Sleepy drivers on a slippery road: A pilot study using a driving simulator

An Exploration of Self-Reported Sleep Inertia Symptoms Using Network Analysis

PURPOSE

Sleep inertia (SI) is the transitional state accompanied by compromised cognitive and physical performance and sleepiness. Network analysis offers a potential new framework to conceptualize a complex network of symptom-symptom interactions, and the network structure is analyzed to reveal the core characteristics. However, no previous study examined the network structure of SI symptoms. Thus, this study aimed to elucidate characteristics and compare sex differences of SI symptom networks in the general population.

MATERIALS AND METHODS

A total of 1491 participants from China were recruited from 30 May to 17 June, 2021. SI symptoms were assessed by using the Sleep Inertia Questionnaire (SIQ). The network structures were estimated and compared using network analytic methods in the R version 4.1.1.

RESULTS

Centrality properties analysis of the expected influence suggested that symptoms of "Feel sleepy", "Groggy, fuzzy or hazy mind", and "Dread starting your day" exerted greatest influences. The weighted adjacency matrix revealed that the "Dread starting your day" and "Anxious about the upcoming day" edge showed the strongest connection (edge weight value = 0.70). The network comparison test found no significant difference in network global strength (p=0.928), distribution of edge weights (p=0.194) and individual edge weights (all p values >0.05 after Holm-Bonferroni corrections) between males and females.

CONCLUSION

Symptoms of "Feel sleepy", "Groggy, fuzzy or hazy mind", and "Dread starting your day" were central in the SI symptom network. Intervention, such as the artificial dawn and change in body temperature, for symptoms of "Feel sleepy", "Groggy, fuzzy or hazy mind", and "Dread starting your day" might be crucial to hasten the dissipation of SI in the general population who may need to perform tasks upon waking.