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Updated: Sep 16, 2025

Human Circadian Phenotyping and Diurnal Performance Testing in the Real World
Published on: April 7, 2020
Clusters of Sleep Disturbance and Associated Factors in People With Systemic Lupus Erythematosus: A Latent Profile
Yingdan Chen1,2, Liping Qian2, Qing Wu1
1School of Nursing, Shanghai Jiao Tong University, Shanghai, China.
Background:
Individuals with systemic lupus erythematosus (SLE) often suffer from sleep disturbance, which exhibits heterogeneity. Whether it could be grouped into different clusters remains unknown, posing challenges to the development of personalised interventions to address sleep disturbance.
Aim:
To examine clusters of sleep disturbance and associated factors in people with SLE.
Design:
Cross-sectional design.
Methods:
From November 2023 to January 2024, people diagnosed with SLE were recruited by a convenience sampling approach. Data were collected via an online platform Wenjuanxing. Sleep disturbance was evaluated by the Pittsburgh Sleep Quality Index (PSQI). Other information, such as disease activity, pain, fatigue, depression and anxiety was also collected using validated instruments. Latent profile analysis was performed to reveal the distinct clusters of sleep disturbance. Multiple logistic regression analysis was performed to investigate factors associated with the clusters.
Results:
A total of 538 participants were included, with a response rate of 85.1% (538/632). Only those with sleep disturbance (PSQI > 5) were included in the final analyses. Participant mean age was 32.9 (SD = 8.4) years and 402 (92.6%) were females. All had sleep disturbance (PSQI > 5) and their mean PSQI was 8.8 (SD = 2.9). Three distinct clusters were identified: mild sleep disturbance with poor sleep quality, adequate sleep duration and good daytime functioning (50.7%), mild sleep disturbance with poor sleep quality, adequate sleep duration and poor daytime functioning (30.9%) and moderate sleep disturbance with poor sleep quality, inadequate sleep duration and impaired daytime functioning (18.4%). There are both overlaps and unique aspects in terms of factors associated with each cluster of sleep disturbance, including age, body mass index, cardiovascular system damage, musculoskeletal system damage, depression and anxiety.
Conclusions:
Sleep disturbance in patients with SLE showed three distinct clusters, with each cluster having slightly different predisposing factors.
Implications For The Profession:
In clinical practice, nurses are recommended to prioritise assessment and interventions for those at-risk subgroups. They could also use the above information to develop and provide personalised interventions to address the unique needs of each cluster of sleep disturbance.
Reporting Method:
Checklist for reporting of survey studies.
Patient Or Public Contribution:
No patient or public contribution.
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