A Brief Version of the Implicit Positive and Negative Affect Test (IPANAT-18)

Psychol Belg. 2020 Sep 16;60(1):315-327. doi: 10.5334/pb.544.

Abstract

As self-reports of affect are limited in several regards, an indirect measure of affect, the Implicit Positive and Negative Affect Test (IPANAT; Quirin, Kazén, & Kuhl, 2009) has previously been developed and adapted to more than 10 languages (Quirin et al., 2018), showing adequate reliability and validity. Based on a sample of 242 Spanish adults (111 males), we evaluate a trimmed 18 items version of the IPANAT (IPANAT-18). Item reductive procedures consisted in a random selection of the stimuli words used in the IPANAT. Psychometric properties of the IPANAT-18 were evaluated via Confirmatory Factor Analysis. In addition, correlational analyses were used to determine the relationship between the brief and the full version of the IPANAT, and with explicit measures of affect. We replicated a two-factors structure of positive affect versus negative affect and found a good fit for the IPANAT-18 model (CFI = 1; TLI = 1; RMSEA = .00; SRMR = .03). Reliability was adequate (implicit PA, α = .86; implicit NA, α = .77) and the pattern of relationships with explicit affect measures were congruent and consistent with previous findings. Differences between the mean scores of implicit affect assessed with 18 items or 36 items were statistically non-significant, and showed strong correlations (PA, r = .92, p < .01; NA, r = .88, p < .01). In sum, the IPANAT-18 showed satisfactory psychometric properties and constitutes a useful tool for economically measuring affective processes such as in experimental and economical multiple assessment (e.g., daily diary) settings.

Keywords: IPANAT; implicit affect; psychometric properties.

Grants and funding

This work was partially made possible through a grant from the Templeton Rlg. Trust (TRT 0119) supporting MQ and GPH; by the National Council for Science and Technology of Mexico (CONACyT) supporting GPH, and the Spanish Government (under Grant PSI2016-76411-R) supporting GPH, SE and TR. Special thanks to Cafer Bakac for providing advice regarding analysis.