Abstract
Background: Self-report measures of affective states (i.e., explicit measure) underlie a variety of cognitive biasing factors. Therefore, measures for the indirect assessment of affect (i.e., implicit) have previously been developed, such as the Implicit Positive and Negative Affect Test. The IPANAT asks participants to make judgments about the degree to which artificial non-sense words sound like affective states, and has demonstrated good reliability and validity. Methods: We created a Spanish version of this test (IPANAT-SPAIN). After adapting artificial words to Spanish language, based on preliminary studies, the IPANAT-SPAIN was administered to a representative sample of N = 468 adults from Spain (225 men). Competing models of its latent structure were evaluated using confirmatory factor analysis. To assess convergent validity, we correlated the IPANAT-SPAIN with explicit measures of affect. Results: The best-fitting model consisted of two factors corresponding to positive implicit affect (PA) and negative implicit affect (NA). Reliability of the IPANAT-SPAIN was a = .94 for PA, and a = .88 for NA. The pattern of relationships between the IPANAT-SPAIN and explicit affect measures were consistent with previous findings. Conclusions: The results indicate that the Spanish adaptation of the IPANAT has satisfactory psychometric properties.
