课题基金 / 基金详情

Improving Implicit Attitude Measurement

Improving Implicit Attitude Measurement
改进内隐态度测量
批准号:
0615478
负责人:
Brian Payne
金额:
$15.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-09-01 至 2010-08-31

项目摘要

项目成果

Brian Payne的其他基金

相似基金

相关文献

中文摘要
翻译
最近关于态度和偏好的研究中最重要的见解之一是,它们可以被隐性地衡量,而不需要一个人反省和自我报告。隐式测量允许研究人员研究受访者可能不愿意或不能明确报告的态度。因此,它们对于研究社会敏感话题是有价值的,在这些话题中,受访者可能不那么坦诚。然而,尽管取得了这些进展,目前的方法仍有几个心理测量学的局限性需要克服。隐式测量方法的信度和预测效度往往低于显式测量方法。而且,对同一话题的显性和隐性态度的测量往往在同一时间以多种方式不同,允许混淆和替代解释。本项目开发了一种新的隐式测量态度的方法,即影响错误归因程序。它通过使用无意识地将情感反应从一个来源错误归因于另一个来源的倾向来衡量态度。三组侧重于种族态度和酒精滥用的研究将该方法与现有方法进行了比较。第一组研究测试了这种方法预测种族歧视和酗酒行为的能力,并与两种常用的隐式方法进行了比较。第二组测试是对社会期望的抵制。第三组使用该方法在所有维度上将隐式和显式测量等同起来,除了表达一个人态度的意图的关键差异。与其他隐式方法不同,此方法的度量是评估而不是响应时间。因此,自我报告和内隐反应可以直接在同一尺度上进行比较。通过消除隐式和显式方法之间的无关差异,可以比以前更直接地测试隐式和显式措施之间的关系。该项目具有潜在的重要的更广泛的影响,提高了在种族歧视和药物滥用等重要领域测量的保真度。该项目将通过向公众提供一种新的有效的内隐态度测量方法,帮助推进社会和行为科学的研究基础设施。更精确的测量将有助于理论测试和未来的努力,以确定破坏性行为的原因和补救措施。
英文摘要
One of the most important recent insights in the study of attitudes and preferences is that they can be measured implicitly, without asking a person to introspect and self-report. Implicit measurements allow researchers to study attitudes that respondents may be unwilling or unable to report explicitly. They therefore are valuable for studying socially sensitive topics, where respondents may be less than candid. Yet despite this progress, current methods have several psychometric limitations to overcome. Reliability and predictive validity for implicit methods are often lower than accepted for explicit measurement methods. And explicit and implicit measurements of attitudes toward the same topic often differ in multiple ways at the same time, allowing for confounds and alternative explanations. This project develops a novel method for implicitly measuring attitudes, the Affect Misattribution Procedure. It measures attitudes by using the tendency to unintentionally misattribute affective responses from one source to another. Three sets of studies, focusing on racial attitudes and alcohol abuse, compare the method to currently available methods. The first set of studies tests the ability of this method to predict racial discrimination and alcohol abuse behaviors, in comparison to two commonly used implicit methods. The second set tests for resistance to social desirability. The third set uses the method to equate implicit and explicit measures on all dimensions except the crucial difference of intent to express one's attitude. Unlike other implicit methods, the metric for this method is an evaluation rather than response time. Therefore, self-reports and implicit responses can be directly compared on the same scales. By eliminating extraneous differences between implicit and explicit methods, the relationship between implicit and explicit measures can be tested more directly than previously has been possible. The project has potentially important broader impacts, increasing the fidelity of measurement in important domains such as racial discrimination and substance abuse. The project will help advance research infrastructure for social and behavioral science by making publicly available a new validated method for implicit attitude measurement. More accurate measurement will facilitate theory testing and future efforts to identify causes of, and remedies for, destructive behavior.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
CyberCorps Scholarship for Service: Preparing Future Cybersecurity LeADERS through Applied Learning Experiences
SBP: Implicit Bias: Separating Person and Context
SaTC: EDU: Creating Cybersecurity Pathways Between Community Colleges and Universities
Improving the Success of Low-Income Students in a Cybersecurity Program
海外基金