Predicting sleep problems in children with autism spectrum disorders.
Rising aggression in ASD kids with good sleep predicts later bedtime battles.
01Research in Context
What this study did
The team followed children with autism who had no sleep issues at the start.
They tracked how much aggressive behavior each child showed.
One year later they checked who now had trouble sleeping.
What they found
Kids who were more aggressive at the start were the ones who later struggled with sleep.
The model caught most future sleep problems and rarely gave false alarms.
How this fits with other research
Kellems et al. (2016) looked at the same link the other way around. They found that night wakings best predict daytime aggression.
The two papers do not clash. One shows sleep trouble fuels aggression. The other shows early aggression flags later sleep trouble. Together they sketch a loop where each problem feeds the other.
Austin et al. (2015) used pain instead of aggression to forecast sleep issues. Adding aggression gives clinicians a second, easier-to-see warning sign.
Barton et al. (2019) later split aggression into verbal-only and verbal-plus-physical types. The combined type carried the heaviest sleep burden, sharpening the risk picture.
Why it matters
You now have a simple early-warning rule: if an ASD child shows rising aggression, plan a sleep screen even when nights look fine. Pair this with pain checks from Austin et al. (2015) and night-waking logs from Kellems et al. (2016) to catch problems before they snowball.
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02At a glance
03Original abstract
BACKGROUND: Sleep difficulties in children with autism spectrum disorders (ASD) have been well-established. AIMS: To develop a model to predict sleep problems in children with ASD. METHODS AND PROCEDURES: A sample of children in the Autism Speaks-Autism Treatment Network (ATN) registry without parent-reported sleep problems at baseline and with sleep problem (yes/no) data at first annual followup was randomly split into training (n = 527) and test (n = 518) samples. Model predictors were selected using the training sample, and a threshold for classifying children at risk was determined. Comparison of the predicted and true sleep problem status of the test sample yielded model performance measures. OUTCOMES AND RESULTS: In a multivariable model aggressive behavior among children with no sleep problems reported at baseline was associated with having more sleep problems at the first annual follow-up visit. This model performed in the test sample with high sensitivity and accurate prediction of low risk. CONCLUSIONS AND IMPLICATIONS: Among children with ASD aggressive behavior independently predicts sleep problems. The model's high sensitivity for identifying children at risk and its accurate prediction of low risk can help with treatment and prevention of sleep problems. Further data collection may provide better prediction through methods requiring larger samples.
Research in developmental disabilities, 2018 · doi:10.1016/j.ridd.2018.10.002