Nurse retention discourse in YouTube comments: a structural topic modeling analysis.

Purpose: This study analyzed public discourse on nurse retention through YouTube comments posted between 2018 and 2024 to examine how retention issues are collectively framed in online public spheres, thereby extending individual-level retention research to societal-level discourse analysis. Methods...

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Published in:Journal of Korean Academy of Nursing Vol. 56; no. 2; pp. 206 - 220
Main Authors: Lee, Taewha, Lee, JooHyun
Format: research tables/charts Journal Article
Published: Korean Society of Nursing Science May2026
Online Access:View this record in EBSCOhost
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      dt: May2026
      vid: 56
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      pub: Korean Society of Nursing Science
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        atl: Nurse retention discourse in YouTube comments: a structural topic modeling analysis.
      aug:
        au:
          Lee, Taewha
          Lee, JooHyun
        affil: Mo-Im Kim Nursing Research Institute, College of Nursing, Yonsei University, Seoul, South Korea
      sug:
        subj:
          Nurses Psychosocial Factors
          Personnel Retention
          Social Media Utilization
          Workforce
          Data Mining
          Natural Language Processing
          Human
          Funding Source
          South Korea
          Male
          Female
          Correlational Studies
          Discourse Analysis
          Professional Practice
          Machine Learning
          Professional Identity
          Health Policy
          Scope of Nursing Practice
          Coping
          Work Environment
          Stress, Occupational
          Emigration and Immigration
          Career Mobility
          Social Problems
          Male
          Female
      ab: Purpose: This study analyzed public discourse on nurse retention through YouTube comments posted between 2018 and 2024 to examine how retention issues are collectively framed in online public spheres, thereby extending individual-level retention research to societal-level discourse analysis. Methods: Comments were collected from 226 YouTube videos uploaded between January 2015 and December 2024, identified using search terms that combined "nurse" with retention-related keywords. After duplicates and comments posted outside the study period were removed, 32,399 comments were analyzed using structural topic modeling with year and number of likes as covariates. Topic correlation network analysis with community detection was used to identify discourse coalitions. Results: Fourteen substantive topics and one noninterpretive topic emerged, spanning individual coping strategies, organizational workplace issues, and systemic policy structures. "International nursing migration and career pathways" (12.8%) and "Disputes regarding the scope of practice among professionals" (11.4%) were the most prevalent topics. Temporal analysis revealed discourse shifts consistent with focusing events theory: COVID-19 (coronavirus disease 2019) activated structural critique frames while suppressing career mobility discourse; the 2022 Nursing Law followed an issue-attention cycle pattern; and the 2024 medical school quota expansion embedded retention discourse within broader healthcare policy debates. Network analysis identified two discourse communities, professional identity and structural exploitation, with international migration serving as a bridging frame across both. Conclusion: Public discourse framed nurse retention as a systemic and structural issue rather than as an expression of individual professional rejection. These collective framing patterns complement traditional survey-based research and may inform policy design by identifying which frames achieve public resonance and where discourse fragmentation may challenge policy implementation.
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        research
        tables/charts
        Journal Article
      ougenre: Article
    language: Korean
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