Background Sleep disorders are common in people with intellectual disability (ID) and autism, with growing evidence of diverse sleep profiles across ID associated genetic syndromes. Documenting the prevalence and profile of specific sleep disorders in syndromes will quantify syndrome-driven ‘risk’, inform prognosis and enhance understanding of aetiology of sleep disorders. Method Following PRISMA guidelines for meta-analysis, we searched Ovid PsycINFO, Ovid MEDLINE, Ovid Embase, Web of Science and PubMed Central with use of syndrome-specific keywords and 60 sleep-related search terms. We screened and extracted papers that reported sleep disorder prevalence data for five or more individuals within a genetic syndrome, and applied quality criteria to produce a quality-effects prevalence model of six types of sleep disorder across nineteen syndromes. Relative risk estimates were calculated for the prevalence of each sleep disorder in each syndrome. Results Two hundred and seventy three papers were identified, generating 463 prevalence estimates for Angelman, CHARGE, Cornelia de Lange, Down, fragile X, Prader–Willi, Rett, Smith–Magenis and Williams syndromes, mucopolysaccharidoses (MPS disorders), neurofibromatosis and tuberous sclerosis complex. Prevalence estimates were higher in genetic syndromes than published equivalents for typically developing individuals, with few exceptions. Between-syndrome differences for some disorders were evident; sleep-disordered breathing was most prevalent in MPS disorders (72–77%), while excessive daytime sleepiness was highest in Smith–Magenis syndrome (60%). Conversely, insomnia, which was reported at a higher rate than TD estimates in all syndromes except fragile X, was not associated with specific genetic risk. This suggests insomnia could emerge because of the individual’s environment or associated developmental delay, rather than any specific genetic syndromes. Limitations Due to the broad scope of the meta-analysis, only syndromes previously identified as reporting preliminary sleep research were included. Other syndromes may also experience elevated prevalence rates of specific types of sleep disorder. Only English language papers were included. Conclusions Differing prevalence rates between types of sleep disorder suggest differing causal mechanisms, such as cranio-facial morphology in Down and Prader–Willi syndromes and the build-up of mucopolysaccharides in MPS disorders. Priorities for clinical assessment and intervention for sleep disorders are discussed.
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Background Smith–Magenis syndrome (SMS) is a rare genetic syndrome associated with a unique profile of early morning waking and daytime sleepiness. Children with SMS evidence high rates of self-injury and aggression and have a preference for adult over peer attention, with strong motivation to interact with a particular caregiver. In addition, people with SMS have lower adaptive functioning skills relative to cognitive abilities and demonstrate high levels of impulsivity. Taken together, these factors may result in individuals being awake overnight requiring vigilant caregiver supervision. Despite these complexities, no study has described the strategies caregivers take to keep their children with SMS safe overnight or considered the impact of these experiences on caregivers or the wider family. Methods The current study used a mixed-methods approach to consider sleep management strategies and challenges for caregivers of people with SMS at different ages. Caregivers completed an international online survey about sleep management and related difficulties, use of interventions and access to services and support. Semi-structured interviews were conducted with 14 caregivers in the UK to increase understanding of caregiver experiences and priorities for change in the UK context. Interviews were transcribed verbatim and coded using thematic analysis. Results Evidence from the online survey (n = 40) revealed wide-ranging impacts of poor sleep on the person with SMS and the wider family. Only 5% of caregivers reported that the sleep problems had no impact on their child, and 76% reported a moderately or extremely significant impact on themselves. For some individual caregivers, sleep management difficulties improved over time whereas for others no change was reported. Weekly respite emerged as the ideal provision for 49% of caregivers, although only 14% had access to this. The majority of caregivers (54%) received no respite. Thematic analysis of qualitative interviews revealed interactions between aspects of the behavioural phenotype of SMS which may contribute to complex and unusual presentations in relation to sleep management and safety. Conclusions Caregivers’ priorities for sleep management and support were delineated, with key implications for services in terms of the use of SMS-sensitive strategies and respite provision.
Background Aggressive behaviours are common in people with neurodevelopmental conditions, contributing to poorer quality of life and placement breakdown. However, there is limited empirical research documenting the prevalence and persistence of aggressive behaviours in autism. In this longitudinal study, aggressive behaviours were investigated in a sample of autistic individuals over 10 years. Methods Caregivers of autistic individuals, both with and without intellectual disability, completed questionnaires relating to the presence of aggressive behaviours at T1 [N = 229, mean age in years 11.8, standard deviation (SD) 5.9], T2 (T1 + 3 years, N = 81, mean age in years 15.1, SD 5.9) and T3 (T1 + 10 years, N = 54, mean age in years 24.5, SD 8.1). Analyses examined the presence and persistence of aggressive behaviours and the predictive value of established correlates of aggression. Results Aggressive behaviours were common at baseline (61.6%) but only persistent in 30% of the sample over 10 years. Higher composite scores of overactivity and impulsivity at T1 were significantly associated with the persistence of aggressive behaviours at T2 (P = 0.027) and T3 (P = 0.012) with medium effect size. Conclusions Aggressive behaviours are common in autism, but reduce with age. Behavioural correlates of attention deficit hyperactivity disorder (ADHD) predict the presence and persistence of aggressive behaviour and as such may be useful clinical indicators to direct proactive intervention resources to ameliorate aggressive behaviours.
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