Current Trends in Chronic Non-Communicable Disease Management: A Bibliometric Analysis of the Past Two Decades
Bibliographic record
Abstract
Background: In recent years, there has been a growing focus on chronic non-communicable diseases (NCD) and their impact on personal and social health. Effective management of NCD is essential for their prevention and treatment. This study aims to utilize bibliometric methods to analyze and summarize the current development and emerging trends in NCD management. Methods: A literature search and screening were conducted on the Web of Science Core Collection database from January 1, 2004, to December 31, 2023. VOSviewer and Citespace software was performed to examine publication volume, authors, institutions, countries, journals, citation frequencies, keywords, clustering, and burst terms, and to create a visual map. Results: A total of 996 valid publications from 464 journals were included in the study. The number of publications exhibited a gradual growth trend over the years. The United States was the most productive and influential country, contributing the highest proportion of both publications and total citations. BMC Health Services Research, Toronto University, and Marshall, Bruce C. were identified as the most productive journal, institution, and author, respectively. Further analysis of keyword co-occurrence and burst detection revealed that the most prevalent keywords were "improving primary care" and "integrated care". Conclusion: This bibliometric analysis provides a comprehensive overview of the current status and trends in NCD management over the past two decades, providing valuable insights for future research directions. It indicates a potential shift towards enhancing primary healthy care, integrated care, and digital health.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.055 | 0.118 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".