Implicit Attitude Measures
Implicit Attitude Measures
复制标题
隐性态度测量
DOI:
10.1027/0044-3409/a000001
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发表时间:
2010
期刊:
影响因子:
--
通讯作者:
Steffens
中科院分区:
文献类型:
--
作者:
Steffens
Arguably, one of the most thriving research areas in current psychology is assessing attitudes and related constructs with implicit measures, which we define as those indirect measures that rely on response latencies or other indices of spontaneous trait association, the activation of action semantics, or even real behavior. This research area is united by a shared excitement about the discoveries enabled by these measures, be they related to social attitudes and behavior, clinical disorders, consumer decisions, or self-representations, among others. As this enumeration suggests, in spite of the common excitement about the new research questions implicit measures allow us to investigate, there is much diversity in this research. First of all, these approaches bridge subdisciplines of psychology traditionally characterized by little cross-talk. Furthermore, the variety of implicit measures used is already broad and still growing, given variants and implementations of these implicit measures in different samples and research approaches. Given this diversity, we deemed it appropriate to summarize research that focuses either on the comparison of different implicit measures or on the mechanisms underlying one of the measures. Such knowledge is necessary and helpful to determine which measure to employ in a given research context and also to be aware of limitations of certain measures and advantages of others. Thus, the articles collected in this special issue compare two or more different implicit measures, or they focus on the measurement properties of one.One of the mostly used implicit measures, the Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998), was introduced in a way that would have allowed researchers to implement it as if it was a standardized test. In spite of this, researchers not only used stimuli, numbers of trials, evaluation procedures, and other specifics different from those suggested; but in the end, they even suggested their own variants of IATs or implicit measures that keep certain aspects of IATs while eliminating or adding others (eg, De Houwer, 2003; Nosek & Banaji, 2001; Olson & Fazio, 2004; Sriram & Greenwald, 2009; Steffens, Kirschbaum, & Glados, 2008). As a first consequence, the answer to the question how a “good” IAT should be constructed is not as clean and tidy anymore as it appeared in 1998. As a second consequence of these methodological debates IAT research now comprises a diversity at the expense of addressing comparisons with other implicit measures (the implicit-explicit relation on the contrary has been attended to, eg, Hofmann, Gawronski, Gschwendner, Le, & Schmitt, 2005).
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影响因子:
24.8
作者:
Timothy D. Wilson;Elizabeth W. Dunn
通讯作者:
Timothy D. Wilson;Elizabeth W. Dunn
影响因子:
7.6
作者:
Greenwald, AG;Nosek, BA;Banaji, MR
通讯作者:
Banaji, MR
影响因子:
7.6
作者:
Greenwald, AG;McGhee, DE;Schwartz, JLK
通讯作者:
Schwartz, JLK
DOI:
--
发表时间:
1973
期刊:
影响因子:
--
作者:
Thomas Ostrom
通讯作者:
Thomas Ostrom
DOI:
--
发表时间:
1979
期刊:
影响因子:
--
作者:
J. Cacioppo;R. Petty
通讯作者:
R. Petty