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DOI 10.4040/jkan.25172

Медицинская библиотека · Journal of Korean Academy of Nursing · 2026

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

Lee Taewha, Lee JooHyun

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Аннотация

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.

Для цитирования: Lee Taewha, Lee JooHyun. Nurse retention discourse in YouTube comments: a structural topic modeling analysis.. Journal of Korean Academy of Nursing. 2026. DOI: 10.4040/jkan.25172.

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