Evidence map›Paper›PMID 40098795›Full record

ArticleFrontiers in public health2025

Construction and validation of a presenteeism prediction model for ICU nurses in China.

Jijun Wu, Yuxin Li, Xiaoli Liu, Yuting Fan, Ping Dai, Baixia Chen, Zhenfan Liu, Xian Rong, Xiaoli Zhong

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Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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7citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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7 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Jijun Wu *Department of Nursing, Deyang People's Hospital, Deyang, China.
Yuxin Li *Department of Nursing, Deyang People's Hospital, Deyang, China.
Xiaoli LiuDepartment of Nursing, Deyang People's Hospital, Deyang, China.
Yuting FanDepartment of Nursing, Deyang People's Hospital, Deyang, China.
Ping DaiDepartment of Cardiology, Deyang People's Hospital, Deyang, China.
Baixia ChenDepartment of Cardiology, Deyang People's Hospital, Deyang, China.
Zhenfan LiuDepartment of Nursing, Deyang People's Hospital, Deyang, China.
Xian RongSichuan Nursing Vocational College, Chengdu, China.
Xiaoli ZhongDepartment of Nursing, Deyang People's Hospital, Deyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Presenteeism, also known as impaired health productivity, refers to the condition of impaired productivity of an individual due to physiological or mental health problems. ICU, as a place of intensive care for patients with acute and critical illnesses, nurses have long faced the nature of work with high loads, high pressures, and high intensities, which makes them a high prevalence group of presenteeism. Presenteeism not only affects the physical and mental health and work wellbeing of nurses but also reduces the quality of nursing services and affects the life safety of patients, such as increasing the risk of falls during hospitalization, increasing the risk of medication errors, and prolonging the hospitalization time of patients. Therefore, early identification and targeted interventions are crucial to reduce presenteeism among ICU nurses. Objective: This study aimed to construct and validate a predictive model for presenteeism among ICU nurses. Design: A cross-sectional study. Methods: 1,225 ICU nurses were convened from January to April 2023 from 25 tertiary and secondary hospitals in Sichuan Province, China. ICU nurses were randomly divided into a development set ( Results: The presenteeism rate of ICU nurses in the development set was 76.8%. Multifactorial logistic regression analysis showed that independent factors affecting ICU nurses' presenteeism included income per month, physical health status, job satisfaction, perceived work stress, perceived social support, transformational leadership, and occupational coping self-efficacy. In the development set and validation set, the area under the ROC curve was 0.821 and 0.786, respectively; the sensitivity and specificity were 80.6, 69.8 and 80.9%, 65.1%, respectively; the Hosmer-Lemeshow goodness-of-fit was Conclusion: The predictive model of presenteeism risk for ICU nurses constructed in this study has good predictive ability. The model can effectively identify ICU nurses with high presenteeism and provide a reference basis for developing targeted interventions to reduce presenteeism among ICU nurses.

Indexed as

Critical Care NursingIntensive Care UnitsNursing Staff, HospitalPresenteeismAdultChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedSurveys and Questionnairescolumn-line diagramICUnursespresenteeismrisk factorsrisk prediction model

Identifiers

PMID40098795
PMCPMC11911374

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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.