Recent developments in relational frame theory (RFT) have outlined a number of key variables of potential importance when analyzing the dynamics involved in derived relational responding. Recent research has begun to explore the impact of a number of these variables on persistent rule-following, namely, levels of derivation and coherence. However, no research to date has systematically examined the impact of coherence on persistent rule-following at varying levels of derivation. Across two experiments, the impact of coherence (manipulated through the systematic use of performance feedback) was explored on persistent rule-following when derivation was relatively low (Exp. 1) and high (Exp. 2). A training protocol based on the implicit relational assessment procedure (IRAP) was used to establish novel combinatorially entailed relations that manipulated the feedback provided on the untrained, derived relations (A-C) for five blocks of trials in Experiment 1 and one block of trials in Experiment 2. One of these relations was then inserted into the rule for responding on a subsequent contingency-switching match-to-sample task to assess rule persistence. While no significant differences were found in Experiment 1, the provision or non-provision of feedback had a significant differential impact on rule persistence in Experiment 2. These differences, and the subtle complexities that appear to be involved in persistent rule-following in the face of reversed reinforcement contingencies, are discussed.
Keywords: Coherence; Derivation; HDML; Persistent rule-following; RFT.