Stalking the perfect measure of implicit self-esteem: The blind men and the elephant revisited?

Bosson, Jennifer K.; Swann, William B.; Pennebaker, James W.

doi:10.1037/0022-3514.79.4.631

Cited by 905 publications

(1,047 citation statements)

References 53 publications

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“…This combination of a small correlation between the implicit and explicit measures of extraversion, and a heterotrait-monomethod correlation between two reliable IAT measures is what is expected on the basis of the reliable contamination hypothesis. However, besides interindividual differences in task-switching costs, several other factors may have contributed to the low implicit-explicit correlation obtained in Experiment 3, such as balancing of compatibility order (Asendorpf et al, 2002), and differences in the constructs tapped by implicit and explicit measures (Bosson et al, 2000;Wilson, Lindsey, & Schooler, 2000). Additionally, procedural variations like a relatively long response-stimulus interval of 800 ms and the incorporation of task-repetition trials may have played a role.…”

Section: Discussionmentioning

confidence: 93%

Method-Specific Variance in the Implicit Association Test.

Mierke¹,

Klauer²

2003

Journal of Personality and Social Psychology

232

307

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can be used to assess interindividual differences in the strength of associative links between representational structures such as attitude objects and evaluations. Four experiments are reported that explore the extent of method-specific variance in the IAT. The most important findings are that conventionally scored IAT effects contain reliable interindividual differences that are method specific but independent of the measures' content, and that IAT effects can be obtained in the absence of a preexisting association between the response categories. Several techniques to decrease the impact of method-specific variance are evaluated. The best results were obtained with the D measures recently proposed by A. G. Greenwald, B. A. Nosek, and M. R. Banaji (2003).

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Section: Discussionmentioning

confidence: 93%

Method-Specific Variance in the Implicit Association Test.

Mierke¹,

Klauer²

2003

Journal of Personality and Social Psychology

232

307

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“…However, in IAT research it is rare to find substantial (positive) correlations between different implicit measures designed to assess the same concept. For example, Bosson et al (2000) assessed measures of implicit self-esteem and found very low and (often) non-significant correlations. This is often explained by the fact that even subtle changes in a task can trigger different associative processes (e.g.…”

Section: Discussionmentioning

confidence: 99%

Explicit- and Implicit Bullying Attitudes in Relation to Bullying Behavior

Goethem

Scholte

Wiers

2010

J Abnorm Child Psychol

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The main aim of this study was to examine whether an assessment of implicit bullying attitudes could add to the prediction of bullying behavior after controlling for explicit bullying attitudes. Primary school children (112 boys and 125 girls, M age=11 years, 5 months) completed two newly developed measures of implicit bullying attitudes (a general Implicit Association Test on bullying and a movie-primed specific IAT on bullying), an explicit bullying attitude measure, and self reported, peer reported, and teacher rated bullying behavior. While explicit bullying attitudes predicted bullying behavior, implicit attitudes did not. However, a significant interaction between implicit and explicit bullying attitudes indicated that in children with relatively positive explicit attitudes, implicit bullying attitudes were important predictors of bullying behavior. Theoretical and practical implications are discussed.Keywords Explicit bullying attitudes . Implicit bullying attitudes . Interaction explicit and implicit bullying attitudes . Bullying School bullying is a large societal problem and is already evident among primary school children. Studies on this population show that 3-27% of the children bully, and 9-32% are bullied once a week or more (Berger 2007). Bullying has also been shown to have large negative consequences for the well-being of victims and bullies (Berger 2007;Scholte et al. 2007), which stresses the importance of targeting bullying behavior together with the factors that are related to bullying.Various factors have been found to contribute to the extent to which children bully other children. Research evidence indicates that social factors such as group membership and peer pressure, as well as individual, personal factors such as physical strength, aggressiveness, and empathy influence bullying (Rigby 2004). Another often studied individual factor is children's attitudes towards bullying. Attitudes are predictors of all kinds of spontaneous and deliberate social and non-social behavior (e.g., Glasman and Albarracin 2006) including bullying behavior (Salmivalli and Voeten 2004). Attitudes can be defined as general and enduring, concrete or abstract evaluations of a person, group, or issue and can be based on beliefs, emotions and behavior (cf. Petty and Cacioppo 1986).In attitude research, a distinction is made between implicit attitudes and explicit attitudes. Implicit attitudes are impulsive, spontaneous, uncontrolled emotional reactions and evaluations. In contrast, explicit attitudes refer to deliberate, reflective, controlled, consciously self-reported evaluations (Gawronski and Bodenhausen 2006). Dualprocess models assume that there are two different modes of information processing that underlie implicit and explicit attitudes. According to these models more automatic, impulsive, associative processes underlie implicit attitudes and more controlled, reflective processes underlie explicit During the research project on implicit and explicit bullying attitudes all authors were working at ...

