Relational Frame Theory (RFT)

This chapter considers how the ability to relationally frame sets the stage for the emergence of language and how the former's generative and flexible nature accounts for much of the latter's utility. It also highlights how relational framing rapidly increases in both scale and complexity, expanding from the relating of individual stimuli to the relating of relational networks to other networks. The chapter describes the notion of “cognition” and considers how different types and properties of relational framing play a role in perspective-taking, intelligence, and implicit cognition. It concludes by providing a brief overview of the key achievements of relational frame theory (RFT) research to date.

This chapter introduces the origins of, as well as arguments and evidence for, relational frame theory (RFT). It presents the study of arbitrarily applicable relational responding (AARR) to its historical roots and explains why this phenomenon has occupied the attention of behavioral scientists for over 40 years now. The chapter highlights a number of features of relational responding that becomes important when linking RFT to language and cognition later on. It examines how RFT carves this type of operant behavior into two different varieties (nonarbitrarily and arbitrarily applicable) and discusses how the latter may not only provide an explanation for stimulus equivalence, but for other types of derived stimulus relations as well.

Learning can be defined functionally as the impact of regularities in the environment on behavior. The concept of environmental regularities is a crucial part of this definition because it (a) improves the scope and depth of the definition and (b) provides ways to differentiate between different types of learning. We argue that this concept is useful also for conceptualizing learning from the perspective of Relational Frame Theory. More specifically, even if all instances of learning qualify as instances of arbitrarily applicable relational responding, different types of learning could still be functionally different because they involve different types of proximal regularities.

Cognitive neuroscience has developed many approaches to the study of learning that might be useful to functionally oriented researchers, including those from a relational frame theory (RFT) perspective. We focus here on two examples. First, cognitive neuroscience often distinguishes between habit and goal-directed reinforcement learning, in which only the latter is sensitive to proximal changes in behavior-environment contingencies. This distinction is relevant to RFT’s original concerns about how rule-based processes can sometimes render an individual’s behavior maladaptive to changing circumstances.

Relational Frame Theory (RFT) is a contemporary account of language and cognition rooted in behavior analysis. This paper presents a citation analysis of the RFT literature that follows on from that conducted by Dymond, May, Munnelly and Hoon (2010) who examined the evidence base for and impact of RFT between 1991 and 2008. The current analysis focused on Empirical and Non-Empirical studies citing RFT-related search terms and their publishing outlets in the period from 2009 to 2016. An emphasis was placed on Empirical RFT articles, which were organized by frames targeted, country of origin and participant demographics. The analysis revealed 521 papers that met inclusion criteria.

The relational evaluation procedure (REP) is seen by proponents of relational frame theory (RFT) as a useful means by which to assess and train relational responding. Most REP work so far has been conducted with typically developing adults; however, given the importance of relational responding as a repertoire and of the potential utility of the REP for assessing and training this repertoire, researchers need to investigate its use with other populations including children with autism and other developmental delay. The current study presents relevant data.