Evidence map›Paper›PMID 41919302›Full record

ArticleFrontiers in public health2026

Addressing factors associated with nursing workforce instability: the mediating effect of professional identification between perceived responses to capitalization attempts and job burnout in newly recruited nurses.

Fuhai Xia, Gen Li, Liqin Xu, Li Li, Xi Chen, Qiang Li

Abstract read
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.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Fuhai Xia *Department of Operating Room, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Gen Li *Department of Operating Room, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Liqin Xu *Department of Operating Room, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Li LiDepartment of Operating Room, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xi ChenDepartment of Operating Room, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Qiang LiDepartment of Operating Room, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Newly recruited nurses are prone to negative emotions and have a high incidence of job burnout due to insufficient work experience and weak ability to handle clinical emergencies. Different modes of perceived responses to capitalization attempts may affect their job burnout through professional identification, and the specific mechanism of action among the three has not been clarified yet. Objectives: To explore the mediating role of professional identification between perceived responses to capitalization attempts and job burnout among newly recruited nurses, and to provide theoretical basis and practical reference for burnout intervention in this group. Methods: A cross-sectional study was conducted. From May to August 2024, 232 newly recruited nurses ( ≤ 2 years of clinical experience) from two tertiary hospitals in Wuhan were selected via cluster sampling. Data were collected using the Perceived Responses to Capitalization Attempts Scale, Professional Identification Scale, and Chinese version of Maslach Burnout Inventory. Pearson correlation, multiple linear regression, and structural equation modeling with bias-corrected bootstrapping were used for analysis. Results: Job burnout was negatively correlated with active-constructive ( Conclusion: This study reveals, within the Job Demands-Resources and positive psychology frameworks, the mediating role of professional identification in how perceived responses to capitalization attempts affect job burnout in new nurses. The findings offer empirical support for developing targeted strategies to enhance professional identity, reduce burnout, and address factors associated with nursing workforce instability.

Indexed as

Burnout, ProfessionalNursesNursing Staff, HospitalSocial IdentificationAdultChinaCross-Sectional StudiesFemaleHumansMaleSurveys and Questionnairesmediation analysisnursesprofessional burnoutprofessional identitysocial support

Identifiers

PMID41919302
PMCPMC13033650

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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.