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A Meta-Analysis on the Correlation Between the Implicit Association Test and Explicit Self-Report Measures

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TLDR
The results suggest that implicit and explicit measures are generally related but that higher order inferences and lack of conceptual correspondence can reduce the influence of automatic associations on explicit self-reports.
Abstract
Theoretically, low correlations between implicit and explicit measures can be due to (a) motivational biases in explicit self reports, (b) lack of introspective access to implicitly assessed representations, (c) factors influencing the retrieval of information from memory, (d) method-related characteristics of the two measures, or (e) complete independence of the underlying constructs. The present study addressed these questions from a meta-analytic perspective, investigating the correlation between the Implicit Association Test (IAT) and explicit self-report measures. Based on a sample of 126 studies, the mean effect size was .24, with approximately half of the variability across correlations attributable to moderator variables. Correlations systematically increased as a function of (a) increasing spontaneity of self-reports and (b) increasing conceptual correspondence between measures. These results suggest that implicit and explicit measures are generally related but that higher order inferences and lack of conceptual correspondence can reduce the influence of automatic associations on explicit self-reports.

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Development and psychometric properties of the Knowledge and Attitudes to Mental Health Scales (KAMHS): a psychometric measure of mental health literacy in children and adolescents.

TL;DR: In this paper, the authors developed and validated a psychometric instrument (termed the Knowledge and Attitudes to Mental Health Scales: KAMHS) to assess the mental health literacy of adolescents.
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Construction and validation of an implicit instrument to assess God representations : Part 1: Associations between implicit and explicit God representation and distress measures

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Jürgen Maes
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Implicit and explicit attitudes of Chinese youth toward the second-generation rich

TL;DR: Wang et al. as discussed by the authors investigated the implicit attitudes of Chinese youth towards the second-generation rich and the relationship of these with their explicit attitudes, and found that the participants exhibited a negative explicit attitude toward the second generation rich.
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Measures of implicit cognition for marketing research

TL;DR: In this paper, the authors provide a broad methodological overview of implicit cognition measures to guide future researchers' marketing applications and present the methods' theoretical foundations, outlines how they can overcome explicit measures' limitations, and sketches their potential for marketing applications.
References
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Journal ArticleDOI

Measuring individual differences in implicit cognition: The implicit association test.

TL;DR: An implicit association test (IAT) measures differential association of 2 target concepts with an attribute when instructions oblige highly associated categories to share a response key, and performance is faster than when less associated categories share a key.
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The file drawer problem and tolerance for null results

TL;DR: Quantitative procedures for computing the tolerance for filed and future null results are reported and illustrated, and the implications are discussed.
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Attitude-behavior relations: A theoretical analysis and review of empirical research.

TL;DR: In this article, a review of available empirical research supports the contention that strong attitude-behavior relations can be obtained only under high correspondence between at least the target and action elements of the attitudinal and behavioral entities.
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Implicit Social Cognition: Attitudes, Self-Esteem, and Stereotypes.

TL;DR: The present conclusion--that attitudes, self-esteem, and stereotypes have important implicit modes of operation--extends both the construct validity and predictive usefulness of these major theoretical constructs of social psychology.
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Understanding and using the Implicit Association Test: I. An improved scoring algorithm.

TL;DR: The best-performing measure incorporates data from the IAT's practice trials, uses a metric that is calibrated by each respondent's latency variability, and includes a latency penalty for errors, and strongly outperforms the earlier (conventional) procedure.
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