Cargando…

A text mining and network analysis of topics and trends in major nursing research journals

AIM: This study is set to determine the main topics of the nursing field and to show the changing perspectives over time by analysing the abstracts of several major nursing research journals using text mining methodology. DESIGN: Text mining and network analysis. METHODS: Text analysis combines auto...

Descripción completa

Detalles Bibliográficos
Autores principales: Oner, Beratiye, Hakli, Orhan, Zengul, Ferhat D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10697125/
http://dx.doi.org/10.1002/nop2.2050
_version_ 1785154710679846912
author Oner, Beratiye
Hakli, Orhan
Zengul, Ferhat D.
author_facet Oner, Beratiye
Hakli, Orhan
Zengul, Ferhat D.
author_sort Oner, Beratiye
collection PubMed
description AIM: This study is set to determine the main topics of the nursing field and to show the changing perspectives over time by analysing the abstracts of several major nursing research journals using text mining methodology. DESIGN: Text mining and network analysis. METHODS: Text analysis combines automatic and manual operations to identify patterns in unstructured data. Detailed searches covering 1998–2021 were conducted in PubMed archives to collect articles from six nursing journals: Journal of Advanced Nursing, International Journal of Nursing Studies, Western Journal of Nursing Research, Nursing Research, Journal of Nursing Scholarship and Research in Nursing and Health. This study uses a four‐phase text mining and network approach, gathering text data and cleaning, preprocessing, text analysis and advanced analyses. Analyses and data visualization were performed using Endnote, JMP, Microsoft Excel, Tableau and VOSviewer versions. From six journals, 17,581 references in PubMed were combined into one EndNote file. Due to missing abstract information, 2496 references were excluded from the study. The remaining references (n = 15,085) were used for the text mining analyses. RESULTS: Eighteen subjects were determined into two main groups; research method topics and nursing research topics. The most striking topics are qualitative research, concept analysis, advanced practice in the downtrend, and literature search, statistical analysis, randomized control trials, quantitative research, nurse practice environment, risk assessment and nursing science. According to the network analysis results, nursing satisfaction and burnout and nursing practice environment are highly correlated and represent 10% of the total corpus. This study contributes in various ways to the field of nursing research enhanced by text mining. The study findings shed light on researchers becoming more aware of the latest research status, sub‐fields and trends over the years, identifying gaps and planning future research agendas. No patient or public contribution.
format Online
Article
Text
id pubmed-10697125
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-106971252023-12-06 A text mining and network analysis of topics and trends in major nursing research journals Oner, Beratiye Hakli, Orhan Zengul, Ferhat D. Nurs Open Research Methodology: Discussion Paper ‐ Methodology AIM: This study is set to determine the main topics of the nursing field and to show the changing perspectives over time by analysing the abstracts of several major nursing research journals using text mining methodology. DESIGN: Text mining and network analysis. METHODS: Text analysis combines automatic and manual operations to identify patterns in unstructured data. Detailed searches covering 1998–2021 were conducted in PubMed archives to collect articles from six nursing journals: Journal of Advanced Nursing, International Journal of Nursing Studies, Western Journal of Nursing Research, Nursing Research, Journal of Nursing Scholarship and Research in Nursing and Health. This study uses a four‐phase text mining and network approach, gathering text data and cleaning, preprocessing, text analysis and advanced analyses. Analyses and data visualization were performed using Endnote, JMP, Microsoft Excel, Tableau and VOSviewer versions. From six journals, 17,581 references in PubMed were combined into one EndNote file. Due to missing abstract information, 2496 references were excluded from the study. The remaining references (n = 15,085) were used for the text mining analyses. RESULTS: Eighteen subjects were determined into two main groups; research method topics and nursing research topics. The most striking topics are qualitative research, concept analysis, advanced practice in the downtrend, and literature search, statistical analysis, randomized control trials, quantitative research, nurse practice environment, risk assessment and nursing science. According to the network analysis results, nursing satisfaction and burnout and nursing practice environment are highly correlated and represent 10% of the total corpus. This study contributes in various ways to the field of nursing research enhanced by text mining. The study findings shed light on researchers becoming more aware of the latest research status, sub‐fields and trends over the years, identifying gaps and planning future research agendas. No patient or public contribution. John Wiley and Sons Inc. 2023-11-30 /pmc/articles/PMC10697125/ http://dx.doi.org/10.1002/nop2.2050 Text en © 2023 The Authors. Nursing Open published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Research Methodology: Discussion Paper ‐ Methodology
Oner, Beratiye
Hakli, Orhan
Zengul, Ferhat D.
A text mining and network analysis of topics and trends in major nursing research journals
title A text mining and network analysis of topics and trends in major nursing research journals
title_full A text mining and network analysis of topics and trends in major nursing research journals
title_fullStr A text mining and network analysis of topics and trends in major nursing research journals
title_full_unstemmed A text mining and network analysis of topics and trends in major nursing research journals
title_short A text mining and network analysis of topics and trends in major nursing research journals
title_sort text mining and network analysis of topics and trends in major nursing research journals
topic Research Methodology: Discussion Paper ‐ Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10697125/
http://dx.doi.org/10.1002/nop2.2050
work_keys_str_mv AT onerberatiye atextminingandnetworkanalysisoftopicsandtrendsinmajornursingresearchjournals
AT hakliorhan atextminingandnetworkanalysisoftopicsandtrendsinmajornursingresearchjournals
AT zengulferhatd atextminingandnetworkanalysisoftopicsandtrendsinmajornursingresearchjournals
AT onerberatiye textminingandnetworkanalysisoftopicsandtrendsinmajornursingresearchjournals
AT hakliorhan textminingandnetworkanalysisoftopicsandtrendsinmajornursingresearchjournals
AT zengulferhatd textminingandnetworkanalysisoftopicsandtrendsinmajornursingresearchjournals