In the present study we applied a validation strategy for implicit measures like the IAT, which complements multitrait-multimethod (MTMM) analyses. As the measurement method (implicit vs. explicit) and underlying representation format (associative vs. propositional) are often confounded, the validation of implicit measures has to go beyond MTMM analysis and requires substantive theoretical models. In the present study (N = 133), we employed such a model ( Hofmann, Gschwendner, Nosek, & Schmitt, 2005 ) and investigated two moderator constructs in the realm of anxiety: specificity similarity and content similarity. In the first session, different general and specific anxiety measures were administered, among them an Implicit Association Test (IAT) general anxiety, an IAT-spider anxiety, and an IAT that assesses speech anxiety. In the second session, participants had to deliver a speech and behavioral indicators of speech anxiety were measured. Results showed that (a) implicit and explicit anxiety measures correlated significantly only on the same specification level and if they measured the same content, and (b) specific anxiety measures best predicted concrete anxious behavior. These results are discussed regarding the validation of implicit measures.
A Parallel-Computing Approach for Vector Road-Network Matching Using GPU Architecture
