Multiple schedules of conjugate reinforcement and extinction: A translational model for assessing automatically reinforced behavior

This study evaluated the extent to which a conjugate reinforcement schedule (CONJ) involving a contingency between pedaling a stationary bike and viewing a preferred movie could serve as a translational preparation for the analysis of automatically reinforced behavior. In part, researchers examined...

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Veröffentlicht in:Journal of applied behavior analysis 2024-03, Vol.57 (2), p.383-393
Hauptverfasser: Peterson, Matthew C., Ghezzi, Patrick M., Rapp, John T.
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container_title Journal of applied behavior analysis
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creator Peterson, Matthew C.
Ghezzi, Patrick M.
Rapp, John T.
description This study evaluated the extent to which a conjugate reinforcement schedule (CONJ) involving a contingency between pedaling a stationary bike and viewing a preferred movie could serve as a translational preparation for the analysis of automatically reinforced behavior. In part, researchers examined whether providing participants with either an accurate or an inaccurate rule about the extinction (EXT) component of a multiple schedule (MULT) contributed to the development of control by the MULT (CONJ EXT) schedule. Results show schedule control emerged for four of five participants who received the accurate rule and none of the five participants who received the inaccurate rule. In addition, participants who received accurate rules typically increased pedaling during CONJ components that followed two consecutive EXT components, suggesting that they experienced deprivation for audio and visual stimulation generated by pedaling. These preliminary findings suggest that researchers could use this translational preparation to identify matched interventions for some automatically reinforced behavior.
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subjects automatically reinforced behavior
conjugate reinforcement
multiple schedule
rule governance
translational research
title Multiple schedules of conjugate reinforcement and extinction: A translational model for assessing automatically reinforced behavior
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