1. Measuring automatic associations: Validation of algorithms for the Implicit Association Test (IAT) in a laboratory setting
- Author
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Glashouwer, Klaske A., Smulders, Fren T.Y., de Jong, Peter J., Roefs, Anne, and Wiers, Reinout W.H.J.
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ALGORITHMS , *MEDICAL laboratories , *PATHOLOGICAL psychology , *SOCIAL psychology , *ANXIETY , *MENTAL depression - Abstract
Abstract: Background and objectives: In their paper, “Understanding and using the Implicit Association Test: I. An improved scoring algorithm”, Greenwald, Nosek, and Banaji (2003) investigated different ways to calculate the IAT-effect. However, up to now, it remained unclear whether these findings – based on internet data – also generalize to laboratory settings. Therefore, the main goal of the present study was to cross-validate scoring algorithms for the IAT in a laboratory setting, specifically in the domain of psychopathology. Methods: Four known IAT algorithms and seven alternative IAT algorithms were evaluated on several performance criteria in the large-scale laboratory sample of the Netherlands Study of Depression and Anxiety (N = 2981) in which two IATs were included to obtain measurements of automatic self-anxious and automatic self-depressed associations. Results and conclusions: Results clearly demonstrated that the D2SD-measure and the D600-measure as well as an alternative algorithm based on the correct trials only (DnoEP-measure) are suitable to be used in a laboratory setting for IATs with a fixed order of category combinations. It remains important to further replicate these findings, especially in studies that include outcome measures of more spontaneous kinds of behaviors. [Copyright &y& Elsevier]
- Published
- 2013
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