Research trends in manual therapy: a bibliometric review of the last 10 years
Why this work is in the frame
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Bibliographic record
Abstract
Manual therapy (MT) is a dynamic entity progressing rapidly. The current trend stimulates a direction toward higher specificity in the research. This is the first bibliometric review to identify the trends in MT in the last ten years (till 2023). The Scopus database was selected to retrieve the bibliographic records. Biblioshiny (Bibliometrix), PowerBI, MS Excel, and MS Access were used to visualize and analyze the results. 1208 relevant studies were included in the analysis. Publishing has a rising character. The four-author articles are the most common, while only 68 are single-author studies. In 2021, the highest number of publications (n=178) was published. The Journal of Bodywork and Movement Therapies has published the highest number of publications (75). The USA is the most prolific country in publishing (361 studies) and total citations (4869). Universidad Rey Juan Carlos (Spain) is the most productive and cited institution. Fernández-De-Las-Peñas C. is the most productive, and Mark D. Bishop is the most cited author. The USA, Australia, Canada, and European countries have the most frequent collaborations. MT was the most common research focus from 2017 to 2019. The topics of exercise therapy, musculoskeletal therapy, physical therapy, and physiotherapy have been the focus of research in the context of MT lately. The present study reported the research-related trends in MT applying bibliometric methods and identified the most productive countries, institutions, and researchers over the past decade. These findings are intended to assist the researchers in better orientation in the research field and to specify the trends for future research studies. Keywords: Manual therapy; physiotherapy; research trends; bibliometrics; thematic evolution; research collaboration
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.029 | 0.114 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it