A network analysis of insomnia symptoms in young adults

Hao Fong Sit, Forrest Tin Wai Cheung, Xiao Li, Ngan Yin Chan, Joey Wing Yan Chan, Yun-Kwok Wing, Shirley Xin Li

Abstract

Introduction: Insomnia is highly common in young adults with a prevalence rate up to 38%. It is associated with not only significant personal distress but also a wide array of symptoms affecting both daytime and nighttime functioning in young people. However, little is known about the interplay of these symptoms in the context of insomnia. Network analysis is a novel approach to understand the underlying mechanisms of a health-related issue at the symptom level. The current study aimed to investigate the network structure of insomnia in youths.

Materials and Methods: A total of 902 participants (Age: 21.20 ± 2.64, female: 70.29%) were recruited from the community. Participants completed Insomnia Severity Index (ISI) online, which is a 7-item self-reported questionnaire to assess different aspects of insomnia including its nocturnal symptoms (difficulties initiating or maintaining sleep, early morning awakening), severity, and consequences. An ISI score between 8-14 denoted subthreshold insomnia and a cutoff score of 15 was used to determine moderate to severe insomnia. Network analysis was applied to all 7 items using regularized partial correlation network modeling in R. Three centrality indices (i.e., “strength”, “closeness”, and “betweenness”) were used to assess the importance of symptoms in the network.

Results: Forty-one percent and 14.3% of the recruited participants were considered to have subclinical insomnia and clinical insomnia, respectively. The network model revealed that distress caused by the sleep difficulties was the most central symptom in youths with the strongest strength, betweenness, and closeness. The network model demonstrated robust accuracy and stability (Node strength: CS (cor=0.70) = 0.75). Dissatisfaction with sleep was connected to the cluster of nocturnal symptoms (i.e., difficulty initiating sleep, difficulty maintaining sleep, and early morning awakening) and daytime symptoms (noticeability of sleep problems by others, distress caused by the sleep difficulties, and impairment in daytime functioning) of insomnia.

Conclusion: This was the first study to characterize the network structure of insomnia symptoms in young adults using the network approach. Distress caused by the sleep difficulties was identified as the core symptom in the network, indicating that future interventions could target worries or distress to address insomnia. Future interventions may also target dissatisfaction with sleep to address both clusters of nocturnal symptoms and daytime symptoms.

Recommended citation: Sit, H. F., Cheung, F. T. W., Li, X., Chan, N. Y., Chan, J. W., Wing, Y. K., & Li, S. X. (2022). A network analysis of insomnia symptoms in young adults. Sleep Medicine, 100, S108.