Evaluating motion detection to score sleep disturbance for children: A translational approach to developing a measurement system

Sleep in Children with Autism Spectrum Disorder: A Narrative Review and Systematic Update

Purpose of Review

Sleep problems are a common comorbidity for children with autism spectrum disorder (ASD), and research in this area has a relatively long history. Within this review, we first outline historic patterns in the field of sleep and ASD. Second, we conducted a systematic update and coded these studies based on their alignment with historic patterns. Research on ASD and sleep over the past two decades has primarily focused on four principal areas: (1) documenting the prevalence and types of sleep problems; (2) sleep problem treatment options and efficacy; (3) how sleep problems are associated with other behavioral, contextual, or biological elements; and (4) the impact of child sleep problems on families and care providers. The systematic update in this paper includes empirical studies published between 2018 and 2021 with terms for sleep and ASD within the title, keywords, or abstract.

Recent Findings

In sum, 60 studies fit the inclusion/exclusion criteria and most fit within the historic patterns noted above. Notable differences included more global representation in study samples, studies on the impacts of COVID-19, and a growing body of work on sleep problems as an early marker of ASD. The majority of studies focus on correlates of sleep problems noting less optimal behavioral, contextual, and biological elements are associated with sleep problems across development for children with ASD.

Summary

Recommendations for future directions include continued expansion of global and age representation across samples, a shift toward more treatment and implementation science, and studies that inform our mechanistic understanding of how sleep and ASD are connected.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40675-022-00234-5.

Behavioral assessment and faded bedtime intervention for delayed sleep-onset in an adult with autism spectrum disorder

Faded bedtime has been evaluated as a behavioral intervention for delayed sleep-onset principally with children and youth who have intellectual and developmental disabilities in hospital and home settings. The present case report describes behavioral assessment and faded bedtime intervention in a 21-year old adult man with autism spectrum disorder at a community-based group home. The study also documented the effects of family home visits on the man's sleep when he returned to the group home. Compared to a pre-intervention (baseline) phase, faded bedtime was associated with increased intervals of recorded sleep and a decrease in sleep-onset latency over several months of implementation. We discuss clinical implications of the case and generality of findings across populations and settings.

Applied behavior analysis measurement, assessment, and treatment of sleep and sleep-related problems

This discussion article considers applied behavior analysis measurement, assessment, and treatment of sleep and sleep-related problems among infants, children, and youth who are typically developing and have neurodevelopmental disabilities. Measurement has concentrated on designing practitioner-implemented methods and improving fidelity of data recording through sleep-monitoring instrumentation. The emphasis of assessment is identifying antecedent and consequence variables that promote sleep and evoke and maintain sleep-related problems. Treatment research has evaluated several effective interventions for problems such as delayed sleep-onset, night and early morning waking, bedtime resistance, and unwanted co-sleeping. Early and contemporary applied behavior analysis research is reviewed relative to function-based treatment formulation, intervention integrity, social validity, and research-to-practice translation.

Video Analysis of Parent-Child Interactions in Behavioral Sleep Disorders: Development of a Scoring Algorithm

Introduction: Behavioral sleep disorders, including chronic insomnia (CI), are generally assessed by subjective parent interview. However, evidence suggests that parental report of children's overnight behaviors is unreliable, perhaps due to recall bias or confusion due to sleep deprivation. Video technology has been used clinically to capture complex behavioral disorders in children during the day. However, there is no standardized means of analyzing child and parent behavior at bedtime or during the night. We aimed to create an algorithm for this purpose. Methods: Child brain tumor survivors (a population previously shown to have a high prevalence of CI) were screened for difficulties initiating and maintaining sleep using sub-scales from the Sleep Disturbance Scale for Children. Those who screened positive (n = 3) then completed a detailed parent interview to confirm a clinical diagnosis of CI. One night of home video footage was obtained from initial settling period to morning waking (SOMNOmedics camera). Footage was imported into BORIS^© software and a coding system for parent and child behavior was developed over multiple iterations until agreeable inter-rater reliability (>70%) was achieved between two independent coders. Results: The final coding categories were: 1) time domains, 2) physical environment, 3) child global status, 4) location, 5) activity, and 6) physical interaction. This achieved 74% inter-reliability in its last iteration. Discussion: A statistically acceptable behavior scoring algorithm was achieved. With further development, this tool could be applied clinically to investigate behavioral insomnia and in research to provide more objective outcome measurement.