Behavioral momentum theory: equations and applications.
Every reinforcer in the room, even accidental ones, makes behavior stickier, so plan your extinction and DRA knowing the math says it will take longer.
01Research in Context
What this study did
Hattier et al. (2011) wrote the math behind behavioral momentum. They showed how any reinforcers in a setting, even free ones, make behavior harder to stop. The paper gives equations but no new data.
What they found
The team proved that resistance to change grows with total reinforcers, not just the ones you meant to deliver. Extinction gets tougher after thick schedules or extra non-contingent snacks.
How this fits with other research
Fisher et al. (2018) later used the same math to beat resurgence. They stacked reinforcement on the replacement response before thinning, and problem behavior returned less.
Cox et al. (2015) added a time rule. Pigeons needed several sessions of steady pay before momentum kicked in; one or two good days were not enough.
Matousek et al. (1992) seemed to disagree. They saw little momentum when the contingency itself changed. The clash fades once you see they tested short, shaky baselines, not the long stable ones the equations assume.
Why it matters
You now have a ruler for persistence. Before you fade reinforcement or place a client on extinction, ask: how dense has the history been? If it is rich, expect a longer fight. Add extra reinforcement to the new skill first, as Fisher did, and you will see less resurgence next week.
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02At a glance
03Original abstract
Behavioral momentum theory provides a quantitative account of how reinforcers experienced within a discriminative stimulus context govern the persistence of behavior that occurs in that context. The theory suggests that all reinforcers obtained in the presence of a discriminative stimulus increase resistance to change, regardless of whether those reinforcers are contingent on the target behavior, are noncontingent, or are even contingent on an alternative behavior. In this paper, we describe the equations that constitute the theory and address their application to issues of particular importance in applied settings. The theory provides a framework within which to consider the effects of interventions such as extinction, noncontingent reinforcement, differential reinforcement of alternative behavior, and other phenomena (e.g., resurgence). Finally, the theory predicts some counterintuitive and potentially counterproductive effects of alternative reinforcement, and can serve as an integrative guide for intervention when its terms are identified with the relevant conditions of applied settings.
Journal of applied behavior analysis, 2011 · doi:10.1901/jaba.2011.44-877