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PHYSIOLOGICAL AND FAMILIAL PREDICTORS OF SLEEP QUALITY IN AUTISTIC ADOLESCENTS

Abstract

Adolescents on the autism spectrum commonly experience sleep-related difficulties such as insomnia and nightmares, and prior studies have sought to understand whether physiological or family-level measures serve as better predictors for sleep quality in this population. The current study sought to conceptually replicate and extend to an autistic adolescent sample a prior study that had found respiratory sinus arrhythmia (RSA), a physiological measure of parasympathetic nervous system activity, to predict sleep quality in autistic children. Additionally, the current study examined potential family-level predictors of sleep quality in autistic adolescents. 107 adolescents on the autism spectrum who were verbal and their parents participated in the study. Parents were asked to participate in a discussion about a topic that caused disagreement in their relationship. Then, adolescents watched a nature video as their baseline RSA was measured and watched the recorded video of their parents’ conflict discussion as their reactivity RSA was measured. Parents completed questionnaires measuring marital conflict, and adolescents completed questionnaires measuring their sleep quality and family functioning. The current study did not conceptually replicate the findings of a prior study that had found RSA, a physiological measure, to be a significant predictor of sleep quality in autistic children. Rather, the current study found that measures of family context, especially those of marital conflict, were a significant predictor of children’s sleepiness above and beyond RSA levels. This failure to conceptually replicate the prior study could have occurred for several reasons, two of which being that the sample in the current study was older and that the current study relied on a child-report of sleep quality. Future directions may include studying child and adolescent samples who are nonverbal and/or have an IQ <70, recruiting more girls on the autism spectrum, and studying child samples as opposed to only adolescents.

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