Exploring the potential impact of relational coherence on persistent rule-following: The first study

Abstract

Rule-governed behavior and derived relational responding have both been identified as important variables in human learning. 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 explored the impact of one of these variables, level of derivation, on persistent rule-following and implicated another, coherence, as possibly important. However, no research to date has examined the impact of coherence on persistent rule-following directly. Across two experiments, coherence was manipulated through the systematic use of performance feedback, and its impact was examined on persistent rule-following. A training procedure based on the implicit relational assessment procedure (IRAP) was used to establish novel combinatorially entailed relations that manipulated the feedback provided on the trained relations (A-B and B-C) in Experiment 1, and on the untrained, derived relations (A-C) in Experiment 2. One of these relations was then inserted into the rule for responding on a subsequent contingency-switching match-to-sample (MTS) 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. Specifically, participants in the Feedback group resurged back to the original rule for significantly more responses after demonstrating contingencysensitive responding than did the No Feedback group, after the contingency reversal. The results highlight the subtle complexities that appear to be involved in persistent rule-following in the face of reversed reinforcement contingencies.

Exploring a Training IRAP as a single participant context for analyzing reversed derived relations and persistent rule‐following

“…Following the rule was initially reinforced but the contingencies subsequently reversed and thus the rule now specified a direct contingency that no longer applied. This study and others that followed provided evidence that rules involving derived relations could override the impact of contact with direct contingencies (Bern et al, 2020; Harte et al, 2018; Harte, Barnes‐Holmes, Barnes‐Holmes, McEnteggart et al, 2020).…”

“…The Derivation Pretraining Task. An adapted version of the Derivation Pretraining Task employed by Harte, Barnes‐Holmes, Barnes‐Holmes, McEnteggart et al (2020) was employed. Harte et al noted that pretraining appeared to reduce attrition in the context of persistent rule‐following, and thus, it was employed in the current series of experiments (although Experiment 1 did not examine persistent rule‐following, the pretraining was employed to maintain procedural integrity across subsequent experiments).…”

“…Recent attempts to bridge the gap between these two research areas have involved training and testing a simple relational network and inserting a derived element of that network into a rule for responding on a contingency‐switching MTS task. The critical measures involved determining the extent to which participants would persist with the derived rule when the contingencies switched and were thus inconsistent with that rule (e.g., Harte et al, 2017, 2018; Harte, Barnes‐Holmes, Barnes‐Holmes, McEnteggart et al, 2020). Experiments 2 and 3 reported here employed the derived (persistent) rule‐following paradigm developed by (Harte et al, 2017, 2018; Harte, Barnes‐Holmes, Barnes‐Holmes, McEnteggart et al, 2020) to determine if flexibility in reversing the derived A‐C relations in Experiment 1 would generalize in a persistent rule‐following context.…”

“…Later in the current article, we will argue that persistent rule‐following in the face of competing reinforcement contingencies may be usefully interpreted as evaluating the various properties (in this case coherence) of two relational networks; specifically, the derived rule provided within the experiment versus the rule generated by direct exposure to the task contingencies. Finally, it is again worth noting that unlike previous research in this area (i.e., Bern et al, 2020; Harte et al, 2017, 2018; Harte, Barnes‐Holmes, Barnes‐Holmes, McEnteggart et al, 2020), the current study employed single‐case experimental designs in order to demonstrate high levels of behavioral prediction and influence.…”

“…The experiments reported in the current study aimed to address this question. In conducting this work, we adopted a methodology (a training version of the implicit relational assessment procedure [IRAP] 1 ), similar to that employed by Harte and colleagues (e.g., 2018; Harte, Barnes‐Holmes, Barnes‐Holmes, McEngeggart et al, 2020) for training and testing, and then reversing and retesting the relevant derived relations. We opted to use this methodology because this recent work had successfully demonstrated that derived rules could indeed override direct reinforcement contingencies, at least for a limited number of trials.…”