Examination of the psychometric properties of the Ethnic Identity Scale (EIS) and Multicultural Identity Integration Scale (MULTIIS) in a multiracial population in the United States.

Ethnic identity is theorized to be a critical aspect of human development and is shown to be associated with health and well-being. The Ethnic Identity Scale is a widely used measure that assesses key aspects of ethnic identity development (Umaña-Taylor et al., 2004). The Multicultural Identity Integration Scale (MULTIIS) is a measure that has been more recently developed to assess key aspects of identity integration for individuals with multicultural identities (Yampolsky et al., 2016). Despite the ongoing utilization of these instruments, a comprehensive psychometric evaluation within Multiracial populations has yet to be established in extant literature. Addressing this gap, the present study aims to examine the internal consistency, factor structure, and other psychometric characteristics of the Ethnic Identity Scale and MULTIIS within a sample of 1,012 Multiracial adults in the United States. The majority of the sample identified as female (67.5%, n = 683), straight (80.1%, n = 798), having attained less than a college degree (62.3%, n = 627), and having a household income less than $60,000 (57.4%, n = 552). The majority of participants (55%, n = 557) were classified as having White and non-White racial/ethnic backgrounds, 45.0% (n = 455) as non-White. Findings suggest the Ethnic Identity Scale fits the data poorly by all measures, despite supporting the three-factor structure recommended in the original study; the MULTIIS fits the data acceptably by all measures and supports both a three-factor first-order and eight-factor second-order structure recommended in the original study. Analyses of the MULTIIS three-factor first-order model's measurement invariance across race, gender, educational attainment, and household income identified variance for specific latent factors. Overall, the MULTIIS performed acceptably; however, studies relying on the MULTIIS should account for differential measurement. Implications for clinical, scientific, and public health practice are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).