Evidence map›Paper›PMID 42533478›Full record

ArticleJournal of nursing management2026

Associations Between Fatigue and Sleep Among Night-Shift Nurses: Mediating Role of Depressive Symptoms and Social Support.

Yingying Gu, Qiqi Huang, Shuhong Ni, Caijun Dai, Wenwei Ren

Abstract read
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.

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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yingying GuDepartment of Psychiatry, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China, wzhospital.cn.ORCID https://orcid.org/0009-0008-3835-9592
Qiqi HuangPediatric Nursing Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China, wzhospital.cn.ORCID https://orcid.org/0000-0002-6029-8481
Shuhong NiDepartment of Nursing, Jinhua Municipal Central Hospital, Jinhua, Zhejiang, China, jhzxyy.cn.ORCID https://orcid.org/0009-0004-2242-1401
Caijun DaiDepartment of Pulmonary and Critical Care Medicine, Jinhua Municipal Central Hospital, Jinhua, Zhejiang, China, jhzxyy.cn.ORCID https://orcid.org/0009-0000-8466-1823
Wenwei RenDepartment of Psychiatry, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China, wzhospital.cn.ORCID https://orcid.org/0000-0001-6054-4323

Funding

Wenzhou Municipal Science and Technology Bureau Y20220841
6 · The paper itself

Abstract

backgroundThis study examined the association between fatigue and sleep disturbance among night-shift nurses during the COVID-19 pandemic and the mediating roles of depressive symptoms and social support.

methodsA cross-sectional survey was conducted involving 1667 night-shift nurses from multiple hospitals. The Pittsburgh Sleep Quality Index (PSQI), Fatigue Scale-14, Hospital Anxiety and Depression Scale, and Social Support Rating Scale were used for assessment. Correlation analysis and mediation effect analysis were performed using SPSS 26.0 and PROCESS macro.

resultsPoor sleep (PSQI ≥ 6) was reported by 70.7% of nurses. Increased workload (89.7%) and fear of infection (58.1%) were significantly associated with worse sleep (both p < 0.05). Fatigue correlated positively with depression (r = 0.607, p < 0.001) and sleep disturbance (r = 0.550, p < 0.001) and negatively with social support (r = -0.242, p < 0.001). Mediation analysis identified three pathways: depressive symptoms alone (30.25% of the total effect), social support alone (0.80%), and the sequential depression ⟶ social support path (2.23%).

conclusionsAmong night-shift nurses, fatigue is directly and indirectly associated with poorer sleep quality via three mediating pathways: depressive symptoms alone, social support alone, and the sequential effect of depressive symptoms on social support. Interventions should address these pathways to improve sleep in night-shift nurses under high-load public health emergency contexts. IMPLICATIONS FOR NURSING MANAGEMENT: For night-shift nurses facing excess workload during public health emergencies, managers could adopt a tiered strategy: (1) optimize shift schedules to reduce fatigue and (2) strengthen peer and family support systems. Regular monitoring of sleep and fatigue indicators is recommended to evaluate intervention effectiveness under such high-stress contexts.

Indexed as

COVID-19DepressionFatigueNursesShift Work ScheduleSleep Wake DisordersSocial SupportWork Schedule ToleranceAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedSleep QualitySurveys and Questionnairesdepressive symptomsfatiguenight-shift nursessleepsocial support

Identifiers

PMID42533478
PMCPMC13424447

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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.