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Erschienen in: Learning & Behavior 2/2021

15.07.2020

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

verfasst von: Colin Harte, Dermot Barnes-Holmes, Yvonne Barnes-Holmes, Ciara McEnteggart

Erschienen in: Learning & Behavior | Ausgabe 2/2021

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Abstract

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.

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Fußnoten
1
An inherent assumption of the HDML framework is that changes in one dimension may involve changes in other dimensions. Thus, it is possible, for example, that as derivation reduces coherence may increase. Recognizing the dynamical nature of the dimension of AARRing does not mean, however, that experimental analyses cannot attempt to examine the differential impact of one dimension relative to another. It is entirely reasonable, therefore, to test the impact of coherence by manipulating feedback while recognizing that derivation per se is also likely influencing coherence. Ultimately, the utility of the units of analysis specified within the HDML framework will remain an empirical matter. For example, if derivation and coherence cannot be analyzed as separate dimensions, then no differences should be observed between conditions that attempt to separate these dimensions analytically.
 
2
The PFI employed in the current study was a very early version and to all intents and purposes no longer exists. The PFI is now named the Everyday Psychological Inflexibility Checklist (EPIC; Thompson, Bond, & Lloyd, 2019), which has only seven items (in contrast to the 80 items in the PFI). We have not, therefore, presented any psychometric properties for the PFI.
 
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Metadaten
Titel
Exploring the impact of coherence (through the presence versus absence of feedback) and levels of derivation on persistent rule-following
verfasst von
Colin Harte
Dermot Barnes-Holmes
Yvonne Barnes-Holmes
Ciara McEnteggart
Publikationsdatum
15.07.2020
Verlag
Springer US
Erschienen in
Learning & Behavior / Ausgabe 2/2021
Print ISSN: 1543-4494
Elektronische ISSN: 1543-4508
DOI
https://doi.org/10.3758/s13420-020-00438-1

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