|Relapse and Behavioral Momentum|
|Monday, May 28, 2012|
|2:00 PM–3:20 PM |
|608 (Convention Center)|
|Area: EAB; Domain: Basic Research|
|Chair: Duncan Pritchard (Aran Hall School)|
|Discussant: Iser Guillermo DeLeon (Kennedy Krieger Institute)|
The relapse of problem behavior following apparently successful treatment is an enduring problem for the field of behavior analysis. Treatment relapse can occur when, for example, treatment is withdrawn to test for maintenance or when there are lapses in treatment integrity. Behavior momentum theory describes how behavior persists despite changes in the environment. Behavior momentum studies have shown that rate and resistance to change are independent aspects of behavior. Problem behavior is more resistant to change, and thus more likely to relapse in environments that are associated with high rates of reinforcement than in environments associated with low rates, even if an alternative behavior has been reinforced at the same time. Reinstatement, resurgence, and renewal models have been used to demonstrate treatment relapse. An effective method of evaluating the resistance of a behavior to disruption in each of these three models is to use multiple schedules of reinforcement in which differing rates of reinforcement occur in the context of alternating discriminative stimuli. Relapse is greater in the richer of the two multiple schedules. Translational researchers are now developing treatments based on these procedures to successfully reduce the magnitude of the relapse of problem behavior.
|Keyword(s): Behavioral momentum, Persistence, Relapse, Renewal|
Clinical Demonstration of the Renewal Model of Treatment Relapse
|DUNCAN PRITCHARD (Aran Hall School), Marguerite L. Hoerger (Bangor University), F. Charles Mace (Nova Southeastern University), Brian Harris (Aran Hall School), Heather Penney (Aran Hall School), Llio Eiri (Aran Hall School)|
The magnitude of treatment relapse has been shown to be greater when high rates of reinforcement are used to reduce problem behavior in both resurgence and reinstatement models. The effects of high rate reinforcement on the relapse of problem behavior within an ABA renewal model was evaluated. The participant was an 18 year-old male with severe intellectual disabilities who presented problem behavior maintained by attention. In the first context (A) problem behavior was reinforced by2 therapists on a multiple schedule of reinforcement. Therapist 1 reinforced problem behavior on a VT 30s schedule and Therapist 2 on a VT 120s schedule until stable responding was achieved. The participant was then moved to a second context (B) and all behaviors were placed on extinction by both therapists in consecutive extinction sessions. The participant was then transferred back to the first context (A) and all behaviors were again placed on extinction by both therapists in consecutive extinction sessions. Results demonstrated that the renewal of problem behavior was greater following high-rate reinforcement, that is, with Therapist 1 (VT 30s), than with Therapist 2 (VT 120s). This result suggests that low rate reinforcement may be more effective in preventing treatment relapse of problem behavior than high rate reinforcement.
Effects of Combining Stimulus Contexts on Resistance to Change
|CHRISTOPHER A. PODLESNIK (University of Auckland), John Bai (University of Auckland), Douglas Elliffe (University of Auckland)|
Consistent with behavioral momentum theory, arranging alternative sources of reinforcement within a stimulus context decreases target response rates but enhances resistance to disruption. We explored a method developed previously to circumvent enhancing the persistence of the target response while still reducing its rate. Keypecking in pigeons was maintained in 3 mutually exclusive stimulus contexts defined by keylight color. One stimulus context maintained a target response and another stimulus context maintained an alternative response. In a third context, a target response was reinforced concurrently with an alternative response, modeling a differential-reinforcement-of-alternative-behaviour (DRA) schedule. The overall reinforcement rate in the concurrent context was equal to the sum of the separate stimulus contexts. Combining the separate stimulus contexts during extinction enhanced disruption of target responding relative to target responding in the DRA context. In comparison, combining the separate alternative context with the target response from the overall richer concurrent context produced smaller disruptions in target responding. These findings suggest that alternative stimulus contexts function as disrupters of target behavior, and resistance to disruption to the addition of separate stimulus contexts is a function of the overall baseline reinforcement rate in a stimulus context, consistent with the assertions of behavioral momentum theory.
|Mechanisms of Resurgence|
|MARY MARGARET SWEENEY (Utah State University), Timothy A. Shahan (Utah State University)|
|Abstract: Resurgence is an increase in a previously extinguished response that occurs if alternative reinforcement introduced during extinction is removed. Shahan and Sweeney (2011) developed a quantitative model of resurgence based on behavioral momentum theory that suggests alternative reinforcement delivered during extinction has both disruptive and strengthening effects on the target response. The resurgence model captures existing data well and predicts that resurgence should decrease as time in extinction and exposure to alternative reinforcement increases. Two experiments tested this prediction. Data from Experiment 1 indeed suggest that without a return to baseline, resurgence decreases with increased exposure to alternative reinforcement and extinction of the target response. Experiment 2 found comparable resurgence across conditions at the same time point in extinction, despite dissimilar previous exposures to alternative reinforcement—suggesting that time in extinction is a more important determinant of resurgence than length of exposure to alternative reinforcement. Additional experiments exploring interactions between resurgence and other sources of relapse are also discussed, including contextual renewal, acute food deprivation, and negative incentive contrast. These data are then evaluated within the framework of the behavioral momentum-based quantitative model of resurgence.|