptable. There were no appreciable differences in the rated acceptability of interventions described from either a behavioral or a cognitive conceptual framework. Results suggest that conceptual framework may not influence treatment acceptability ratings.

With commercial and healthcare applications of Artificial Intelligence proliferating, the question of whether Artificial Intelligence can add value to the practice of Applied Behavior Analysis exists. Presented here are preliminary data of Artificial Intelligence as it is applied to common concerns presented to or encountered by Behavior Analysts in daily practice. Queries like "how do I help my child sleep better", "my child only eats french fries", or "how can I help my client distinguish between different colors" were submitted to an Artificial Intelligence engine. A collection of the queries presented to the Artificial Intelligence engine by Board Certified Behavior Analysts was analyzed. A collection and analysis of the output or responses presented by the Artificial Intelligence engine was analyzed and scored on a four-point rubric for quality. Early data suggest that Artificial Intelligence can add value to the practice of Applied Behavior Analysis in the form of a job tool for Behavior Analysts or where no resources were available, a possible option for consumers seeking help. No Artificial Intelligence "hallucinations" occurred. Useful, practical information was provided to the vast majority of queries submitted. These data are encouraging. Future directions are discussed.