Toward an Automation of Functional Analysis Interpretation: A Proof of Concept

Abstract

The advent of functional analysis (FA) methodology paved the way for improved function-based behavioral interventions and ultimately client outcomes. Behavior analysts primarily rely on visual inspection to interpret FA results. However, the literature suggests interpretations may vary across raters resulting in poor interobserver agreement (IOA). To increase interpretation objectivity and address IOA issues, Hagopian et al. created visual-inspection criteria. They reported improved IOA, alongside criteria limitations. Following this, Roane et al. modified these criteria. The current project describes the first steps toward developing a decision support system to assist in FA interpretation. Specifically, we created a computer script, written in R, designed to evaluate FA data and produce an outcome (assign function) based on the Roane et al. criteria. Average agreement between experienced human raters and the computer script outcomes was 81%. We discuss criteria limitations (e.g., vague rules), study implications, and the significance of further research on this topic.