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Category: Project

Description: The congruence model of faking behavior is a well-known and often researched procedure for detecting faking on psychological self-report measures. However, previous research that has investigated the model’s applicability to faked data, has used scales with large numbers of items (more than 60 items) and has warned participants that faking can be detected. In applied assessment, lengthy scales and warnings may not be acceptable. With respect to scale length, the ongoing trend is to use increasingly shorter scales. As such, it becomes important to investigate whether the congruence model also applies to self-report measures with small numbers of items. In addition, it is unclear whether warning participants about faking detection is a necessary precondition for the successful application of the congruence model. This is especially important considering that it may not be best practices to inform test-takers that their faking can be detected. To address these issues, we re-analyzed data sets of two studies that investigated faking good and faking bad on extraversion (n = 255) and need for cognition (n = 146) scales. Re-analyses demonstrated that having only a few items per scale and not warning participants represent a challenge for the congruence model of faking. The congruence model of faking was only partly confirmed under these conditions. Although faking good on extraversion was associated with the expected longer latencies for incongruent answers, all other conditions remained non-significant. Thus, properties of the measurement and properties of the procedure affect whether the congruence model can be applied successfully.