Abstract
The aim of the present study was to develop and validate the Immigration-Related Political Ideology Scale (IRPIS), designed to measure diverse political perspectives on immigration among US voters. The IRPIS was developed following a series of focus groups and refined through a systematic item-generation process involving expert panels. The scale was validated using a two-step factor analysis with a nationally representative sample of 1292 US voters, divided into exploratory (n = 632) and confirmatory (n = 660) sub-samples. The exploratory factor analysis identified seven distinct factors: conservative views, welcoming attitudes, world regions, flexibility, assimilationist expectations, multicultural expectations, and undocumented immigrant rights. Confirmatory factor analysis provided an acceptable fit (CFI = .901; RMSEA = .050), and the scale demonstrated high internal consistency (Cronbach’s alphas ranging from .89 to .97). Inter-factor correlations varied, with strong links observed among welcoming attitudes, flexibility, and multicultural expectations (r’s > .80), confirming a polarization between liberal and conservative stances on immigration. These findings suggest that the IRPIS is the first scale specifically designed to assess immigration-related political orientations in a polarized US context. This tool has important implications for political strategy and policymaking, especially in the context of rising immigration rates and political polarization.
Public Significance Statement
The present study validates the Immigration-Related Political Ideology Scale (IRPIS) using a nationally representative sample of 1292 US voters. Immigration remains a highly polarizing issue, with deeply entrenched ideological differences influencing policy preferences and public discourse. Exploratory factor analysis identified seven distinct factors and confirmed a clear polarization between liberal and conservative views on immigration. The IRPIS represents a critical tool for research, political strategy, and policymaking.