Construction and evaluation of a predictive model for high mental workload risk among clinical nurses: a cross-sectional study

A validated nomogram was developed to predict the risk of high mental workload among clinical nurses. The model exhibited favorable discrimination, sound calibration, and consistent internal reliability, offering an effective means for identification and focused intervention.

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Publication Details

Journal
Frontiers in Public Health
Published
2026-02-09
DOI
https://doi.org/10.3389/fpubh.2026.1724229
Primary Topic
Nursing education and management
Type
article
Field-Weighted Citation Impact
0.00
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article

Construction and evaluation of a predictive model for high mental workload risk among clinical nurses: a cross-sectional study

Zhongqing Yuan, Li Zeng, Wanqing Xie, Fengxue Yang et al.
Frontiers in Public Health
Nursing education and management
article

Construction and evaluation of a predictive model for high mental workload risk among clinical nurses: a cross-sectional study

Zhongqing Yuan, Li Zeng, Wanqing Xie, Fengxue Yang, Jialin Wang
article en

Abstract

A validated nomogram was developed to predict the risk of high mental workload among clinical nurses. The model exhibited favorable discrimination, sound calibration, and consistent internal reliability, offering an effective means for identification and focused intervention.

Frontiers in Public HealthVol. 14
National Clinical Research (US), Sichuan Provincial Hospital of Traditional Chinese Medicine (CN), Science and Technology Department of Sichuan Province (CN), Chengdu University of Traditional Chinese Medicine (CN)
Reduced inequalities
Openalex Percentile: Top 62%
Nursing education and management
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Construction and evaluation of a predictive model for high mental workload risk among clinical nurses: a cross-sectional study — Zhongqing Yuan, Li Zeng, et al. · Frontiers in Public Health (2026) | TGRS Research Map | TGRS