Bibliometric analysis of core competencies associated nursing management publications
Bibliographic record
Abstract
AIMS: This study aimed to identify high-impact papers on global nursing to determine and analyse the publication of articles on core competencies in nursing-related journals and the research trends in the era of globalization. BACKGROUND: Bibliometrics has been shown to be an effective method for analysing publications. Through bibliometrics, nursing managers and researchers can understand the trends of high-impact international nursing core competencies research, identify mainstream research directions and obtain relevant knowledge and information, thereby facilitating the translation of research outcomes into nursing management practice. EVALUATION: The study adopted bibliometric analysis and the VOSviewer software to explore dynamic publication trends and analyse the current situation of nursing research from a comprehensive development perspective, which was realized by searching for nursing core competencies papers in the Web of Science (WoS) database, calculating citations and determining the trends of the most influential papers. KEY ISSUES: Nursing core competencies research grew rapidly between 1997 and 2022. Countries with the most core competencies publications were the United States, England, Australia and Canada. The Journal of Nursing Management has attracted substantial attention from researchers worldwide. Education, Management and Nurses were the most frequently used keywords in the study. A total of 534 papers were retrieved from the WoS database with the main research fields, including nursing, business economics, public environmental occupational health and health care science services. CONCLUSION: Equipping nursing graduates with core competencies has always been an important goal of global medical and nursing education. This study analysed papers across 35 years, most of which were published in the Journal of Nursing Management. In addition, the study identified some of the main research topics of nursing management, such as the integration of education with nursing management and the cultivation of nurses' core competencies. The study also provides a fresh review of highly cited articles. The results of the study show that high-quality articles play the role of improving both the quality and the quantity of related research. By analysing the trends of the research on core competencies, this study lays a bibliometric foundation for researchers regarding international journals, hot topics and relevant fields. In addition, the highly cited articles reveal new perspectives for the nursing field, providing inspiration for nursing management and education researchers. IMPLICATIONS FOR NURSING MANAGEMENT: This study provides scholars and managers with an overview of the current situation of nursing management research and the development of benchmark journals. The study provides researchers not only with a better understanding of various international journals, allowing them to transition out of traditional thinking in the era of science and technology, but also with innovative thinking by combining research with nursing management. The results of this study invite nursing managers to study relevant topics of core competencies and integrate information technology to education, management and nurses, thereby contributing to nursing management and educational research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.208 | 0.220 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".