Evolution of the thematic structure and main producers of physical therapy interventions research: A bibliometric analysis (1986 to 2017)
Bibliographic record
Abstract
BACKGROUND: Bibliometric studies are used to analyse and map scientific areas, and study the scientific output and impact of institutes and countries. OBJECTIVES: Describe the thematic structure and evolution of the field of physical therapy interventions using articles indexed in Physiotherapy Evidence Database (PEDro). Also, identify and compare the main producers (countries, institutions) over time (research output, citation impact). METHODS: Eligible articles were those indexed in PEDro (1986-2017) and matched to Web of Science. VOSviewer software, bibliometric text mining, and visualisation techniques were used to evaluate the thematic structure of the included articles. We collected data about authors' country and institutional affiliation, and calculated bibliometric indicators (production, citation impact). RESULTS: A total of 29 090 articles were analysed. Eight topics were identified: "neurological rehabilitation"; "methods"; "exercise for prevention and rehabilitation of lifestyle diseases"; "assessment and treatment of musculoskeletal pain"; "physical activity", "health promotion and behaviour change"; "respiratory physical therapy"; "hospital, primary care and health economics"; "cancer and complementary therapies". The most productive countries were United States, United Kingdom, Australia, and Canada. The most impactful countries were United States, France, Finland, and Canada. The most productive institutions were University of Sydney, VU University of Amsterdam, University of Queensland, and University of Toronto. CONCLUSIONS: The thematic structure of physical therapy interventions has evolved over time with "neurological rehabilitation", "methods", "exercise related to lifestyle diseases", and "physical activity" becoming increasingly important. Main producers of this research were traditionally located in North America and Europe but now include countries like China and Brazil.
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 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 | 0.018 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.285 | 0.726 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 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".