A Scientometric Overview of the Current Status and Trends of Holistic Nursing Studies
Bibliographic record
Abstract
Holistic nursing care, which has been discussed a lot recently, provides better quality and more effective patient care. This study was planned to analyze the studies conducted on holistic care, by using the bibliometric method and to reveal which types of studies are needed to increase the effectiveness of holistic nursing care and to make it more widespread. The study has the potential to guide scientists who would like to work on this subject. This study describes the current published evidence about holistic nursing between January,1, 1979 and March 18, 2023. The study's data obtained from the Web of Science (WOS) database were analyzed using both quantitative and qualitative measures. The Excel program was used to analyze the study's data, and VOSviewer was used to visualize it. A total of 3887 publications (reviews and articles) obtained in the search for holistic nursing have been published. A total of 2716 (69 875%) of all publications on holistic nursing were published since 2013, and these publications were cited 45 843 times, and 77.832% of all citations were cited to publications published since 2013. The top 5 countries that made the highest number of contributions were the United States (1259 documents), England (457 documents), Australia (380 documents), Canada (253 documents), and Sweden (183 documents). The University of London in England was the top institute focused on holistic nursing. Holistic nursing is a growing and developing subject, especially considering the number of citations and publications in the last 10 years. Most research and cooperation has occurred in a few developed nations: America, Australia, and European 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 | 0.001 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".