The nurse COVID and historical epidemics literature repository: Development, description, and summary

Background: During COVID-19, a Kaggle challenge was issued to data scientists to leverage text mining to provide high-level summaries of full-text articles in the COVID-19 Open Research Dataset (CORD-19) data set, a data set containing articles around COVID-19 and other epidemics. A question was asked: What if nursing had something similar? Purpose: Describe the development and function of the Nursing COVID and Historical Epidemic Literature and describe high-level summaries of abstracts within the repository. Method: Nurse-specific literature was abstracted from two data sets: CORD-19 and LitCOVID. LitCOVID is a data set containing the most up-to-date literature around COVID-19. Multiple text mining algorithms were utilized to provide summaries of the articles. Discussion: As of July 2020, the repository contains 760 articles. Summaries indicate the importance of psychological support for nurses and of high-impact rapid education. Conclusion: To our knowledge, this repository is the only repository specific for nursing that utilizes text mining to provide summaries. Cite this article: Loresto, F.L., Nunez, L., Tarasenko, L., Pierre, M.S., Oja, K., Mueller, M., Switzer, B., Marroquin, K., & Kleiner, C. (2021, May/June). The nurse COVID and historical epidemics literature repository: Development, description, and summary. Nurs Outlook, 69(3), 257-264. https://doi.org/10.1016/j. outlook.2020.12.017.

Automated summary

This study describes the development and function of the Nursing COVID and Historical Epidemic Literature repository, which utilizes text mining algorithms to extract nurse-specific literature from CORD-19 and LitCOVID datasets, providing high-level summaries. The repository contains 760 articles as of July 2020, with summaries indicating the importance of psychological support for nurses and high-impact rapid education.