Evidence map›Paper›PMID 41266941›Full record

ArticleInternational nursing review2025

Media Portrayals of Nurse Retention: A Decade of News With Topic Modeling and Network Analysis.

Taewha Lee, JooHyun Lee

Abstract read
In one paragraph

Article in International nursing review, 2025. 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

2 authors.

Taewha LeeMo-Im Kim Nursing Research Institute, Yonsei University, Seoul, Republic of Korea.
JooHyun LeeMo-Im Kim Nursing Research Institute, Yonsei University, Seoul, Republic of Korea.

Funding

National Research Foundation of Korea (NRF) RS-2024-00350329
6 · The paper itself

Abstract

aimThis study aims to explore how nurse retention has been portrayed in South Korean news media, identifying key themes, discourse shifts, and the relations among them in shaping public perceptions and policy discussions.

backgroundNurse retention is essential for healthcare system stability and quality improvement. Media coverage significantly influences public perception and policy formation through issue selection and framing. However, there is a lack of systematic analysis of nurse retention portrayal in the media.

methodsAn exploratory study using text mining, topic modeling, and network analysis examined 447 news articles published between January 2015 and September 2024 and retrieved from BigKinds, a South Korean news big data platform.

resultsFour themes emerged: (1) healthcare system and policy challenges, (2) gendered power dynamics between nurses and physicians, (3) work environment and employment conditions, and (4) hierarchical strain and adverse workplace culture among nurses. Network analysis indicated increased complexity and interconnectedness over time, with Period 1 (2015-2019) focusing on workplace issues and Period 2 (2020-2024) emphasizing policy debates. DISCUSSION: The discourse shift toward policy emphasis integrated nurse retention into system-level discussions, potentially overshadowing the specific organizational and cultural factors that directly influence nurses' decisions to stay.

conclusionsMedia discourse on nurse retention shifted significantly, integrating retention issues into the broader healthcare system and policy debates. While raising public awareness, this approach risks overlooking the distinct concerns of the nursing workforce. IMPLICATIONS FOR NURSING: Awareness of how media frames nurse retention can help nurses recognize their experiences within broader professional discourse. IMPLICATIONS FOR NURSING POLICY: Understanding media framing informs advocacy for balanced reporting and effective policy reforms aimed at enhancing nurse retention and work environments.

Indexed as

Job SatisfactionMass MediaPersonnel TurnoverAdultFemaleHumansMaleMiddle AgedRepublic of KoreaWorkplacedata miningmass medianetwork analysisnursespersonnel retentionunsupervised machine learning

Identifiers

PMID41266941
PMCPMC12634930

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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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 Socratic graph.