Journal of Korean Academy of Nursing (대한간호학회지)

Korean Society of Nursing Science (한국간호과학회)
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Images of Nurses Appeared in Media Reports Before and After Outbreak of COVID-19: Text Network Analysis and Topic Modeling

COVID-19 발생 전·후 언론보도에 나타난 간호사 이미지에 대한 텍스트 네트워크 분석 및 토픽 모델링

  • Park, Min Young (Department of Nursing, Jeonbuk National University Hospital) ;
  • Jeong, Seok Hee (College of Nursing.Research Institute of Nursing Science, Jeonbuk National University) ;
  • Kim, Hee Sun (College of Nursing.Research Institute of Nursing Science, Jeonbuk National University) ;
  • Lee, Eun Jee (College of Nursing.Research Institute of Nursing Science, Jeonbuk National University)
  • 박민영 (전북대학교병원 간호부) ;
  • 정석희 (전북대학교 간호대학.간호과학연구소) ;
  • 김희선 (전북대학교 간호대학.간호과학연구소) ;
  • 이은지 (전북대학교 간호대학.간호과학연구소)
  • Received : 2022.01.10
  • Accepted : 2022.05.25
  • Published : 2022.06.30
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Abstract

Purpose: The aims of study were to identify the main keywords, the network structure, and the main topics of press articles related to nurses that have appeared in media reports. Methods: Data were media articles related to the topic "nurse" reported in 16 central media within a one-year period spanning July 1, 2019 to June 30, 2020. Data were collected from the Big Kinds database. A total of 7,800 articles were searched, and 1,038 were used for the final analysis. Text network analysis and topic modeling were performed using NetMiner 4.4. Results: The number of media reports related to nurses increased by 3.86 times after the novel coronavirus (COVID-19) outbreak compared to prior. Pre- and post-COVID-19 network characteristics were density 0.002, 0.001; average degree 4.63, 4.92; and average distance 4.25, 4.01, respectively. Four topics were derived before and after the COVID-19 outbreak, respectively. Pre-COVID-19 example topics are "a nurse who committed suicide because she could not withstand the Taewoom at work" and "a nurse as a perpetrator of a newborn abuse case," while post-COVID-19 examples are "a nurse as a victim of COVID-19," "a nurse working with the support of the people," and "a nurse as a top contributor and a warrior to protect from COVID-19." Conclusion: Topic modeling shows that topics become more positive after the COVID-19 outbreak. Individual nurses and nursing organizations should continuously monitor and conduct further research on nurses' image.

