2026/01/01 by Yuke Yang, Zhihao Ma · 1 voice
Psychology · Neuroscience · Decision Sciences · #Cultural Differences and Values #Psychology of Moral and Emotional Judgment #Ethics in Business and Education
paper · doi:10.1525/collabra.162286
openalex publication_date 2026/01/01 · openalex created_date 2026/06/10 · openalex updated_date 2026/07/22
Moral foundations theory (MFT) posits cross-cultural regularities in moral values. Its primary measure, the Moral Foundations Questionnaire-1 (MFQ-1), has faced persistent questions about structural validity and measurement invariance. Using data from the COVIDiSTRESS II survey (N = 9,987 across 21 countries), we evaluated the psychometric properties of the MFQ-1 short-form (MFQ-1-SF) judgment section. Across the full sample and subgroups defined by sex, age, education, and country, the confirmatory factor analysis (CFA) results indicated that none of the candidate models achieved acceptable fit. Only the individualizing–binding (IB) bifactor model showed acceptable fit in the Portugal and Ukraine samples. In the exploratory structural equation modeling (ESEM) analyses, the ESEM within CFA (EwC) three-factor (autonomy, community, and divinity) model provided the best overall fit; however, subgroup analyses showed that this model achieved acceptable fit only in the established-adulthood subgroup and good fit in the Colombia sample. Multi-group analyses based on change-in-fit criteria suggested strict invariance across age and education groups and scalar invariance across sex. Nevertheless, the repeated occurrence of Heywood cases throughout the invariance sequence indicated inadmissible and potentially unstable solutions, limiting confidence in these invariance conclusions. Overall, the present findings offer limited support for the structural validity and cross-group comparability of the MFQ-1-SF judgment subscale in this dataset. These findings highlight the limitations of ultra-brief, judgment-only instruments and suggest that future evaluations of the MFQ—particularly judgment-only versions such as the MFQ-2—may benefit from modeling a general factor to account for shared variance across items or from using ESEM to obtain a more flexible representation. However, such results should be interpreted with caution and require further corroboration in future research.