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.

功能分析 (FA) 方法的出现为改进基于功能的行为干预和最终的客户结果铺平了道路。行为分析师主要依靠视觉检查来解释 FA 结果。然而，文献表明，评估者之间的解释可能会有所不同，从而导致观察者间一致性 (IOA) 不佳。为了提高解释的客观性并解决 IOA 问题，Hagopian 等人。创建视觉检查标准。他们报告了改进的 IOA，以及标准限制。在此之后，Roane 等人。修改了这些标准。当前项目描述了开发决策支持系统以协助 FA 解释的第一步。具体来说，我们创建了一个用 R 编写的计算机脚本，旨在评估 FA 数据并根据 Roane 等人的方法生成结果（分配函数）。标准。经验丰富的人类评估者与计算机脚本结果之间的平均一致性为 81%。我们讨论了标准限制（例如，模糊的规则）、研究意义以及对该主题进一步研究的意义。