Exercise Interventions for Metabolic Diseases: An Analysis of the Evolution of Aerobic Exercise Bibliometrics in the Field of Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Background: Type 2 diabetes mellitus (T2DM) is a major global public health challenge. Aerobic exercise (AE) can be a key strategy for non-pharmacological intervention in T2DM through multi-targeted modulation of glucose and lipid metabolism, inhibition of chronic inflammation, and reduction of oxidative stress. This study aims to investigate the current status of AE intervention in T2DM research and analyze its future evolution. Methods: Using the R-based bibliometric software package and the Java-based visualization software CiteSpace and VOSviewer, we analyzed the literature and cited references related to AE intervention in T2DM research included in the Web of Science Core Collection (WOSCC) and China National Knowledge Infrastructure (CNKI) from 2014 to 2024. Results: This study included a total of 882 relevant literature sources (488 of which were indexed in WOSCC and 394 in CNKI). From the perspective of research trends, the number of literature sources on AE interventions for T2DM has shown fluctuating changes over time. In terms of research output, the United States, China, and Canada are at the forefront. It is worth noting that, although China has a relatively high number of published papers, there is still a significant gap in terms of the depth of international collaboration and the presentation of results in top-tier journals. Among researchers, Dai Xia (China) and Riddell MC (Canada) are the scholars with the highest number of published articles in this field. Keyword analysis indicates that mechanisms such as oxidative stress, insulin resistance, inflammatory responses, and glucose metabolism disorders remain core research hotspots. Time-series analysis reveals that the research paradigm in this field has evolved from single exercise methods to comprehensive exercise prescription studies, and multi-dimensional intervention studies combining exercise, diet, and pharmacological interventions are emerging as new research frontiers. Conclusions: This study uses bibliometric methods to visualize and analyze the progress of AE in T2DM intervention research from a broader perspective, providing a scientific overview and macro-level predictions for the research landscape in this field.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.002 |
| Bibliometrics | 0.008 | 0.030 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".