A person-by-situation approach to predicting behavior with implicit measures

准确预测人类行为的能力是社会科学的一个标志性挑战。态度概括了特定的想法和感觉，这些想法和感觉可能会预测行为。然而，人们往往不愿意或无法提供关于他们态度的准确报告，当他们的态度反映出社会上有争议的信念时，情况往往就是这样。自发明和创新一类被称为“内隐测量”的态度测量以来，现在已经过去了大约20年，这种测量旨在获取一个人不愿意或无法报告的精神内容。这一重要的方法论进步对科学理论和公共话语都产生了巨大的影响。然而，关于这些措施在预测行为方面的效用，证据是混合的。目前的项目重新调整了数十年的研究，以表明这些测量方法提取的精神内容在预测能力上存在差异：1)在重要方面存在差异的人之间；2)这些人发现自己处于各种不同的情况下。恰当的问题可能不是“隐含的措施能预测行为吗？”相反，它们是“隐含的衡量标准是否能更好地预测某些人的行为，以及在某些情况下比其他情况下更好地预测行为？”以及“这两个层次的调查是否相互作用，使得预测在某些情况下对某些人特别有效？”该项目对影响隐性测量效用的因素进行了迄今为止最全面的测试。这12项研究使用五个态度领域的三个内隐测量来测试预测，并在四个不同的诱导背景下检查了八个个体的差异。具体方法测试个人因素(态度可及性、一致性)和情景因素(激活度、控制力)。调查的广度和大样本是做出有信心和可概括的主张的关键。这项研究的结果对难以衡量的态度的有效性具有关键影响，包括那些导致对他人不利待遇的态度。只有准确地评估人们和环境中的态度，才能更好地理解和解决他们对社会问题的下游后果。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The ability to accurately predict human behavior is a signature challenge of social science. Attitudes encapsulate specific thoughts and feelings that presumably should predict behavior. However, often people are unwilling or unable to provide accurate reports of their attitudes, which frequently is the case when their attitudes reflect socially controversial beliefs. It has now been roughly two decades since the invention and innovation of a class of attitude measures termed "implicit measures", which were designed to access mental content that a person is either unwilling or unable to report. This important methodological advance has had an immense impact on both scientific theory and public discourse. However, the evidence is mixed with respect to the utility of these measures in predicting behavior. The current project reframes decades of research to suggest that the mental content picked up by these measures varies in predictive ability 1) across people who differ from one another in important ways, and 2) as those people find themselves in a variety of different situations. The appropriate question may not be "Do implicit measures predict behavior?". Rather they are "Do implicit measures predict behavior better for some people rather than others and in some situations more than in others?" and "Do these two levels of inquiry interact so that prediction works particularly well for some people in some situations?"The project provides the most comprehensive test to date of factors affecting the utility of implicit measures. The 12 studies test predictions using three implicit measures across five attitude domains and examine eight individual differences within four different eliciting contexts. Specific methods test person factors (attitudinal accessibility, consistency) and situational factors (activation, control). The breadth of inquiry and large samples are essential to make confident and generalizable claims. The findings of this research have critical implications regarding the validity of attitudes that are difficult to measure, including those that contribute to the adverse treatment of others. Only by accurately assessing attitudes across people and contexts can their downstream consequences on societal problems be better understood and addressed.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.