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To IMPRES or to EXPRES? Exploiting comparative judgments to measure and visualize implicit and explicit preferences

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  • Tom Everaert
  • Adriaan Spruyt
  • Jan De Houwer

Abstract

We introduce an adaptation of the affect misattribution procedure (AMP), called the implicit preference scale (IMPRES). Participants who complete the IMPRES indicate their preference for one of two, simultaneously presented Chinese ideographs. Each ideograph is preceded by a briefly presented prime stimulus that is irrelevant to the task. Participants are hypothesized to prefer the ideograph that is preceded by the prime they prefer. In the present research, the IMPRES was designed to capture racial attitudes (preferences for white versus black faces) and age-related attitudes (preferences for young versus old faces). Results suggest that (a) the reliability of the IMPRES is similar (or even better) than the reliability of the AMP and (b) that the IMPRES and the AMP correlate significantly. However, neither the AMP nor the IMPRES were found to predict attitude-related outcome behavior (i.e., the preparedness to donate money to a charity benefiting ethnic minorities vs. the elderly). Further research is thus necessary to establish the validity of the IMPRES. Finally, we demonstrated that, unlike the AMP, the IMPRES allows for an in-depth assessment of unanticipated response patterns and/or extreme observations using multidimensional scaling algorithms.

Suggested Citation

  • Tom Everaert & Adriaan Spruyt & Jan De Houwer, 2018. "To IMPRES or to EXPRES? Exploiting comparative judgments to measure and visualize implicit and explicit preferences," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-14, January.
    • Handle: RePEc:plo:pone00:0191302
    DOI: 10.1371/journal.pone.0191302
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    References listed on IDEAS

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    1. Eric Luis Uhlmann & Anthony Greenwald & Andrew Poehlmann & Mahzarin Banaji, 2009. "Understanding and Using the Implicit Association Test: III. Meta-Analysis of Predictive Validity," Post-Print hal-00516146, HAL.
    2. de Leeuw, Jan & Mair, Patrick, 2009. "Multidimensional Scaling Using Majorization: SMACOF in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 31(i03).
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