Interdisciplinary Insights and Global Perspectives on ADHD in Children: A Comprehensive Bibliometric Analysis (2014–2024)
Bibliographic record
Abstract
This study used bibliometric analysis to investigate the research on Attention-Deficit/Hyperactivity Disorder (ADHD) in pediatric populations between January 2014 and January 2024. The Scopus database is utilized to gather a diverse array of scholarly research on this complex ailment. Our objective was to compile a comprehensive dataset on understanding and managing ADHD by selecting specific terms such as “ADHD in Children”, “ADHD Treatment and Management”, and “Attention-Deficit/Hyperactivity Disorder”. We utilized the advanced analytical capabilities of Biblioshiny (bibliometrix R-package) and VOSviewer (VOSviewer version 1.6.19), within our methodological framework, to do network analysis. By conducting this analysis, we were able to examine patterns in publications, author affiliations, the geographic spread of research, and identify influential texts and developing research topics. The findings underscore the collaborative endeavors of medicine, psychology, and neuroscience in tackling the physiological and psychological aspects of ADHD, with a focus on interdisciplinary contributions. The extensive global impact of ADHD research is highlighted by the significant contributions made by countries including the United States, China, the UK, the Netherlands, and Canada. Our data indicates a notable shift towards holistic strategies that encompass socioeconomic, environmental, and behavioral aspects, alongside emerging practices like the utilization of non-invasive brain stimulation techniques in research. This bibliometric study offers a comprehensive view of ADHD research by identifying significant patterns and clusters of themes. It illuminates the shifts in scientific conversation over time and identifies areas that show potential for additional research. The study advocates for ongoing collaboration across various disciplines and nations, emphasizing the significance of innovative strategies to enhance the well-being of those affected by ADHD.
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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: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | high |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.232 | 0.301 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".