Evidence map›Paper›PMID 42037554›Full record

ArticleJournal of nursing management2026

Network Analysis of Sleep Quality and Psychiatric Symptoms Among ICU Nursing Staff.

Yating Li, Yan Zhang, Wenjin Chen, Wei He, Jie Jian, Jingyi Xu, Yang Sun, Xiaoguo Ma, Ziyi Ding, Di Zhao and 1 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of nursing management, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Yating LiHebei Key Laboratory of Early Life Health Promotion (SZX202419), Hebei Medical University, Shijiazhuang, China, hebmu.edu.cn.
Yan ZhangHandan Central Hospital, Handan, China, hdzxyy.com.
Wenjin ChenDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Fengtai, Beijing, China, ccmu.edu.cn.
Wei HeDepartment of Critical Care Medicine, Beijing Tongren Hospital, Capital Medical University, Fengtai, Beijing, China, ccmu.edu.cn.
Jie JianHebei Key Laboratory of Early Life Health Promotion (SZX202419), Hebei Medical University, Shijiazhuang, China, hebmu.edu.cn.
Jingyi XuHebei Key Laboratory of Early Life Health Promotion (SZX202419), Hebei Medical University, Shijiazhuang, China, hebmu.edu.cn.
Yang SunHebei Key Laboratory of Early Life Health Promotion (SZX202419), Hebei Medical University, Shijiazhuang, China, hebmu.edu.cn.
Xiaoguo MaHebei Key Laboratory of Early Life Health Promotion (SZX202419), Hebei Medical University, Shijiazhuang, China, hebmu.edu.cn.
Ziyi DingHebei Key Laboratory of Early Life Health Promotion (SZX202419), Hebei Medical University, Shijiazhuang, China, hebmu.edu.cn.
Di ZhaoHebei Key Laboratory of Early Life Health Promotion (SZX202419), Hebei Medical University, Shijiazhuang, China, hebmu.edu.cn.ORCID https://orcid.org/0000-0001-6671-9307
Haishui ShiHebei Key Laboratory of Early Life Health Promotion (SZX202419), Hebei Medical University, Shijiazhuang, China, hebmu.edu.cn.ORCID https://orcid.org/0000-0002-7478-4405

Funding

Hebei Medical University USIP2024084Hebei Provincial Social Science Development Research Project HBSKFZ25QN120Medical Science Research Project of Hebei 20250178Ministry of Education of the People's Republic of China NV20250010National Natural Science Foundation of China 82171536Project from Handan Municipal Bureau of Science and Technology 23422083010ZC
6 · The paper itself

Abstract

backgroundIntensive care unit (ICU) nurses are at high risk for sleep problems and psychological symptoms. This study aimed to construct a network model to explore the interrelationships between sleep quality and psychiatric symptoms among ICU nurses and to identify central and bridge symptoms for precise intervention.

methodsA multicenter cross-sectional study was conducted from January to March 2025 among registered nurses working in ICUs. Psychiatric symptoms were assessed using the Symptom Checklist-90 (SCL-90), and sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI). A Gaussian Graphical Model was estimated using the EBICglasso algorithm. Centrality indices (strength, closeness, betweenness, and expected influence) and bridge centrality were calculated to identify key symptoms. The stability of the network was assessed using nonparametric and case-dropping bootstrap analyses.

resultsA total of 5560 nurses were included in the analysis. The network model revealed a well-connected structure. Centrality analysis indicated that "subjective sleep quality", "anxiety", and "sleep and eating problems" were the most central symptoms in the entire network. Bridge centrality analysis identified "sleep and eating problems" as the most critical bridge symptoms, forming the strongest connections between the sleep and psychiatric symptom communities. The network demonstrated excellent stability, with a correlation stability coefficient of 0.75 for both strength and bridge strength.

conclusionThe findings highlight the pivotal roles of subjective sleep quality, sleep and eating problems, and anxiety as potential targets for precise interventions. Focusing on these symptoms may effectively disrupt the vicious cycle between poor sleep and psychological distress, thereby improving overall well-being.

Indexed as

Sleep QualityAdultCross-Sectional StudiesFemaleHumansIntensive Care UnitsMaleMiddle AgedPsychometricsSleep Wake DisordersSurveys and Questionnairesintensive care unitnetwork analysisnursespsychiatric symptomssleep quality

Identifiers

PMID42037554
PMCPMC13112185

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.