Identifying early developmental profiles of 5-year-olds: a latent profile analysis using IELS 2018 data

Abstract Background Previous research in early childhood development has largely focused on isolated skills in early childhood development, often neglecting the complex, interconnected nature of developmental skills. In addition, studies have typically overlooked potential heterogeneity in developmental pathways that may arise from individual differences across multiple skill domains. This study addresses these gaps by adopting a multifactorial approach in order to examine the interrelations among cognitive (emergent literacy, emergent numeracy, working memory, mental flexibility, and inhibition) and social-emotional (emotion identification and emotion attribution) skills in 5-year-old children, using data from three large, nationally representative samples. Methods We used data from the 2018 International Early Learning and Child Well-being Study (IELS), conducted in England, Estonia and the United States. Latent Profile Analysis (LPA) was employed to identify early developmental profiles based on children’s cognitive and social-emotional skills. We then conducted a multinomial regression analysis to examine how profile membership was associated with children’s background characteristics. Results Across all three countries, we consistently identified four distinct early developmental profiles: low achieving, low-average achieving, average-high achieving and high achieving. Contrary to our expectations, the differences between profiles were quantitative rather than qualitative. Age emerged as a strong and consistent predictor of profile membership, with older children more likely to be classified within the higher-achieving profiles. In contrast, associations between sex, socioeconomic status (SES), and profile membership were less consistent and varied both across countries and among profiles. Conclusions The findings highlight the multidimensional and interrelated nature of early cognitive and social-emotional development. They underscore the value of person-centered approaches for capturing individual variation and call attention to the importance of considering age-related differences when assessing early learning outcomes.