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 assessed using the Clinical Evaluation of Language Fundamentals 4th Edition (CELF-4). W

SUBMITTER: Gasparini L 

PROVIDER: S-EPMC10952842 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature