Evolution of simulation scholarship: A text mining exploration

被引：0

作者：

Blanchard, Erin E. ^{[1
]}

Oner, Beratiye ^{[2
]}

Allgood, Ashleigh ^{[3
]}

Peterson, Dawn Taylor ^{[4
]}

Zengul, Ferhat ^{[5
]}

Brown, Michelle R. ^{[6
]}

机构：

[1] Univ Alabama Birmingham, Sch Hlth Profess, Heersink Sch Med, Dept Hlth Serv Adm,Dept Anesthesiol & Perioperat M, Birmingham, AL 35294 USA

[2] Lokman Hekim Univ, Fac Hlth Sci, Dept Nursing, Sogutozu St, Ankara, Turkiye

[3] Univ Alabama Birmingham, Sch Hlth Profess, Dept Hlth Serv Adm, SHPB 580AA, Birmingham, AL 35294 USA

[4] Univ Alabama Birmingham, Sch Med, Sch Hlth Profess, Dept Med Educ,Dept Hlth Serv Adm, Birmingham, AL 35294 USA

[5] Univ Alabama Birmingham, Ctr Integrated Syst, Sch Hlth Profess, Heersink Sch Med,Dept Biomed Informat & Data Sci D, SHPB 580F, Birmingham, AL 35294 USA

[6] Univ Alabama Birmingham, Sch Hlth Profess, Dept Hlth Serv Adm, Off Interprofess Simulat, SHPB 580B, Birmingham, AL 35294 USA

来源：

CLINICAL SIMULATION IN NURSING | 2024年 / 96卷

关键词：

Healthcare simulation; Latent semantic; analysis; Natural language; processing; Review article; Text mining; FIDELITY SIMULATION; HEALTH-CARE;

D O I：

10.1016/j.ecns.2024.101620

中图分类号：

R47 [护理学];

学科分类号：

1011 ;

摘要：

Background: Text mining uses advanced machine learning algorithms, natural language processing, and statistical analyses to unveil hidden themes in a body of text. Reviewing the simulation literature though text mining allows researchers to categorize extensive collections of publications and develop salient questions based on mapping the evolution of simulation scholarship. Methods: This review examined manuscripts in five healthcare simulation journals between 2006 and 2022, resulting in 2,382 articles included in the text corpus. Results: The top 20 topics were identified and named, in addition to which topics had the highest number of publications. Finally, publication patterns for each topic were examined, with several hypotheses offered as explanation of the results. Discussion: Practical implications of text mining include tracking publication shifts over time, as well as identifying areas of future research that warrant more in-depth, contextual analyses.

引用

页数：8

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