Evolving Trends in Physiotherapy Research Publications between 1995 and 2015
Bibliographic record
Abstract
Purpose: The aim of this study was to comparatively analyze evolving trends in physiotherapy (PT) research publications (excluding case reports and epidemiological and qualitative studies) between 1995 and 2015, inclusively in terms of research design, funding support, age groups, and health conditions. Method: This was an observational study using PubMed-indexed data. Combinations of medical subject headings identified yearly research publications for PT and comparator fields: human-based health and physical rehabilitation. Yearly publications data were extracted, relative percentages were computed, and linear or exponential regressions examined the yearly growth in the proportion of research publications over these 2 decades. Results: As a percentage of human-based health research publications, PT research publications grew exponentially: from 0.54% in 1995 to 2.37% in 2015 ( r² = 0.97; p < 0.01). As a percentage of physical rehabilitation research publications, PT research grew from 38.2% in 1995 to 58.7% in 2015 ( r² = 0.89; p < 0.01). Randomized controlled trials (RCTs) resulted in the majority of PT research publications (from 45.1% in 1995 to 59.4% in 2015; r² = 0.79; p < 0.01). Rates of declared funding increased (from 29.7% in 1995 to 57% in 2015; r² = 0.83; p < 0.01), but the comparator fields had similar growth. The percentage of PT research publications remained stable for most health conditions and age groups, decreased for those aged 0–18 years ( p = 0.012) and for cardiovascular and pulmonary conditions (both p < 0.01), and increased for neoplasms ( p < 0.01). Conclusions: PT research publications have become more prevalent among health and physical rehabilitation research publications; the majority of publications report on RCTs.
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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 | 0.022 | 0.125 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.036 | 0.047 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".