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“…It should be noted, however, that correlations between affective priming effects and criterion variables are sometimes small or even absent (e.g., Banse, 1999Banse, , 2001Bosson, Swann, & Pennebaker, 2000). In part, this fact seems to be related to the on-average-limited reliability of affective priming scores.…”

Section: Affective Priming Effects the What Criterion: What Attributementioning

confidence: 99%

Implicit measures: A normative analysis and review.

Houwer¹,

Teige‐Mocigemba

Spruyt³

et al. 2009

Psychological Bulletin

724

657

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Implicit measures can be defined as outcomes of measurement procedures that are caused in an automatic manner by psychological attributes. To establish that a measurement outcome is an implicit measure, one should examine (a) whether the outcome is causally produced by the psychological attribute it was designed to measure, (b) the nature of the processes by which the attribute causes the outcome, and (c) whether these processes operate automatically. This normative analysis provides a heuristic framework for organizing past and future research on implicit measures. The authors illustrate the heuristic function of their framework by using it to review past research on the 2 implicit measures that are currently most popular: effects in implicit association tests and affective priming tasks.Keywords: implicit measures, automaticity, IAT, affective priming Most psychologists would argue that a full understanding of the behavior of an individual requires knowledge not only of the external situation in which the individual is present but also of the internal psychological attributes of the individual. Throughout the history of psychology, researchers have therefore attempted to measure interindividual differences in the psychological attributes of people (e.g., Anastasi, 1958;Eysenck & Eysenck, 1985;Mischel & Shoda, 1995). During the past decade, a major development in this research has been the introduction of so-called implicit measures. These measures were originally put forward mainly within the social psychology literature (e.g., Fazio, Jackson, Dunton, & Williams, 1995;Greenwald, McGhee, & Schwartz, 1998) but have since then spread to various other subdisciplines of psychology, including differential psychology (e.g., Asendorpf, Banse, & Mücke, 2002), clinical psychology (e.g., Gemar, Segal, Sagrati, & Kennedy, 2001, consumer psychology (e.g., Maison, Greenwald, & Bruin, 2004), and health psychology (e.g., Wiers, van Woerden, Smulders, & de Jong, 2002).Despite the widespread use of implicit measures, the actual meaning of the term implicit measure is rarely defined. On the basis of the work of Borsboom (Borsboom, 2006;Borsboom, Mellenbergh, & van Heerden, 2004) and De Houwer (De Houwer, 2006;, we first provide a normative analysis of the concept "implicit measure." The analysis is normative in the sense that it stipulates the properties that an ideal implicit measure should have. As such, the analysis provides a heuristic framework for reviewing and evaluating existing research on implicit measures. By examining the extent to which a particular implicit measure exhibits these normative properties, one can clarify the way in which the measure is an implicit measure and highlight those issues on which further research is required. In the second part of this article, we perform this exercise with regard to the two types of implicit measures that are currently most popular: effects in implicit association tests (IATs;Greenwald et al., 1998) and affective priming tasks (Fazio et al., 1995). Before we present and ap...

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Stalking the perfect measure of implicit self-esteem: The blind men and the elephant revisited?

Cited by 905 publications

References 53 publications

Method-Specific Variance in the Implicit Association Test.

Method-Specific Variance in the Implicit Association Test.

Explicit- and Implicit Bullying Attitudes in Relation to Bullying Behavior

Implicit measures: A normative analysis and review.

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