Analysis of issues related to nursing law: Examination of news articles using topic modeling

PLoS One. 2024 Aug 22;19(8):e0308065. doi: 10.1371/journal.pone.0308065. eCollection 2024.

Abstract

Purpose: The objective of this study was to analyze proposed Korean nursing legislation as depicted in newspaper articles, to highlight issues related to the legislative process for this potential law, and to better understand social awareness regarding this matter.

Methods: The study focused on articles from 11 leading newspapers in Korea, published between February 2020 and August 2023, that pertained to nursing legislation. The articles were retrieved from the BigKinds database. Following text preprocessing, analytical methods including term frequency-inverse document frequency were employed, along with latent Dirichlet allocation (LDA), for word and topic modeling analysis. Additionally, LDA was applied across time periods to examine temporal changes in topics.

Results: Following preprocessing, a total of 7,967 words were extracted from the 991 articles selected for analysis. The primary themes identified in newspaper articles concerning the nursing legislation were organized into three main topics: 1) the necessity and impact of enactment of the nursing law, 2) the political context surrounding enactment of the law, and 3) the conflicts between and actions of healthcare organizations related to enactment of the law.

Conclusions: The findings confirmed that media coverage regarding the proposed nursing legislation primarily concentrated on the political and social conflicts associated with the law's passage, rather than its necessity and substance. More compelling evidence must be presented concerning the influence of the nursing workforce and the work environment of nurses on patient safety and health outcomes. Additionally, strategies should be devised to improve public comprehension of the nursing law's provisions.

MeSH terms

  • Humans
  • Legislation, Nursing
  • Mass Media
  • Newspapers as Topic*
  • Republic of Korea

Grants and funding

This work was supported by the Korea Environmental Industry & Technology Institute (KEITI), with a grant funded by the Korean government, Ministry of Environment (The development of IoT-based technology for collecting and managing big data on environmental hazards and health effects), under Grant RE202101551.