The state of nursing research from 2000 to 2019: A global analysis
Bibliographic record
Abstract
AIM: This study aims to present a general bibliometric overview of the development status of global nursing research from 2000 to 2019. DESIGN: A longitudinal bibliometric analysis of nursing research was conducted. METHODS: Nursing research publications (N = 88,665) were obtained from Web of Science. Bibliometric method was used to map the output and citation impact trends of countries/regions, institutions, disciplines, and journals and analyse the research collaboration among countries/regions and institutions. RESULTS: The global paper output in nursing research increased steadily over the past two decades and it varied in different countries/regions with the USA being far ahead of the others. The paper output and cross-border collaboration are mainly distributed in several developed countries like the USA, the UK, Australia, and Canada. The University of Pennsylvania, Harvard University, University of Toronto, and University of North Carolina at Chapel Hill have high academic influence in the field of nursing. Increasing attention from academic fields has been paid to research on nursing. Journal of Advanced Nursing is the most prolific and most cited journal in nursing field. CONCLUSION: Nursing research has developed steadily over the last two decades. Both the scientific output and research collaboration are disproportionally distributed between high-income countries/regions and low- and middle-income countries/regions. Most research and collaboration have taken place in a few developed countries across North America, Europe, and Oceania. IMPACT: The study highlighted the need for policy makers and funding agencies, especially those from low- and middle-income countries/regions, to allocate research funding that supports the nursing higher education and international cooperation so as to promote the development of high-quality nursing research in those countries/regions. At the same time, researchers from non-English-speaking countries/regions should attach more importance to publishing papers in English, strengthening the academic exchanges with international nursing colleagues and better integrating into the international academic community.
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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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.041 | 0.084 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".