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Prevalence of language and pre-literacy difficulties in an Australian cohort of 5-year-old children experiencing adversity.

Jodie SmithPenny LevickisRoslyn NeilsonFiona MensahSharon R GoldfeldHannah Elise Bryson
Published in: International journal of language & communication disorders (2021)
This is the first empirical Australian-based study highlighting the high prevalence and co-occurrence of language and pre-literacy difficulties in preschool children experiencing social adversity. Clinicians should be aware of co-morbid language and pre-literacy difficulties in disadvantaged populations and consider both areas during assessment and intervention planning. What this paper adds What is already known on the subject The prevalence of language and literacy difficulties is substantially higher in cohorts experiencing social adversity when compared with more advantaged families. There is some evidence that adversity also contributes to pre-literacy difficulties, but less is known here. What this paper adds to existing knowledge This study presents new prevalence data showing high rates of language and pre-literacy difficulties for 5-year-old children experiencing adversity within an Australian context. It is the first to explore these skills in a large cohort of pre-schoolers recruited from community settings in Australia. What are the potential or actual clinical implications of this work? In this cohort experiencing adversity, most children who presented with language difficulties likewise exhibited pre-literacy difficulties. This concordance reflects how early oral language and pre-literacy skills develop together. Clinicians should assess both skills in preschool populations-especially those working with children experiencing adversity-to ensure all children have strong foundations to become proficient beginner readers.
Keyphrases
  • early life
  • health information
  • autism spectrum disorder
  • healthcare
  • risk factors
  • young adults
  • randomized controlled trial
  • mental health
  • machine learning
  • climate change
  • big data
  • deep learning