Feature-specific attention allocation in implicit measures based on face stimuli

内隐测量允许分析包括态度和刻板印象在内的认知过程。当前的项目调查了刺激特征对内隐测量结果的影响，内隐测量是对目标对象或社会群体的态度的一种指示。通过快速（和自动）反应任务，如情感启动，影响错误归因或内隐联想测试，探讨了面部特征的后果。就像面孔是多维刺激一样，它们负责分类过程及其引发的影响。可以预期，将注意力集中在特定的特征上（性别、种族、吸引力）决定了情感的类型，从而也决定了隐性测量的结果。与Jamin Halberstadt（新西兰达尼丁奥塔哥大学）的合作已经开始并将继续。该项目部分回答了以下问题：(a)通过隐式测量评估什么样的影响，以及(b)隐式测量程序需要如何调整以评估利益关联。

Implicit measures allow the analysis of cognitive processes including attitudes and stereotypes. The current project investigates the impact of stimulus features on the outcomes of implicit measures, which are taken as an indication of attitudes towards target objects or social groups. By means of quick (and automatic) response tasks, such as affective priming, affect misattribution or implicit association tests, the consequences of facial features are explored. In as much as faces are multidimensional stimuli, they are responsible for categorization processes and the affect they elicit. It can be expected that focusing the attention on specific features (gender, ethnicity, attractiveness) determines the type of affect, thus also the outcome of the implicit measure. The cooperation with Jamin Halberstadt (University of Otago, Dunedin, New Zealand) has begun and shall be continued. The project partially answers the questions (a) what kind of affect is assessed by implicit measures and (b) how implicit measurement procedures need to be tailored to assess the associations of interest.