A Bibliometric Analysis of Nursing Research in the Field of Refugee Health Between 1980 and 2024
Bibliographic record
Abstract
AIM: This study aimed to examine the bibliographic characteristics of publications on refugees in the nursing field. DESIGN: A bibliometric analysis design was adopted for the study. SAMPLE: Included the articles scanned in the Web of Science Core Collection database. The study excluded the other databases and gray literature. MEASUREMENTS: The 2120 articles published between 1980 and 2024 that met the inclusion criteria were analyzed using Bibliometrix in RStudio, VOSviewer, and Microsoft Excel software. RESULTS: The majority of publications were published in 2024. The United Kingdom, the United States, Canada, and Australia have the highest publications, citations, and international cooperation. Additionally, "mental health" is one of the most frequently used keywords in studies. CONCLUSIONS: The increased migration rates and the growing need for healthcare for refugees underscore the importance of investing in nursing research within this field. Nurses and researchers should establish partnerships and share best practices with leading countries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.120 | 0.414 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".