Association for Behavior Analysis International

The Association for Behavior Analysis International® (ABAI) is a nonprofit membership organization with the mission to contribute to the well-being of society by developing, enhancing, and supporting the growth and vitality of the science of behavior analysis through research, education, and practice.

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45th Annual Convention; Chicago, IL; 2019

Event Details

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Symposium #431
CE Offered: BACB
Model Dependency in Basic Research and Clinical Practice: Why Behavior Analysis Cannot Be the Same Tomorrow as it is Today
Monday, May 27, 2019
9:00 AM–9:50 AM
Hyatt Regency East, Ballroom Level, Grand Ballroom CD South
Area: VRB/AUT; Domain: Translational
Chair: Caleb Stanley (Southern Illinois University)
Discussant: Mark R. Dixon (Southern Illinois University)
CE Instructor: Jordan Belisle, Ph.D.
Abstract:

Science is self-correcting, generating quantifiable and testable predictions of events in nature (basic experimental models) and influencing such events to improve the lives of people (applied clinical models). Skinner discussed the importance of understanding the behavior of scientists in his radical behavioral account, and more recent attempts have been made in other fields to develop a self-correcting and evolving science of science. In particular, model dependent realism developed by Hawking and Mlodinow (2010) puts forward contextual and pragmatic criteria for vetting competing scientific models. In the first presentation, Dr. Jordan Belisle (Missouri State University) compares four basic theories of human language learning framed within model dependent realism. He also discusses advances in the quantitative analysis of behavior that could be used to make quantitative predictions about human language. In support of a quantitative approach, the presenter will show new data that support Relational Density Theory as a model for predicting and potentially influencing higher order properties of language. In the second presentation, Dr. James Moore (Canopy Children’s Solutions) extends model dependent realism in the context of comparing applied clinical models from within a pragmatic truth criterion. Traditional models that have emphasized direct contingency control and verbal behavior are compared against contemporary treatment models in relational training and acceptance and commitment training. Finally, the discussant highlights the need for basic experimental and applied clinical models that can generate large-scale outcome research, as only by examining the utility of our models in changing the lives of people, can we move toward a more complete, adaptive, and evolved science of human behavior.

Instruction Level: Advanced
Keyword(s): ACTraining, Model Dependency, Relational Density, Relational Framing
Target Audience:

BCBAs

Learning Objectives: Define stimulus equivalence and related research Interpret research on relational training Interpret research on acceptance and commitment training with children with autism
 

Model Dependent Realism in Behavior Science and Higher-Order Relational Behavior

(Basic Research)
JORDAN BELISLE (Missouri State University)
Abstract:

A defining feature of radical behaviorism is the assumption that behavioral principles can be applied to the behavior of the scientist, and indeed, to the science itself (Skinner, 1945, 1956, 1974; Chiesa, 1992). Two model dependent theories of science have been put forward by Kuhn (1962) and Hawking and Mlodinow (2010) that are largely consistent with radical behaviorism. Model dependent realism in particular establishes four criteria that can be used to compare competing models in basic science that may be useful when models are incompatible. The criteria propose that models should (a) be elegant, (b) contain few if any arbitrary or adjustable elements, (c) explain all existing observations, and (d) make quantifiable predictions about future events that are falsifiable. Current models of human language learning (verbal behavior, bidirectional naming, equivalence, and relational frame theory) are compared using these criteria to determine elements of each that are compatible, and when models are incompatible, to determine which models best explain human language. In pursuing the fourth criteria, Relational Density Theory (Belisle & Dixon, in press) is put forward as a model of higher-order and self-emergent properties of relational language that generates quantifiable predictions that can be directly tested. Data are presented that support the predictions made in Relational Density Theory, along with preliminary data in application with children with autism.

 
Model Dependent Clinical Application: Extending the Account to Autism Treatment
(Applied Research)
JAMES MOORE (Canopy Children's Solutions), Breanna Newborne (Canopy Children’s Solutions), Christopher M. Furlow (Canopy Children's Solutions )
Abstract: Contextually controlled relational responding, also referred to as relational framing, has been established as a basic model of complex human learning. Hayes et al. (2001) conceptualized phenomenon as generalized operant behavior that is learned through multiple exemplar training. This behavior appears to emerge spontaneously in typically developing children, as they learn through natural language contexts (e.g., Lipkens, Hayes & Hayes, 1993; Luciano, Gómez & Rodríguez, 2007). However, children with autism spectrum disorders (ASD) do not easily learn this key form of responding and may experience psychological suffering when language emerges (e.g., Rehfeldt, Dillen, Ziomek, & Kowalchuk, 2007). Relational training and acceptance and commitment training provide clinical training models that make use of contemporary advances in relational frame theory. The former emphases derived relational responding and transformations of stimulus function that participate in language development. The latter emphasis the role of experiential avoidance and cognitive fusion in psychological inflexibility in human suffering. In the presentation, we present data demonstrating the efficacy of training relational frames in the early portions of intervention for children with ASD. We also present data suggesting that acceptance and commitment training can effectively influence behavior when language is evident. Whereas prior work has posited that more basic models may be needed developmentally prior to introducing relational training, we review data suggesting that these elementary verbal operants may be accounted for within relational learning, leading to early generative language acquisition, and a necessity for more complete clinical models in autism treatment.
 

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