Cross-Lagged Panel Networks of Sleep Inertia Across Its Distinct Change Patterns Among Intern Nurses with Shift Work in China.

Nat Sci Sleep

Center for Studies of Psychological Application, School of Psychology, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, People's Republic of China.

Published: August 2024


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Article Abstract

Purpose: Although experimental psychopathology using PET, EEG, and fMRI is at the forefront of understanding the underlying mechanisms of sleep inertia, many questions concerning causality remain unanswerable due to ethical constraints and the use of small and heterogeneous samples in experimental methods. There is a pressing need for a novel perspective in a large and relatively homogeneous population to fully capture and elucidate longitudinal processes and dynamic causality that culminate in episodes of sleep inertia over time. Therefore, this study aimed to reveal the causal relationships between symptoms of sleep inertia across its distinct patterns.

Patients And Methods: A total of 1636 intern nurses participated in the first survey (94.1% validity rate), then 1277 intern nurses were followed up (82.9% tracing rate). Symptoms of sleep inertia were self-reported using the Sleep Inertia Questionnaire. The cross-lagged panel network models were used to examine unique longitudinal relationships between symptoms of sleep inertia across distinct trajectories.

Results: Four distinct trajectories of sleep inertia were established. Additionally, we found differences in those symptoms with the highest influence on other symptoms at the subsequent point across the networks of four trajectories, particularly, "Difficulty in concentrating" in the persistent-high group and "Feeling tense" in the deteriorating groups.

Conclusion: The current study highlights changes in sleep inertia based on the long-term course over time. Notably, symptoms of "Difficulty in concentrating" and "Feeling tense" are imperative to address these specific symptoms within subpopulations.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11316483PMC
http://dx.doi.org/10.2147/NSS.S467433DOI Listing

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