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Association for Behavior Analysis International

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42nd Annual Convention; Downtown Chicago, IL; 2016

Event Details

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Paper Session #124
Complex Analyses in Verbal Behavior: Probabilistic Index and Contextual Analysis
Sunday, May 29, 2016
4:00 PM–4:50 PM
Michigan ABC, Hyatt Regency, Bronze East
Area: VRB
Chair: Ian Hussey (Ghent University)
Quantifying Effects on Implicit Measures Using a More Behavior-Analytic Consistent Metric: The Probabilistic Index
Domain: Applied Research
IAN HUSSEY (Ghent University), Maarten De Schryver (Ghent University), Jan De Houwer (Ghent University)
Abstract: Measures of "implicit attitudes" such as the Implicit Association Test have become popular in many areas of psychological research. While there have been efforts to understand the effects generated by such tasks from a behavior-analytic perspective, the fact that such effects are typically quantified using abstractive statistics makes them harder to reconcile with the behaviour-analytic approach. For example, the commonly used D score compares differences between mean response times. This paper will first discuss the conceptual difficulties this poses. It will then outline a non-abstractive scoring metric: the Probabilistic Index. The PI has a clear interpretation: it reflects the probability that a randomly selected response on a trial within one block is faster than a randomly selected response on a trial within the opposing block. Support for the conceptual and empirical utility of the PI metric, and its compatibility with the behaviour analytic approach, will be argued for based on several data sources. First, we present data from a Monte Carlo simulation that indicates that PI is more robust to the influence of outliers than the D score. Second, data from three studies collected on the Project Implicit website in three different domains (self-esteem, race, and voting behaviour). The PI demonstrated higher internal consistency in all three domains. Furthermore, the third study allowed for the calculation of predictive validity: the included graph demonstrating the PI's superior sensitivity and specificity in predicting voting in the US election. Finally, two studies will be reported on utility of the PI in scoring implicit measures of verbal behaviour within depression and self-harm in students at Ghent University. The arguments for the use of PI in the analysis of verbal behavior will be discussed.
Skinner Laid the Blueprints, Who Will Build the House? Exploring the Skinnerian/Post-Skinnerian Divide
Domain: Theory
NEAL SHIPLEY (The Chicago School of Professional Psychology)
Abstract: The current paper explores the divide between Skinnerian and post-Skinnerian interpretations of verbal behavior, specifically the persistent debate between Skinner's analysis of verbal behavior, and Relational Frame Theory. ConsideringSkinner's definition of operant behavior, Relational Frame Theory is presented not as a revolutionary paradigm, but instead as a behavior analytic tool emergent from Skinner's analysis, much like the technologies of Functional Communication Training, or Picture Exchange Communication Systems. An interpretation of Relational Frame Theory amenable to Skinner's analysis of verbal behavior is presented, along with suggestions for how the established differences between each approach can be smoothed over. Comparisons are drawn specifically between Skinner's definition of multiple control, and Relational Frame Theory's concept of derived relational responding. Further suggestions for how Skinner's elementary operants can be incorporated into the language of Relational Frame Theory are also provided. Finally the issue of "cognition" is presented as an argument that Skinner never pursued in Verbal Behavior, but a final frontier of human behavior that Relational Frame Theory enthusiastically promises to explore.


Modifed by Eddie Soh