刻板印象威胁效应的消除：干预策略及其展望

刻板印象威胁效应的产生主要受到情境线索、所在刻板印象威胁群体的集体表征及群体认同、信念和动机等个人特质因素的影响。本文以认同威胁模型为基础,针对影响刻板印象威胁效应产生的主要因素,分别从改善情境、改变认知图式和训练积极的内隐态度和动机等多个方面系统地探讨了干预刻板印象威胁可能采用的策略,主要包括提供对困难的外归因、提供角色榜样、启动积极身份特征、提供多重社会身份信息、鼓励自我肯定、强调智力增长观、训练积极内隐态度及重塑任务环境等。在系统梳理各种干预策略的基础上,本文还探讨了当前该领域研究存在的不足和未来的发展方向。     

负性情绪刺激对大学生多目标追踪能力的影响

探讨了负性情绪对大学生多目标追踪能力的影响以及其影响机制。实验要求被试在观看国际情绪图库中的负性或中性图片后,完成多目标追踪和点探测任务,同时设置基线条件作为对照。采用状态-特质焦虑量表和贝克抑郁自评量表考察不同情绪图片条件下被试的诱发情绪状态。研究结果发现：（1）被试观看负性情绪图片后状态焦虑程度和抑郁量表评分显著提高,观看情绪图片有效诱发了被试的负性情绪;（2）基线条件下的被试追踪正确率显著低于中性条件,基线条件和负性图片条件下的追踪正确率无差异,说明训练可以提高被试的多目标追踪能力,但负性情绪抑制了被试在基线追踪任务中的训练效果;（3）负性图片条件下的点探测觉察率显著低于中性图片条件,说明负性情绪影响了被试的注意资源分配。研究结果表明：负性情绪可能干扰了被试目标导向的注意系统,使得个体更易受刺激驱动的注意系统影响,并且在追踪过程中影响被试中央执行系统的抑制和转移功能。     

Mothers' Impact on Daughters' Cardiovascular Reactivity in a High‐Threat Context: An Immersive Virtual Environment Study

Applying Attachment Theory, research on confirmation, the Entropy Model of Uncertainty, and the Biopsychosocial Model of Challenge and Threat, this investigation examined the role of mothers' communication on adolescents' cardiovascular response to threat. An experimental design allowed for the manipulation of maternal response to daughters experiencing a rapidly approaching wildfire in an immersive virtual environment. Results revealed complexities in the relative benefits of maternal vocalic presence during high‐threat situation, with the mother's history of confirming feedback playing an important role in daughters' cardiovascular response. Implications for knowledge are addressed and methodological possibilities of using immersive virtual environments are noted.     

幽默加工中不一致探测与解决的脑机制分离

本fMRI研究使用“文字背景—漫画图片”实验范式,设计了三种实验条件（可笑、不可笑和无关）,试图对幽默加工中不一致探测与解决的脑机制进行分离。可笑与不可笑条件对比的结果与前人研究一致,证明了新实验范式的有效性。其次,无关与不可笑条件比较,右侧脑岛激活,说明脑岛可能与不一致探测有关。综合分析发现,脑岛与杏仁核可能共同参与了不一致探测加工。此外,结果还第一次区分了幽默加工中不一致解决与一般问题解决的脑区。     

Flexible representations in visual working memory and interactions with long‐term learning: Commentary on the special issue

This special issue of the British Journal of Psychology brings together cutting edge research on a range of topics in visual working memory (VWM). In this commentary, we attempt to summarize common themes in current VWM research exemplified in this issue. The articles include several reviews of important topics as well as empirical papers covering three main themes. The first concerns the nature of mental representations of memoranda in the commonly used delayed estimation task, where both fine‐grained and broad categorical details appear to be represented, and their susceptibility to interference. The second concerns interactions between VWM representations, both those that produce individuation of representations and those that create an overarching ensemble structure. Finally, the third main topic concerns the use of VWM during visual search and in the learning of repeated configurations in search displays. The work presented here, and other work in the field, points to a rich interplay between representations in VWM but also between VWM and information in long‐term memory. Opportunities for further investigation are highlighted throughout.     

Breaking face processing tasks apart to improve their predictive value in the real world: A comment on Ramon,Bobak, and White (2019)

In this commentary, I will expand on three aspects suggested by Ramon et al. (2019, British Journal of Psychology, 110, 461) to improve the predictive value of laboratory‐based tasks in real‐world applications. There are potential benefits that may arise from three interrelated considerations, particularly in terms of predicting agents’ susceptibility to errors in operational settings. The first is a proposal to conduct a detailed examination of performance on face processing tests rather than only analysing overall accuracy scores. The second involves considering non‐face‐related cognitive and meta‐cognitive sub‐processes involved in face processing tasks. The third highlights the contribution of superior recognisers in creating challenging tests that simulate difficult real‐world situations.     

Rater Model Using Signal Detection Theory for Latent Differential Rater Functioning

Differential rater functioning (DRF) occurs when raters show evidence of exercising differential severity or leniency when scoring examinees within different subgroups. Previous studies of DRF have examined rater bias using manifest variables (e.g., use of covariates) to determine the subgroups. These manifest variables include gender and the ethnicity of the examinee. For example, a rater may score males more severely. Ideally, each rater’s severity should be invariant across subgroups. This study examines DRF in the context of latent subgroups that classify possible sources of DRF based on raters’ scoring behavior rather than manifest factors. An extension of the latent class signal detection theory (LC-SDT) model for identifying DRF is proposed and examined using real-world data and simulations. Results from real-world data show that the signal detection approach leads to an effective method to identify latent DRF. Simulations with varying sample sizes and conditions of rater precision were shown to recover parameters at an adequate level, supporting its use to identify latent DRF in large-scale data. These findings suggest that the DRF extension of the LC-SDT can be a useful model to examine characteristics of raters and add information that can aid rater training.     

Using the Reality Interview improves the accuracy of the Criteria‐Based Content Analysis and Reality Monitoring

Active interviewing approaches can exploit the verbal differences between truthtellers and liars, thus improving detecting deception. One such method is the Reality Interview (RI) aimed to facilitate recall from truthtellers, while increasing the difficulty for liars. This study investigated whether the RI could improve the diagnostic accuracy of the Reality Monitoring and the Criteria‐Based Content Analysis. Liars and truthtellers were either asked to freely recall an event or interviewed with the RI. As hypothesized, the RI improved the discriminability of Reality Monitoring and Criteria‐Based Content Analysis over Free Recall. Honest responses were longer, and the RI increased the word count difference between honest and false statements. However, after correcting for word count, results were no longer significant, showing its importance for deception detection. Nonetheless, the RI increased verbal differences between truthtellers and liars, demonstrating that using the RI with verbal credibility assessment tools is a powerful combination for investigative interviewing.     

功能性近红外光谱技术在说谎研究中的应用

功能性近红外光谱技术(functional near-infrared spectroscopy, fNIRS)是近年来新兴起的一种脑成像技术, 其凭借生态效度高,成本低等优势已成为一种具有广阔前景的测谎技术.研究者使用了被动说谎和主动说谎的实验范式, 验证了fNIRS技术在说谎研究中的可行性和准确性, 揭示了其在探讨年幼儿童说谎行为和真实互动情景中自发说谎行为的神经机制中的优势.未来研究应综合运用多种指标和方法, 考察说谎行为的神经网络, 加强真实人际互动情景下自发谎言神经机制和儿童说谎认知发展神经机制的研究, 这将有助于揭示说谎的本质, 提高测谎效力.     

视觉注意离散性的实验范式

注意离散性是注意间歇性地采集外界信息的特性。文章综述了视觉注意离散性的4种实验范式:(1)车轮错觉范式,刺激强度大、实验条件少、被试任务量小,较早地证实了视觉注意的离散性;(2)视觉探测范式,同时观察了被试的行为表现与电生理信号,确定了视觉注意离散性与神经振荡的关联;(3)线索靶子范式和视觉搜索范式,通过系统地变化SOA大幅提高了行为数据的时间分辨率,直观地探测到注意离散性调制的行为振荡。