The Development and Validation of the Primary Affect Inventory (PAFI), a Self-Rating Questionnaire for the Measurement of Primary Affective States

= 34.79 y, SD = 11.63 y). Based on sample 1 reliability was estimated via McDonald's omega, structural validity using exploratory graph analysis (EGA), convergent and criterion validity were assessed through correlations with primary affective traits (BANPS-GL), Big Five personality traits (BFI-K), and psychiatric symptoms (ISR). Using sample 2, the proposed latent structure was investigated by a confirmatory factor analysis (CFA). All subdomains showed good to excellent internal consistency (ω ≥ 0.88). EGA identified seven communities corresponding to the predefined primary affects. Overall, correlation analyses supported expected relationships between PAFI subdomains, personality, and symptoms. CFA confirmed excellent fit for the correlated subdomains model, while a two-higher-order-factor model showed acceptable fit. Finally, invariance analysis of the factor-structure in both samples suggested full measurement invariance up to the scalar level. PAFI demonstrates strong psychometric properties, including reliability, structural validity, convergent and criterion validity. Its brief format and straightforward language make it suitable for efficiently assessing primary affective states across populations.