Arbitrary metrics in psychology.

Blanton, Hart; Jaccard, James

doi:10.1037/0003-066x.61.1.27

Cited by 602 publications

(481 citation statements)

References 36 publications

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“…On the startle-probe, however, the (same) smoking pictures significantly suppressed startle responses in comparison to neutral pictures and therefore acted in a similar fashion to positive pictures (Cuthbert et al, 1996). Put another way, on the IAT the smoking pictures appeared to receive an automatic negative evaluation (but see comments above on the IAT's zero point, Blanton and Jaccard, 2006), whereas on the startle-probe they appeared to receive an automatic positive evaluation. This might be explained if the societal influences noted above impact the IAT effect more than startle-probe responses.…”

Section: Discussionmentioning

confidence: 96%

“…A negative IAT effect has generally been interpreted in the literature as reflecting a negative implicit attitude to smoking (preference for smoking over not smoking). Blanton and Jaccard (2006) have argued that the location of the IAT's zero point has not yet been firmly established, and so the meaning of absolute IAT scores is uncertain. On the other hand, Greenwald et al, (2006) provided evidence that the observed zero point corresponds to the true zero point in one context (preference for one presidential candidate over another).…”

Section: Discussionmentioning

confidence: 99%

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Implicit attitudes to smoking are associated with craving and dependence

Waters

Carter

Robinson

et al. 2007

Drug and Alcohol Dependence

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The Implicit Association Test (IAT) has been used to assess automatic affective responses to drug cues. Smokers (N = 57) completed the IAT at four experimental sessions. They abstained from smoking before two of the sessions (AB), and smoked normally before the other two sessions (NON). At one AB (and NON) session, they smoked a cigarette about 40 minutes before completing the IAT (S), and at the other they did not smoke (NS). Overall, participants exhibited a negative IAT effect, indicating that they found the classification task easier when smoking was paired with bad than when smoking was paired with good. Using repeated measures ANOVA, the IAT effect was made less negative by pre-session Abstinence, and made more negative by Smoking. It was most negative in the NON-S condition. Using Generalized Estimating Equations analyses, the IAT effect was positively associated with pre-task craving ratings assessed on the Questionnaire of Smoking Urges-Brief, but was not associated with a physiological measure of automatic affective responses (startles while viewing smoking vs. neutral pictures). The IAT effect was associated with scores on the Fagerstrom Test for Nicotine Dependence. In sum, automatic affective responses assessed with the smoking IAT are associated with measures of smoking motivation and dependence.

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Section: Discussionmentioning

confidence: 96%

Section: Discussionmentioning

confidence: 99%

Implicit attitudes to smoking are associated with craving and dependence

Waters

Carter

Robinson

et al. 2007

Drug and Alcohol Dependence

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“…For instance, even if racial attitudes are a direct cause of scores on a racial IAT, it is not certain that a zero score on the racial IAT means that the person likes Black and White individuals to the same extent. Because of this fact, the IAT effect shown by a particular individual can be interpreted only by comparing it with the IAT effects of other persons (e.g., Person A has more positive attitudes toward White persons or less positive attitudes toward Black persons than does Person B; but see Greenwald, Nosek, & Sriram, 2006, for a critique of Blanton & Jaccard, 2006).…”

Section: Iat Effects the What Criterion: What Attributes Cause Variatmentioning

confidence: 99%

Implicit measures: A normative analysis and review.

Houwer¹,

Teige‐Mocigemba

Spruyt³

et al. 2009

Psychological Bulletin

729

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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“…Importantly, the IAT can only measure relative attitudes (e.g., attitudes to fat people relative to attitudes to thin people). It is therefore impossible to determine using the IAT whether this bias is the result of a strong/weak pro-thin bias, a strong/weak anti-fat bias or some combination of the two (see Blanton & Jaccard, 2006;Roddy, Stewart, & Barnes-Holmes, 2011;2012). Likewise, the IAT cannot be used to determine how interventions that aim to increase or reduce implicit biases have their effect (e.g., a difference in implicit attitudes could be reduced by acting on the 'Thin Person' category, the 'Fat Person' category, or both; see Lai et al, in press).…”

Section: Absolute Vs Relative Measures Of Implicit Cognitionmentioning

confidence: 99%

Measuring implicit attitudes: A positive framing bias flaw in the Implicit Relational Assessment Procedure (IRAP).

O’Shea

Watson

Brown

2016

Psychological Assessment

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How can implicit attitudes best be measured? The Implicit Relational Assessment Procedure (IRAP), unlike the Implicit Association Test (IAT), claims to measure absolute, not just relative, implicit attitudes. In the IRAP, participants make congruent (Fat Person-Active:False; Fat Person-Unhealthy: True) or incongruent (Fat Person-Active: True; Fat PersonUnhealthy: False) responses in different blocks of trials. IRAP experiments have reported positive or neutral implicit attitudes (e.g., neutral attitudes towards fat people) in cases where negative attitudes are normally found on explicit or other implicit measures. It was hypothesized that these results might reflect a Positive Framing Bias (PFB) that occurs when participants complete the IRAP. Implicit attitudes towards categories with varying prior associations (nonwords, social systems, flowers and insects, thin and fat people) were measured. Three conditions (standard, positive framing, and negative framing) were used to measure whether framing influenced estimates of implicit attitudes. It was found that IRAP scores were influenced by how the task was framed to the participants, that the framing effect was modulated by the strength of prior stimulus associations and that a default PFB led to an overestimation of positive implicit attitudes when measured by the IRAP. Overall, the findings question the validity of the IRAP as a tool for the measurement of absolute implicit attitudes. A new tool (Simple Implicit Procedure: SIP) for measuring absolute, not just relative, implicit attitudes is proposed. Implicit attitudes are automatic evaluations that occur outside conscious awareness and are measured without requiring respondents to introspect on their feelings. Explicit attitudes in contrast are the result of deliberate introspection and controlled evaluative judgment (Greenwald & Banaji, 1995). One reason for measuring implicit attitudes is that participants may use self-presentation tactics or respond in a socially desirable manner on explicit self-reports to avoid being perceived as prejudiced. Implicit measures can also be useful in areas where participants might be unwilling to reveal personal psychological attributes or are unaware of these psychological attributes (for a review of implicit attitudes and the tools used to measure them see Gawronski & De Houwer, 2014).The current gold standard method for assessing implicit attitudes is the Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998) and this tool has been increasingly used in clinically relevant areas (see https://implicit.harvard.edu/implicit/pimh/).The IAT has shown promise in predicting self-harm (Randall, Rowe, Dong, Nock, & Colman 2013), social anxiety disorders (Teachman & Allen, 2007) and suicidal ideation (Harrison, Stritzke, Fay, Ellison, & Hudaib, 2014). The current study questions the validity of a recently developed implicit measure, the Implicit Relational Assessment Procedure (IRAP; BarnesHolmes, Barnes-Holmes, Stewart, & Boles, 2010a), which has also been u...

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Arbitrary metrics in psychology.

Cited by 602 publications

References 36 publications

Implicit attitudes to smoking are associated with craving and dependence

Implicit attitudes to smoking are associated with craving and dependence

Implicit measures: A normative analysis and review.

Measuring implicit attitudes: A positive framing bias flaw in the Implicit Relational Assessment Procedure (IRAP).

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