UCL Department of Security and Crime Science, University College London, 35 Tavistock Square, London, WC1H 9EZ, UK.
UCL Centre for the Forensic Sciences, University College London, 35 Tavistock Square, London, WC1H 9EZ, UK.
Behav Res Methods. 2023 Aug;55(5):2575-2582. doi: 10.3758/s13428-022-01915-3. Epub 2022 Jul 25.
This paper presents a method to induce stress in human subjects during online participation in research studies without the presence of researchers. In this study, participants in the stress-inducing condition (N = 52, 44%) were asked to answer general knowledge and mathematical questions which people often get wrong, and did so under time pressure as well as receiving feedback. In contrast, participants in the control condition (N = 66, 56%) did not have time pressure or receive feedback. The stress manipulation was found to be effective, as the reported state anxiety and visual analog scale on stress scores were higher for the stress group than for the non-stress group (both findings, p < 0.001). Consistent findings were found when accounting for trait anxiety as a moderator, with the exception of the state anxiety levels in high trait anxiety group. This stressing method combines the established stress conditions of uncontrollability (such as time pressures) and social evaluative threats (such as negative feedback). In addition, the method contains specific measures (such as a commitment statement and attention check questions) to enhance the internal validity by preventing and detecting cheating or random responses. This method can be deployed through any commonly available online software. It offers a simple and cost-effective way to collect data online - which fits the increasing need to carry out research in virtual and online environments.
本文提出了一种在研究参与者在线参与研究时无需研究人员在场的情况下人为施加压力的方法。在这项研究中，压力诱导组（N=52，44%）的参与者被要求回答人们经常答错的常识和数学问题，并在时间压力下以及收到反馈的情况下回答。相比之下，对照组（N=66，56%）没有时间压力也没有收到反馈。压力诱发被证明是有效的，因为与非压力组相比，压力组报告的状态焦虑和压力得分的视觉模拟量表得分更高（两项发现，p<0.001）。当考虑特质焦虑作为调节变量时，也得到了一致的发现，除了高特质焦虑组的状态焦虑水平。这种施压方法结合了不可控性（如时间压力）和社会评价威胁（如负面反馈）等既定的压力条件。此外，该方法包含特定的措施（如承诺声明和注意力检查问题），通过防止和检测作弊或随机响应来提高内部有效性。这种方法可以通过任何常见的在线软件部署。它提供了一种简单且具有成本效益的在线数据收集方法——这符合在虚拟和在线环境中进行研究的日益增长的需求。
