Clusters of Sleep Disturbance and Associated Factors in People With Systemic Lupus Erythematosus: A Latent Profile Analysis.

睡眠障碍 扰动(地质) 医学 潜在类模型 重症监护医学 精神科 失眠症 生物 古生物学 统计 数学
作者
Ying-Dan Chen,Qian Liu,Qing Wu,Jinjin Yuan,Cynthia Fritschi,Jingqi Bai,Pei Chen,Yueying Wang,Fan Liu,Jiahui Zhang,Jinle Wang,Hongsheng Tan,Bingqian Zhu
出处
期刊:PubMed
标识
DOI:10.1111/jocn.70026
摘要

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. To examine clusters of sleep disturbance and associated factors in people with SLE. Cross-sectional design. 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. 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. Sleep disturbance in patients with SLE showed three distinct clusters, with each cluster having slightly different predisposing factors. 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. Checklist for reporting of survey studies. No patient or public contribution.
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