Halstead EJ, Sullivan EC, Dimitriou D
Front Psychiatry 12 (-) 708339 [2021-09-21; online 2021-09-21]
Background: The longer-term impact of the pandemic on autistic adults' sleep are yet to be revealed, with studies concentrating on sleep in autistic children or mental health outcomes and coping strategies of autistic adults. Given the prevalence of sleep problems experienced by autistic adults and the changes in routine that have occurred as a result of COVID-19 societal restrictions, this study assessed the impact of the COVID-19 pandemic on sleep problems via a longitudinal subjective assessment method. Methods: Sleep data were gathered at three time points from 95 autistic adults, namely prior to the pandemic, at the start of COVID-19 and several months into COVID-19 to obtain a rich longitudinal dataset ascertaining how/if sleep patterns have changed in autistic adults over these several months. Results: In comparison to pre-lockdown, several sleep components were shown to improve during the lockdown. These improvements included reduced sleep latency (time taken to fall asleep), longer sleep duration, improved sleep efficiency, improved sleep quality, as well as improved daytime functioning. Pre-sleep cognitive arousal scores were found to decrease compared to pre-lockdown, meaning cognitive arousal improved. Approximately 65% of participants reported that they felt their sleep had been impacted since COVID-19 since Time 1, with the most common reasons reported as waking up exhausted (36.92%), not being able to get to sleep (33.85%), waking up in the night (29.23%), having a disrupted sleep pattern (27.69%), and nightmares (18.46%). Conclusions: Improvements in sleep may be related to societal changes (e.g., working from home) during the pandemic. Some of these changes are arguably beneficial for autistic adults in creating a more autism-inclusive society, for example telehealth opportunities for care. Further exploration of the associations between mental health and sleep are warranted.
Research Area: Data-driven research – models and AI