Amazon Mechanical Turk (MTurk) is a crowdsourcing marketplace providing researchers with the opportunity to collect behavioral data from remote participants at a low cost. Recent research demonstrated reliable extinction effects, as well as renewal and resurgence of button pressing with MTurk participants. To further examine the generality of these findings, we replicated and extended these methods across six experiments arranging reinforcement and extinction of a target button press. In contrast to previous findings, we did not observe as reliable of decreases in button pressing during extinction (1) after training with VR or VI schedules of reinforcement, (2) in the presence or absence of context changes, or (3) with an added response cost for button pressing. However, we found that that a 1-point response cost for all button presses facilitated extinction to a greater extent than the absence of response cost. Nevertheless, we observed ABA renewal of button pressing when changing background contexts across phases and resurgence when extinguishing presses on an alternative button. Our findings suggest that MTurk could be a viable platform from which to ask and address questions about extinction and relapse processes, but further procedural refinements will be necessary to improve the replicability of control by experimental contingencies.

Amazon Mechanical Turk (MTurk) 是一个众包市场，为研究人员提供了以低成本收集远程参与者行为数据的机会。最近的研究证明了可靠的灭绝效应，以及 MTurk 参与者按下按钮的更新和复苏。为了进一步检验这些发现的普遍性，我们在六个实验中复制和扩展了这些方法，以安排目标按钮按下的增强和消失。与之前的发现相比，我们没有观察到在消退期间按钮按下的减少是可靠的（1）在使用 VR 或 VI 强化计划训练后，（2）在存在或不存在上下文变化的情况下，或（3）在增加了按钮按下的响应成本。然而，我们发现，与没有响应成本相比，所有按钮按下的 1 点响应成本在更大程度上促进了灭绝。尽管如此，我们观察到 ABA 在跨阶段更改背景上下文时重新按下按钮，并在熄灭替代按钮上的按下时重新出现。我们的研究结果表明，MTurk 可能是一个可行的平台，可以从中提出和解决有关灭绝和复发过程的问题，但还需要进一步的程序改进，以通过实验突发事件提高控制的可复制性。