Inclusive Healthcare System for Children with Disabilities: A Bibliometric Analysis and Visualization
Bibliographic record
Abstract
BACKGROUND: Children with disabilities face complex, systemic health access barriers rooted in societal, institutional, and structural inequities, requiring urgent global policy attention. Publications on access to health services for this population category have been found to have a significant growth in both quantity and content. The article aims to examine the structure and evolution of scientific literature in analyzing the healthcare system through the lens of inclusive services. METHODS: We present the bibliometric profile of the global literature on access to health services for children with disabilities, the publication trends, the structure of research in this field concerning geographical distribution, methodological approaches, and interdisciplinary collaborations, and the core research topics, conceptual clusters, and future research directions in the field. The publications were screened from Web of Science databases, using PRISMA methodology. Finally, 1100 academic publications published between 1984 and 2025, obtained from a total of 432 different sources, the majority of which were peer-reviewed journals, were screened. RESULTS: The calculated annual publication growth rate of 8.37% and the distinct upward trend observed, especially after 2015. The highest level was reached in 2023, with over 90 publications showing that the topic has become a focus of international academic interest. The USA (33.5%), the United Kingdom (15.7%), Australia (9.5%), and Canada (9.5%) stood out in publications, and there were strong collaborative networks among European nations (8.2%). CONCLUSIONS: Although high-income countries still appear to play a dominant role in research production, expanding international collaborations and distributing resources more equitably will contribute to the development of more inclusive solutions on a global scale. Temporal trends show an evolution toward diagnostic processes, family-centered approaches, and psychosocial dimensions. The results draw a clear picture of the current research landscape regarding access to health services for pediatric disability populations and identify potential directions for future research.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.051 | 0.140 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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, 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".