Keywords

References

  1. Kotler P, Clarke RN. Marketing for health care organizations. Englewood Cliffs (NJ): Prentice-Hall Inc.; 1986. p. 1-576.
  2. Seong JA, Yeom EY, Do YS. Image of nurses and nursing professional values perceived by nursing students. Journal of the Korea Contents Association. 2014;14(11):798-809. https://doi.org/10.5392/JKCA.2014.14.11.798
  3. Takase M, Maude P, Manias E. Impact of the perceived public image of nursing on nurses' work behaviour. Journal of Advanced Nursing. 2006;53(3):333-343. https://doi.org/10.1111/j.1365-2648.2006.03729.x
  4. Lim EJ. WHO, Declaring a pandemic on COVID-19. "Can be controlled" [Internet]. Seoul: The Yonhap News; c2020 [cited 2020 May 12]. Available from: http://www.yna.co.kr/view/AKR20200312002153088.
  5. Lee SH. Mental health impacts in health care workers during the COVID-19 pandemic. Journal of Korean Neuropsychiatric Association. 2021;60(1):19-22. https://doi.org/10.4306/jknpa.2021.60.1.19
  6. Yang Y. Analysis of publicness criteria and cases of newspaper language. Korean Language Research. 2011;28:115-140. https://doi.org/10.16876/klrc.2011..28.115
  7. Pedersen PM. Examining equity in newspaper photographs: A content analysis of the print media photographic coverage of interscholastic athletics. International Review for the Sociology of Sport. 2002;37(3-4):303-318. https://doi.org/10.1177/1012690202037004895
  8. Iyengar S, Simon A. News coverage of the Gulf crisis and public opinion: A study of agenda-setting, priming, and framing. Communication Research. 1993;20(3):365-383. https://doi.org/10.1177/009365093020003002
  9. Park SA, Kwon HJ, Kim HJ. The portrayal of nurses and physicians in hospital administration journals. Journal of Korean Clinical Nursing Research. 2010;16(2):33-42. https://doi.org/10.22650/JKCNR.2010.16.2.33
  10. Cho J. A study for research area of library and information science by network text analysis. Journal of the Korean Society for information Management. 2011;28(4):65-83. https://doi.org/10.3743/KOSIM.2011.28.4.065
  11. Lee SS. Network analysis methods. Seoul: Nonhyung; 2012. p. 207-268.
  12. Lee SS. Network analysis methods applications and limitations. Seoul: ChungRam; 2018. p. 142-154.
  13. Ryu S, Park H, Kim YH. Knowledge structure of nursing studies on heart failure patients in South Korea through text network analysis. Korean Journal of Adult Nursing. 2020; 32(4):409-420. https://doi.org/10.7475/kjan.2020.32.4.409
  14. Park CS, Park EJ. Identification of knowledge structure of pain management nursing research applying text network analysis. Journal of Korean Academy of Nursing. 2019; 49(5):538-549. https://doi.org/10.4040/jkan.2019.49.5.538
  15. Seo Y. Identification of knowledge structure of accidental falls nursing research: Text network analysis and topic modelling [dissertation]. Seoul: Chung-Ang University; 2021. p. 1-151.
  16. Park EJ, Ahn DW, Park CS. Text network analysis of newspaper articles on life-sustaining treatments. Journal of Korean Academy of Community Health Nursing. 2018;29(2):244-256. https://doi.org/10.12799/jkachn.2018.29.2.244
  17. Kim JI. Visualization of unstructured personal narratives of perterm birth using text network analysis. Korean Journal of Women Health Nursing. 2020;26(3):205-212. https://doi.org/10.4069/kjwhn.2020.08.08
  18. Choi JS, Kim Y. A study on research trend for nurses' workplace bullying in Korea: Focusing on semantic network analysis and topic modeling. Korean Journal of Occupational Health Nursing. 2019;28(4):221-229. https://doi.org/10.5807/kjohn.2019.28.4.221
  19. Kang J, Kim S, Roh S. A topic modeling analysis for online news article comments on nurses' workplace bullying. Journal of Korean Academy of Nursing. 2019;49(6):736-747. https://doi.org/10.4040/jkan.2019.49.6.736
  20. An J. Analysis of image of nurses on articles in Korean daily newspapers after Corona pandemic. The Journal of the Convergence on Culture Technology. 2021;7(1):66-74. https://doi.org/10.17703/JCCT.2021.7.1.66
  21. Yoon YM, Kim SK, Kim HK, Kim EJ, Jeong Y. Comparison of topics related to nurse on the internet portals and social media before and during the COVID-19 era using topic modeling. Journal of Muscle and Joint Health. 2020;27(3):255-267. https://doi.org/10.5953/JMJH.2020.27.3.255
  22. Yun EK, Kim JO, Byun HM, Lee GG. Topic modeling and keyword network analysis of news articles related to nurses before and after "the thanks to you challenge" during the COVID-19 pandemic. Journal of Korean Academy of Nursing. 2021;51(4):442-453. https://doi.org/10.4040/jkan.20287
  23. Hur MS. Reporting frame in articles on female professionals. Media, Gender & Culture. 2007;7:5-45.
  24. Oh MY. U.S. news coverage and image of Korea before and after 2002 worldcup. Korean Journal of Policy Analysis and Evaluation. 2006;16(4):325-352. https://doi.org/10.23036/kapae.2006.16.4.012
  25. World Health Organization (WHO). Archived: WHO timeline - COVID-19 [Internet]. Geneva: WHO; c2020 [cited 2020 Apr 27]. Available from: https://www.who.int/news/item/27-04-2020-who-timeline---covid-19.
  26. Cyram Inc. CYRAM NetMiner 4.4 program. Seongnam: Cyram Inc.; 2021.
  27. Robertson SE. The probability ranking principle in IR. Journal of Documentation. 1977;33(4):294-304. https://doi.org/10.1108/eb026647
  28. Boudin FA. A comparison of centrality measures for graphbased keyphrase extraction [Internet]. Nagoya: International Joint Conference on Natural Language Processing; c2013 [cited 2020 Apr 27]. Available from: https://hal.archives-ouvertes.fr/hal-00850187/document.
