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Predicting sleep problems in children with autism spectrum disorders

Amy M Shui1, Terry Katz2, Beth A Malow3

  • 1Biostatistics Center, Massachusetts General Hospital, 50 Staniford Street, Suite 560, Boston, MA 02114, USA.

Research in Developmental Disabilities
|November 6, 2018
PubMed

Insights

Aggressive behavior in children with autism spectrum disorder (ASD) can predict future sleep problems. A new model accurately identifies children at risk, aiding in early intervention and prevention strategies.

Area of Science:

  • Pediatric Sleep Medicine
  • Autism Spectrum Disorder Research
  • Behavioral Health

Background:

  • Sleep difficulties are common in children with autism spectrum disorder (ASD).
  • Existing research highlights the prevalence of sleep issues in this population.
  • Understanding predictors of sleep problems is crucial for intervention.

Purpose of the Study:

  • To develop and validate a predictive model for sleep problems in children with ASD.
  • To identify key behavioral indicators associated with sleep difficulties.
  • To improve early identification and management of sleep disturbances.

Main Methods:

  • A cohort of children from the Autism Speaks-Autism Treatment Network (ATN) registry was analyzed.
  • Children without baseline sleep problems were randomly assigned to training (n=527) and testing (n=518) sets.
  • A multivariable model was developed using the training set to predict sleep problems at follow-up.

Main Results:

  • Aggressive behavior at baseline was significantly associated with increased sleep problems at follow-up in children with ASD.
  • The predictive model demonstrated high sensitivity in identifying children at risk.
  • The model accurately predicted low risk for sleep problems in the test sample.

Conclusions:

  • Aggressive behavior is an independent predictor of sleep problems in children with ASD.
  • The developed model offers a sensitive tool for early risk identification and prevention.
  • Further research with larger datasets may enhance predictive accuracy and clinical utility.
Abstract

Keywords:
AggressionAsthmaAutism spectrum disorderNeurodevelopmental disordersSleep

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