A multi-method multi-trait test of the dual-attitude perspective

The dual-attitude perspective posits that it is useful for research and theory to assume two distinct constructs: explicit and implicit attitudes (or automatic and deliberate evaluation). Much evidence supports this perspective, but some important tests are missing, casting doubts on studies that relied on the perspective for inference. We used a multimethod multitrait design to extensively test the validity of the dual perspective. The dataset (N = 24,015) included measurements of attitudes in 3 domains (race, politics, the self) with 7 indirect measures, and at least 3 self-report measures for each attitude domain. The dual-attitude model fit the data better than a single-attitude model. Six of the 7 indirect measures were related to the implicit construct more than to the explicit construct. The evidence supports the dual-attitude perspective, bolsters the validation of 6 indirect measures, and clears doubts from countless previous studies that used only one indirect measure to draw conclusions about implicit attitudes