Using machine-learning methods to identify early-life predictors of 11-year language outcome

Abstract

Background: Language is foundational for neurodevelopment and quality of life, but an estimated 10% of children have a language disorder at age 5. Many children shift between classifications of typical and low language if assessed at multiple times in the early years, making it difficult to identify which children will have persisting difficulties and benefit most from support. This study aims to identify a parsimonious set of preschool indicators that predict language outcomes in late childhood, using data from the population-based Early Language in Victoria Study (n = 839). Methods: Parents completed surveys about their children at ages 8, 12, 24, and 36 months. At 11 years, children were ..