Thirty years of research on traumatic brain injury rehabilitation: a bibliometric study
Bibliographic record
Abstract
Background Traumatic brain injury (TBI) is a major public health concern with far-reaching consequences on individuals’ lives. Despite the abundance of works published on TBI rehabilitation, few studies have bibliometrically analyzed the published TBI rehabilitation research. This study aims to characterize current international trends and global productivity by analyzing articles on TBI rehabilitation using bibliometric approaches and visualization methods. Methods We conducted a bibliometric analysis of data retrieved and extracted from the Web of Science Core Collection database to examine the evolution and thematic trends in TBI rehabilitation research up until December 31, 2022. The specific characteristics of the research articles on TBI rehabilitation were evaluated, such as publication year, countries/regions, institutions, authors, journals, research fields, references, and keywords. Results Our analysis identified 5,541 research articles on TBI rehabilitation and observed a progressive increase in publications and citations over the years. The United States (US, 2,833, 51.13%), Australia (727, 13.12%), and Canada (525, 9.47%) were the most prolific countries/regions. The University of Washington (226, 4.08%) and Hammond FM (114, 2.06%) were the most productive institution and author, respectively. The top three productive journals were Brain Injury (862; 15.56%), Archives of Physical Medicine and Rehabilitation (630; 11.37%), and Journal of Head Trauma Rehabilitation (405, 7.31%). The most frequent research fields were Rehabilitation, Neurosciences, and Clinical Neurology. Co-citation references primarily addressed “outcome assessment,” “community integration” and “TBI management,” and “injury chronicity” and “sequelae” have gained more attention in recent years. “Mild TBI,” “outcome,” “stroke” and “children” were the commonly used keywords. Additionally, the analysis unveiled emerging research frontiers, including “return to work,” “disorder of consciousness,” “veterans,” “mild TBI,” “pediatric,” “executive function” and “acquired brain injury.” Conclusion This study provides valuable insights into the current state of TBI rehabilitation research, which has experienced a rapid increase in attention and exponential growth in publications and citations in the last three decades. TBI rehabilitation research is characterized by its multi-disciplinary approach, involving fields such as Rehabilitation, Neurosciences, and Clinical Neurology. The analysis revealed emerging research subjects that could inform future research directions.
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 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 | 0.013 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.136 | 0.205 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".