Response‐dependent point loss and response force as disrupting operations on behavioral resistance to change in humans
Dense reinforcement history protects human operant behavior against point-loss and extra effort.
01Research in Context
What this study did
Costa et al. (2024) asked adults to press a key for points on two schedules. One schedule paid more often than the other.
After the baseline, the team added two disruptors. Sometimes points were taken away. Other times the key had to be pressed harder.
What they found
The richer schedule kept its high rate even when points were lost or the key got heavy. The lean schedule dropped off quickly.
Behavioral momentum theory predicts exactly this: stronger reinforcement history protects against disruption.
How this fits with other research
Van der Molen et al. (2010) showed that losing money suppresses human responding. Costa’s work adds that the suppression is smaller when the background payoff is rich.
Pinkston et al. (2018) found force rules did not change extinction resistance. Costa now shows force does disrupt, yet richer components still hold steady.
Moss et al. (2009) saw mice adapt to high force and bounce back. Humans in Costa’s lab did not bounce back under lean pay, showing species and procedure matter.
Why it matters
You can shield skill behaviors from punishment or added effort by first building a thick reinforcement history. Teach the task with dense praise or tokens, then later when you must levy a penalty or add work, the client’s performance should survive.
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02At a glance
03Original abstract
Behavioral momentum theory (BMT) provides a theoretical and methodological framework for understanding how differentially maintained operant responding resists disruption. A common way to test operant resistance involves contingencies with suppressive effects, such as extinction or prefeeding. Other contingencies with known suppressive effects, such as response-cost procedures arranged as point-loss or increases in response force, remain untested as disruptive events within the BMT framework. In the present set of three experiments, responding of humans was maintained by point accumulation programmed according to a multiple variable-interval (VI) VI schedule with different reinforcement rates in either of two components. Subsequently, subtracting a point following each response (Experiment 1) or increasing the force required for the response to be registered (Experiments 2 and 3 decreased response rates, but responding was less disrupted in the component associated with the higher reinforcement rate. The point-loss contingency and increased response force similarly affected response rates by suppressing responding and human persistence, replicating previous findings with humans and nonhuman animals when other types of disruptive events (e.g., extinction and prefeeding) were investigated. The present findings moreover extend the generality of the effects of reinforcement rate on persistence, and thus BMT, extending the analysis of resistance to two well-known manipulations used to reduce responding in the experimental analysis of behavior.
Journal of the Experimental Analysis of Behavior, 2024 · doi:10.1002/jeab.885