Evidence map›Paper›PMID 42630364›Full record

ArticleFrontiers in public health2026

Prevalence of poor sleep quality and its associated factors in nurses: a multicenter cross-sectional study.

Min Li, Xiao-Feng Zheng, Xiu-Chun Yin, Qian-Qian Mou

Abstract readMulticenter Study
In one paragraph

Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Min Li *Department of General Surgery, Division of Vascular Surgery, West China Hospital, Sichuan University, Chengdu, China.
Xiao-Feng Zheng *Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
Xiu-Chun YinDepartment of General Surgery, Division of Vascular Surgery, West China Hospital, Sichuan University, Chengdu, China.
Qian-Qian MouClinical Trial Center, West China School of Nursing, West China Hospital, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Although poor sleep quality has been significantly associated with burnout, medical errors, and patient safety, its prevalence and associated factors among nurses remain underexplored. This study aimed to determine the prevalence of poor sleep quality and identify its associated factors in nurses. Methods: In this multicenter cross-sectional study, convenience sampling was employed to enroll nurses from eight tertiary hospitals across Sichuan Province, China, between October and December 2025. Participants completed a demographic questionnaire, the Pittsburgh Sleep Quality Index, the NASA Task Load Index, and the Self-Regulatory Fatigue Scale. Univariate analysis and binary logistic regression were used to examine the correlates of poor sleep quality. Results: A total of 1,289 nurses were included, with 813 (63.1%) reporting poor sleep quality. Age (31-45 years: OR = 1.628, 95% CI: 1.200-2.209, Conclusion: Poor sleep quality was highly prevalent among nurses and was significantly associated with age, work unit, work experience, night shift, workload, and self-regulatory fatigue. These findings highlight the importance of prioritizing high-risk populations, particularly older nurses and those working in high-acuity settings, with lengthy service, and on rotating night schedules. Moreover, comprehensive strategies addressing workplace stressors and individual resilience may help reduce sleep problems.

Indexed as

NursesNursing Staff, HospitalSleep QualitySleep Wake DisordersAdultChinaCross-Sectional StudiesFatigueFemaleHumansMaleMiddle AgedPrevalenceRisk FactorsSurveys and QuestionnairesWorkloadnursesprevalenceself-regulatory fatiguesleep qualityworkload

Identifiers

PMID42630364
PMCPMC13493609

What OpenQuestion holds

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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.