Exploring the impact of coherence (through the presence versus absence of feedback) and levels of derivation on persistent rule-following

Colin Harte, Dermot Barnes-holmes, Yvonne Barnes-holmes, Ciara McEnteggart

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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.

Original languageEnglish
Pages (from-to)1-18
Number of pages18
JournalLearning & Behavior
Issue number0
Early online date15 Jul 2020
Publication statusE-pub ahead of print - 15 Jul 2020


  • Coherence
  • Derivation
  • HDML
  • Persistent rule-following
  • RFT

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