Resurgence as Choice: Implications for promoting durable behavior change

Greer et al. (2019) wrote a theory paper. They asked, 'What if resurgence is just a choice?' The team sketched a math model. It treats the old problem behavior and the new alternative as two items on a menu. The learner picks whichever feels more rewarding at that moment.

The model predicts when problem behavior will pop back up. It says resurgence grows fast when the alternative reinforcement suddenly gets worse.

The paper itself reports no new data. Instead it gives clinicians a recipe: keep the alternative response the 'better deal' even when reinforcement falters. If the alternative stays valuable, resurgence stays low.

Falligant et al. (2022) tested the recipe in real FCT cases. They saw the same exponential spike the model predicted when big reinforcement cuts were made. Shahan et al. (2020) also found the exponential rule in the lab. These studies act as direct replications.

Ritchey et al. (2023) extended the idea to human adults. They cut the size, not the rate, of alternative rewards. Resurgence still rose as the model said, but the fit was slightly off. The team released RaC2 to fix the errors. This looks like supersession: RaC2 updates the original math.

Craig et al. (2024) stretched the model further. They applied it to alcohol abstinence in rats without extinction. Resurgence still appeared, showing the framework can cross species and behaviors.

You can use the rule on Monday. Plan tiny steps when you thin reinforcement during FCT. Watch for any cue that makes the problem behavior look like the better choice. If resurgence spikes, boost the alternative reward or slow the thinning pace. The choice lens turns a mysterious relapse into a manageable contingency check.