Evidence map›Paper›PMID 41938008›Full record

ArticleInternational journal of nursing sciences2026

Impact of role conflict and job stress on turnover intention among Korean physician assistant nurses: A cross-sectional study.

Jin-Won Lee, Eun-Hi Choi, Ji-Sun Back

Abstract read
In one paragraph

Article in International journal of nursing sciences, 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

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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Jin-Won LeeDepartment of Nursing, Daejeon Eulji Medical Center, Daejeon, the Republic of Korea.
Eun-Hi ChoiDepartment of Nursing, Eulji University, Gyeonggi-do, the Republic of Korea.
Ji-Sun BackDepartment of Nursing, Dongnam Health University, Gyeonggi-do, the Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study aimed to investigate the relationships among role conflict, job stress, and turnover intention among physician assistant (PA) nurses in the Republic of Korea and to identify key influencing factors of turnover intention. Methods: A cross-sectional descriptive study was conducted with 120 PA nurses recruited through a professional PA network in Gyeonggi Province and Daejeon Metropolitan City between June 1 and September 30, 2023. Validated instruments were used to measure role conflict, job stress, and turnover intention. Pearson correlation analysis was used to examine the associations between these variables, and multiple regression analysis was performed to identify influencing factors while controlling for demographic, organizational, and psychological covariates. Results: PA nurses reported relatively high levels of role conflict (3.66 ± 0.60), particularly in the subdomains of role ambiguity and work overload, moderate levels of job stress (2.78 ± 0.21) and higher levels of turnover intention (3.80 ± 0.64). Correlation analysis showed a strong positive association between role conflict and turnover intention ( Conclusions: This study identified key factors influencing turnover intention, including role conflict (primarily driven by role ambiguity and work overload), educational level, and job stress. These findings suggest that establishing clear role definitions, enhancing legal recognition of PA nurses, providing ongoing professional education, and implementing stress management programs are essential strategies for improving PA nurse retention and healthcare workforce stability.

Indexed as

Job stressNursing legislationPhysician assistant nursesRole conflictTurnover intention

Identifiers

PMID41938008
PMCPMC13044359

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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.