  29. Hwang SI, Hwang DR. A study on the research trends in arts management in Korea using topic modeling and semantic network analysis. Journal of Arts Management and Policy. 2018;47:5-29. https://doi.org/10.52564/JAMP.2018.47.5
  30. Griffiths TL, Steyvers M. Finding scientific topics. Proceedings of the National Academy of Sciences of the United States of America. 2004;101(Suppl 1):5228-5235. https://doi.org/10.1073/pnas.0307752101
  31. Panichella A, Dit B, Oliveto R, Di Penta M, Poshynanyk D, De Lucia A. How to effectively use topic models for software engineering tasks? An approach based on genetic algorithms [Internet]. Piscataway: IEEE; c2013 [cited 2020 May 1]. Available from: https://doi.org/10.1109/ICSE.2013.6606598
  32. Rousseeuw PJ. Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics. 1987;20:53-65. https://doi.org/10.1016/0377-0427(87)90125-7
  33. Lee SS. A study on the application of topic modeling for the book report text. Journal of Korean Library and Information Science Society. 2016;47(4):1-18. https://doi.org/10.16981/kliss.47.4.201612.1
  34. Friedkin NE. The development of structure in random networks: An analysis of the effects of increasing network density on five measures of structure. Social Networks. 1981; 3(1):41-52. https://doi.org/10.1016/0378-8733(81)90004-6
  35. Martin MK, Pfeffer J, Carley KM. Network text analysis of conceptual overlap in interviews, newspaper articles and keywords. Social Network Analysis and Mining. 2013;3(4): 1165-1177. https://doi.org/10.1007/s13278-013-0129-5
  36. Scott J. Social network analysis: A handbook. 1st Engl. Ed. Kim HD, Kim GJ, translator. Seoul: Communication Books; c2012. p. 297-308.
  37. Park CS, Chung CW. Text network analysis: Detecting shared meaning through socio-cognitive networks of policy stakeholders. Journal of Governmental Studies. 2013;19(2):73-108.
  38. Na MS, Kang JH. A frame analysis of nurse-related articles from Korean daily newspapers. Journal of Korean Academic Society of Nursing Education. 2018;24(4):453-462. https://doi.org/10.5977/jkasne.2018.24.4.453
  39. Park S, Song J, Song H, Cho E, Choi G, Choi E. A concept analysis of taewom in Korean new nurses. Health & Nursing. 2018;30(2):55-63. https://doi.org/10.29402/HN30.2.6
  40. Choi HK. Enforcement of the workplace harassment prevention act [Internet]. Seoul: The Kukminilbo; c2019 [cited 2019 Jul 16]. Available from: http://news.kmib.co.kr/article/view.asp?arcid=0013502071&code=61211311&cp=kd.
  41. American Nurses Association (ANA). Nurse suicide prevention/resilience [Internet]. Silver Spring (MD): ANA Enterprise; 2021 [cited 2021 Jul 29]. Available from: http://www.nursingworld.org/practice-policy/nurse-suicide-prevention.
  42. Kim HS, Bae HJ, Kang KH. How should we approach nurse suicide in Korea: With the aspect of prevention-intervention-postvention management. Journal of Korean Academy of Nursing. 2021;51(4):408-413. https://doi.org/10.4040/jkan.21171
  43. Davidson JE, Accardi R, Sanchez C, Zisook S, Hoffman LA. Sustainability and outcomes of a suicide prevention program for nurses. Worldviews on Evidence-Based Nursing. 2020;17(1):24-31. https://doi.org/10.1111/wvn.12418 Erratum in: Worldviews on Evidence-Based Nursing. 2020;17(2):179.
  44. Korean Law Information Center. Child welfare act [Internet]. Sejong: Korea Ministry of Government Legislation; 2020 [cited 2020 Nov 29]. Available from: https://www.law.go.kr/법령/아동복지법.
  45. Lee S, Oh H. Research issues and role of experience in expertise development. Asian Journal of Education. 2016;17(3): 461-489. https://doi.org/10.15753/aje.2016.09.17.3.461
  46. Han JY. The period of sanctions for re-issuance of medical personnel's license by lending a license, 2 years -> 3 years enhance [Internet]. Seoul: The DailyMedipharm; c2019 [cited 2019 Aug 4]. Available from: http://www.dailymedipharm.com/news/articleView.html?idxno=47163.
  47. Jang GS, Lee MH, Lee TH, Kim JS, Kang KH, Kim MY, et al. Nursing management. 5th ed. Seoul: Hyunmoonsa; 2020. p. 607-780.
  48. Lee B. Experience of COVID-19 patients care in infectious diseases specialized hospital in Daegu. Korean Journal of Military Nursing Research. 2020;38(2):74-79. https://doi.org/10.31148/kjmnr.2020.38.2.74
  49. Seo H. Analysis of nurses' image as portrayed in Korean online newspapers in association with the MERS outbreak [master's thesis]. Seoul: Chung-Ang University; 2017. p. 1-88.
  50. Hallam J. From angels to handmaidens: Changing constructions of nursing's public image in post-war Britain. Nursing Inquiry. 1998;5(1):32-42. https://doi.org/10.1046/j.1440-1800.1998.510032.x
  51. Hall LM, Angus J, Peter E, O'Brien-Pallas L, Wynn F, Donner G. Media portrayal of nurses' perspectives and concerns in the SARS crisis in Toronto. Journal of Nursing Scholarship. 2003;35(3):211-216. https://doi.org/10.1111/j.1547-5069.2003.00211.x
  52. Lam KK, Hung SY. Perceptions of emergency nurses during the human swine influenza outbreak: A qualitative study. International Emergency Nursing. 2013;21(4):240-246. https://doi.org/10.1016/j.ienj.2012.08.008
  53. Kim J, Lee TW. The influence of nursing practice environment, compassion fatigue and compassion satisfaction on burnout among clinical nurses. Journal of Korean Clinical Nursing Research. 2016;22(2):109-117. https://doi.org/10.22650/JKCNR.2016.22.2.109