Dataset Information

Should We Stop Looking for a Better Scoring Algorithm for Handling Implicit Association Test Data? Test of the Role of Errors, Extreme Latencies Treatment, Scoring Formula, and Practice Trials on Reliability and Validity.

ABSTRACT: Since the development of D scores for the Implicit Association Test, few studies have examined whether there is a better scoring method. In this contribution, we tested the effect of four relevant parameters for IAT data that are the treatment of extreme latencies, the error treatment, the method for computing the IAT difference, and the distinction between practice and test critical trials. For some options of these different parameters, we included robust statistic methods that can provide viable alternative metrics to existing scoring algorithms, especially given the specificity of reaction time data. We thus elaborated 420 algorithms that result from the combination of all the different options and test the main effect of the four parameters with robust statistical analyses as well as their interaction with the type of IAT (i.e., with or without built-in penalty included in the IAT procedure). From the results, we can elaborate some recommendations. A treatment of extreme latencies is preferable but only if it consists in replacing rather than eliminating them. Errors contain important information and should not be discarded. The D score seems to be still a good way to compute the difference although the G score could be a good alternative, and finally it seems better to not compute the IAT difference separately for practice and test critical trials. From this recommendation, we propose to improve the traditional D scores with small yet effective modifications.

SUBMITTER: Richetin J

PROVIDER: S-EPMC4481268 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Should We Stop Looking for a Better Scoring Algorithm for Handling Implicit Association Test Data? Test of the Role of Errors, Extreme Latencies Treatment, Scoring Formula, and Practice Trials on Reliability and Validity.

Richetin Juliette J Costantini Giulio G Perugini Marco M Schönbrodt Felix F

PloS one 20150624 6

Since the development of D scores for the Implicit Association Test, few studies have examined whether there is a better scoring method. In this contribution, we tested the effect of four relevant parameters for IAT data that are the treatment of extreme latencies, the error treatment, the method for computing the IAT difference, and the distinction between practice and test critical trials. For some options of these different parameters, we included robust statistic methods that can provide via ...[more]

PMID: 26107176

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Project description:BackgroundKnowing and, if necessary, altering competitive athletes' real attitudes towards the use of banned performance-enhancing substances is an important goal of worldwide doping prevention efforts. However athletes will not always be willing to reporting their real opinions. Reaction time-based attitude tests help conceal the ultimate goal of measurement from the participant and impede strategic answering. This study investigated how well a reaction time-based attitude test discriminated between athletes who were doping and those who were not. We investigated whether athletes whose urine samples were positive for at least one banned substance (dopers) evaluated doping more favorably than clean athletes (non-dopers).MethodsWe approached a group of 61 male competitive bodybuilders and collected urine samples for biochemical testing. The pictorial doping Brief Implicit Association Test (BIAT) was used for attitude measurement. This test quantifies the difference in response latencies (in milliseconds) to stimuli representing related concepts (i.e. doping-dislike/like-[health food]).ResultsProhibited substances were found in 43% of all tested urine samples. Dopers had more lenient attitudes to doping than non-dopers (Hedges's g?=?-0.76). D-scores greater than -0.57 (CI95?=?-0.72 to -0.46) might be indicative of a rather lenient attitude to doping. In urine samples evidence of administration of combinations of substances, complementary administration of substances to treat side effects and use of stimulants to promote loss of body fat was common.ConclusionThis study demonstrates that athletes' attitudes to doping can be assessed indirectly with a reaction time-based test, and that their attitudes are related to their behavior. Although bodybuilders may be more willing to reveal their attitude to doping than other athletes, these results still provide evidence that the pictorial doping BIAT may be useful in athletes from other sports, perhaps as a complementary measure in evaluations of the effectiveness of doping prevention interventions.

Project description:The Implicit Association Test (IAT) is a reaction time based categorization task that measures the differential associative strength between bipolar targets and evaluative attribute concepts as an approach to indexing implicit beliefs or biases. An open question exists as to what exactly the IAT measures, and here EEG (Electroencephalography) has been used to investigate the time course of ERPs (Event-related Potential) indices and implicated brain regions in the IAT. IAT-EEG research identifies a number of early (250-450 ms) negative ERPs indexing early-(pre-response) processing stages of the IAT. ERP activity in this time range is known to index processes related to cognitive control and semantic processing. A central focus of these efforts has been to use IAT-ERPs to delineate the implicit and explicit factors contributing to measured IAT effects. Increasing evidence indicates that cognitive control (and related top-down modulation of attention/perceptual processing) may be components in the effective measurement of IAT effects, as factors such as physical setting or task instruction can change an IAT measurement. In this study we further implicate the role of proactive cognitive control and top-down modulation of attention/perceptual processing in the IAT-EEG. We find statistically significant relationships between D-score (a reaction-time based measure of the IAT-effect) and early ERP-time windows, indicating where more rapid word categorizations driving the IAT effect are present, they are at least partly explainable by neural activity not significantly correlated with the IAT measurement itself. Using LORETA, we identify a number of brain regions driving these ERP-IAT relationships notably involving left-temporal, insular, cingulate, medial frontal and parietal cortex in time regions corresponding to the N2- and P3-related activity. The identified brain regions involved with reduced reaction times on congruent blocks coincide with those of previous studies.

Dataset Information

Should We Stop Looking for a Better Scoring Algorithm for Handling Implicit Association Test Data? Test of the Role of Errors, Extreme Latencies Treatment, Scoring Formula, and Practice Trials on Reliability and Validity.

Publications

Should We Stop Looking for a Better Scoring Algorithm for Handling Implicit Association Test Data? Test of the Role of Errors, Extreme Latencies Treatment, Scoring Formula, and Practice Trials on Reliability and Validity.

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