Evidence map›Paper›PMID 41882693›Full record

ArticleBMC nursing2026

Work fatigue risk and associated factors among Chinese first-line registered nurses using latent profile analysis: a multicenter cross-sectional study.

Rong Pi, Yunfang Liu, Rong Yan, Yan OuYang, Zong De, Yali Wan, Yi Chen, Fang Liu, Zihan He, Wenjing Li and 3 more

Abstract read
In one paragraph

Article in BMC nursing, 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

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

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

13 authors.

Rong PiDepartment of Nursing, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Yunfang LiuDepartment of Thoracic Surgery, Union Hospitals, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Rong YanDepartment of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Yan OuYangDepartment of Nursing, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Zong DeDepartment of Cardiology, Lhasa People's Hospital, Xizang, China.
Yali WanDepartment of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Yi ChenDepartment of Clinical Nutrition, Wuhan Hospital of Traditional Chinese and Western Medicine (Wuhan No.1 Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Fang LiuDepartment of Nursing, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Zihan HeDepartment of Nursing, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Wenjing LiDepartment of Nursing, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Zixuan HouDepartment of Nursing, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Yan WangDepartment of Nursing, Jingshan Union Hospital of Huazhong University of Science and Technology, Jingshan, Hubei, China.
Suyun LiDepartment of Nursing, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China. lisuyun0503@163.com.

Funding

Humanities and Social Sciences by the Ministry of Education 21YJA630049
6 · The paper itself

Abstract

aimTo investigate subgroups of work fatigue risk in the Chinese first-line registered nurses and identify the associated factors associated with these profiles.

backgroundWork fatigue is a prevalent issue among healthcare professionals, but few studies have employed person-centered approaches to investigate the specific patterns of work fatigue risk in a large sample of Chinese first-line registered nurses.

methodsA convenient cluster sampling method was employed in six general hospitals in Hubei Province, China. Data related to the demographic characteristics, work-related characteristics, work fatigue risk, health promotion lifestyle, resilience and social support were collected. Latent profile analysis was utilized to categorize work fatigue risk subgroups among clinical nurses. Multiple logistic regression analyses were used to investigate associated factors with profile membership.

resultsA total of 1663 valid questionnaires were collected. Latent profile analysis suggested three profiles of work fatigue risk, which were labeled: low work fatigue risk (24.9%), moderate work fatigue risk (51.5%) and moderate high work fatigue risk (23.6%). The results of multiple logistic regression analyses indicated that age, gender, professional title, self-perceived health, number of time off <11 h between shifts per month, social support and resilience were the associated factors for the potential profiles.

conclusionsOur findings explore latent profiles of work fatigue risk among frontline registered nurses, identify subgroups susceptible to work fatigue. This research offers new insights into the heterogeneity of fatigue risks and the necessity for tailored interventions. IMPLICATIONS FOR NURSING MANAGEMENT: The study suggest that nurse managers should take responsibility to implement targeted interventions with the aim of reducing work fatigue among nurses. In addition, it is essential to identify distinct work fatigue groups and provide support to those who are most vulnerable.

Indexed as

Associated factorsFirst-line registered nursesLatent profile analysisWork fatigue risk

Identifiers

PMID41882693
PMCPMC13137588

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.