Network structure of REM sleep behavior disorder symptoms in iRBD patients
Minji Lee1, Hyun Seok Do2, Jung Kyung Hong3
1Department of Psychiatry, Soonchunhyang University Seoul Hospital, Seoul, 04401, Republic of Korea.
Objective:
Employing the REM Sleep Behavior Disorder Questionnaire-Hong Kong (RBDQ-HK) to investigate symptoms and their severity in rapid eye movement (REM) sleep behavior disorder (RBD) patients, this study delves into the construct of RBD through the RBDQ-HK and its links to depression and sleep quality.
Methods:
Data from the RBDQ-HK, the Geriatric Depression Scale (GDS), and the Pittsburgh Sleep Quality Index (PSQI) were compiled from individuals with isolated RBD (iRBD) confirmed by polysomnography. We constructed a network analysis of the RBDQ-HK, measured the centrality of each symptom (node), conducted Exploratory Graph Analysis (EGA) to unveil the dimension structure of the questionnaire, and calculated bridge expected influence (BEI) to identifying critical bridge. Multivariate linear regression was also employed to discover relationships between RBDQ-HK dimensions and variables such as PSQI and GDS.
Results:
In our cohort of 455 iRBD patients (299 males), the items in the RBDQ-HK were divided into three dimensions: dream, movement, and SRI/violence. The symptoms identified as most central to RBD were 'shouting or yelling in sleep', 'dream-enacting movements', and 'talking during sleep'. The highest (BEI) was 'violent and aggressive dreams', which has the potential to bridge three dimensions within the symptom network. Depression was significantly correlated with the movement and dream dimensions of RBD, and sleep quality was predominantly related to the dream dimension score.
Conclusion:
Our findings verify that the principal symptoms of the RBDQ-HK align with the established diagnostic criteria and reveal a three-dimensional structure within RBD symptoms. The relationships between the RBD symptoms, depression, and sleep quality need to be identified for the effective management of RBD patients.
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