Bibliometric Analysis of Global Research on Perinatal Palliative Care
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to perform a bibliometric analysis of publications related to perinatal palliative care to identify scientific output and research trends at a global level. METHODS: The Web of Science Core Collection database was searched to retrieve publications focusing on perinatal palliative care published between 2001 and 2020. All retrieved publications were identified by title and abstract for their relevance to perinatal palliative care. These eligible publications were extracted from the following data: title, abstract, year, keywords, author, organization, journal and cited literature. VOSviewer software was used to conduct bibliographic coupling, coauthorship, and cooccurrence analyses and to detect publication trends in perinatal palliative care research. RESULTS: A total of 114 publications concerning perinatal palliative care were included. The annual number of publications has increased dramatically in recent years. The United States has made the largest contribution to this field with the majority of publications (68, 59.6%) and citations (1,091, 70.5%) and with close collaborations with researchers in Canada, Portugal and Australia. Wool C and her institution, York College of Pennsylvania, are the respectively, most prolific author and institution in this field, publishing 18 papers (15.8%). Journal of Palliative Medicine is the leading and main journal in this field. According to the cooccurrence network analysis, five main research topics were identified: the candidates for PPC, service models and forms, framework components, parental perspectives and satisfaction, and challenges and needs of health care providers. CONCLUSION: The findings of this bibliometric study illustrate the current state and global trends of perinatal palliative care for the past two decades, which will help researchers determine areas of research focus and explore new directions for future research in this field.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.166 | 0.493 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".